Effect of Annealing on Microstructure, Texture and Tensile Properties of Twin-Roll Cast AZ31B

NASA Astrophysics Data System (ADS)

Masoumi, Mohsen; Zarandi, Faramarz; Pekguleryuz, Mihriban O.

Twin-roll cast (TRC) AZ31 alloy (Mg-3wt.%Al-1wt.%Zn) was subjected to heat treatment at 420 °C. As a result, the intensity of the original basal texture was reduced considerably. Crystallographic orientation analysis revealed that such a change in the texture is due to particle-stimulated nucleation of new grains with random orientations. The tensile test results indicate that annealing slightly increases ultimate tensile strength (UTS), however, dramatically improves the elongation.

Influence of Femtosecond Laser Parameters and Environment on Surface Texture Characteristics of Metals and Non-Metals - State of the Art

NASA Astrophysics Data System (ADS)

Bharatish, A.; Soundarapandian, S.

2018-04-01

Enhancing the surface functionality by ultrashort pulsed laser texturing has received the considerable attention from researchers in the past few decades. Femtosecond lasers are widely adopted since it provides high repeatability and reproducibility by minimizing the heat affected zone (HAZ) and other collateral damages to a great extent. The present paper reports some recent studies being made worldwide on femtosecond laser surface texturing of metals, ceramics, polymers, semiconductors, thinfilms and advanced nanocomposites. It presents the state of the art knowledge in femtosecond laser surface texturing and the potential of this technology to improve properties in terms of biological, tribological and wetting performance. Since the texture quality and functionality are enhanced by the proper selection of appropriate laser parameters and ambient conditions for individual application, reporting the influence of laser parameters on surface texture characteristics assume utmost importance.

Influence of Femtosecond Laser Parameters and Environment on Surface Texture Characteristics of Metals and Non-Metals - State of the Art

NASA Astrophysics Data System (ADS)

Bharatish, A.; Soundarapandian, S.

2018-06-01

Enhancing the surface functionality by ultrashort pulsed laser texturing has received the considerable attention from researchers in the past few decades. Femtosecond lasers are widely adopted since it provides high repeatability and reproducibility by minimizing the heat affected zone (HAZ) and other collateral damages to a great extent. The present paper reports some recent studies being made worldwide on femtosecond laser surface texturing of metals, ceramics, polymers, semiconductors, thinfilms and advanced nanocomposites. It presents the state of the art knowledge in femtosecond laser surface texturing and the potential of this technology to improve properties in terms of biological, tribological and wetting performance. Since the texture quality and functionality are enhanced by the proper selection of appropriate laser parameters and ambient conditions for individual application, reporting the influence of laser parameters on surface texture characteristics assume utmost importance.

Revisiting elastic anisotropy of biotite gneiss from the Outokumpu scientific drill hole based on new texture measurements and texture-based velocity calculations

NASA Astrophysics Data System (ADS)

Wenk, H.-R.; Vasin, R. N.; Kern, H.; Matthies, S.; Vogel, S. C.; Ivankina, T. I.

2012-10-01

A sample of biotite gneiss from the Outokumpu deep drilling project in Finland was investigated by Kern et al. (2008) for crystal preferred orientation and elastic anisotropy. Considerable differences between measured acoustic velocities and velocities calculated on the basis of texture patterns were observed. Measured P-wave anisotropy was 15.1% versus a Voigt average yielding 7.9%. Here we investigate the same sample with different methods and using different averaging techniques. Analyzing time-of-flight neutron diffraction data from Dubna-SKAT and LANSCE-HIPPO diffractometers with the Rietveld technique, much stronger preferred orientation for biotite is determined, compared to conventional pole-figure analysis reported previously. The comparison reveals important differences: HIPPO has much better counting statistics but pole figure coverage is poor. SKAT has better angular resolution. Using the new preferred orientation data and applying a self-consistent averaging method that takes grain shapes into account, close agreement of calculated and measured P-wave velocities is observed (12.6%). This is further improved by adding 0.1 vol.% flat micropores parallel to the biotite platelets in the simulation (14.9%).

Texture operator for snow particle classification into snowflake and graupel

NASA Astrophysics Data System (ADS)

Nurzyńska, Karolina; Kubo, Mamoru; Muramoto, Ken-ichiro

2012-11-01

In order to improve the estimation of precipitation, the coefficients of Z-R relation should be determined for each snow type. Therefore, it is necessary to identify the type of falling snow. Consequently, this research addresses a problem of snow particle classification into snowflake and graupel in an automatic manner (as these types are the most common in the study region). Having correctly classified precipitation events, it is believed that it will be possible to estimate the related parameters accurately. The automatic classification system presented here describes the images with texture operators. Some of them are well-known from the literature: first order features, co-occurrence matrix, grey-tone difference matrix, run length matrix, and local binary pattern, but also a novel approach to design simple local statistic operators is introduced. In this work the following texture operators are defined: mean histogram, min-max histogram, and mean-variance histogram. Moreover, building a feature vector, which is based on the structure created in many from mentioned algorithms is also suggested. For classification, the k-nearest neighbourhood classifier was applied. The results showed that it is possible to achieve correct classification accuracy above 80% by most of the techniques. The best result of 86.06%, was achieved for operator built from a structure achieved in the middle stage of the co-occurrence matrix calculation. Next, it was noticed that describing an image with two texture operators does not improve the classification results considerably. In the best case the correct classification efficiency was 87.89% for a pair of texture operators created from local binary pattern and structure build in a middle stage of grey-tone difference matrix calculation. This also suggests that the information gathered by each texture operator is redundant. Therefore, the principal component analysis was applied in order to remove the unnecessary information and additionally reduce the length of the feature vectors. The improvement of the correct classification efficiency for up to 100% is possible for methods: min-max histogram, texture operator built from structure achieved in a middle stage of co-occurrence matrix calculation, texture operator built from a structure achieved in a middle stage of grey-tone difference matrix creation, and texture operator based on a histogram, when the feature vector stores 99% of initial information.

Artificial in-plane ordering of textured YBa2Cu3O(7-x) films deposited on polycrystalline yttria-stabilized zirconia substrates

NASA Astrophysics Data System (ADS)

Harshavardhan, K. S.; Rajeswari, M.; Hwang, D. M.; Chen, C. Y.; Sands, T. D.; Venkatesan, T.; Tkaczyk, J. E.; Lay, K. W.; Safari, A.; Johnson, L.

1992-12-01

Anisotropic surface texturing of the polycrystalline yttria-stabilized zirconia substrates, prior to YBa2Cu3O(7-x) film deposition, is shown to promote in-plane (basal plane) ordering of the film growth in addition to the c-axis texturing. The Jc's of the films in the weak-link-dominated low-field regime are enhanced considerably, and this result is attributed to the reduction of weak links resulting from a reduction in the number of in-plane large-angle grain boundaries.

Detection of pavement cracks using tiled fuzzy Hough transform

NASA Astrophysics Data System (ADS)

Mathavan, Senthan; Vaheesan, Kanapathippillai; Kumar, Akash; Chandrakumar, Chanjief; Kamal, Khurram; Rahman, Mujib; Stonecliffe-Jones, Martyn

2017-09-01

Surface cracks can be the bellwether of the failure of a road. Hence, crack detection is indispensable for the condition monitoring and quality control of road surfaces. Pavement images have high levels of intensity variation and texture content; hence, the crack detection is generally difficult. Moreover, shallow cracks are very low contrast, making their detection difficult. Therefore, studies on pavement crack detection are active even after years of research. The fuzzy Hough transform is employed, for the first time, to detect cracks from pavement images. A careful consideration is given to the fact that cracks consist of near straight segments embedded in a surface of considerable texture. In this regard, the fuzzy part of the algorithm tackles the segments that are not perfectly straight. Moreover, tiled detection helps reduce the contribution of texture and noise pixels to the accumulator array. The proposed algorithm is compared against a state-of-the-art algorithm for a number of crack datasets, demonstrating its strengths. Precision and recall values of more than 75% are obtained, on different image sets of varying textures and other effects, captured by industrial pavement imagers. The paper also recommends numerical values for parameters used in the proposed method.

Influence of stewing time on the texture, ultrastructure and in vitro digestibility of meat from the yellow-feathered chicken breed.

PubMed

Qi, Jun; Li, Xiao; Zhang, Wenwen; Wang, Huhu; Zhou, Guanghong; Xu, Xinglian

2018-02-01

This study assessed the influence of stewing (1, 2 or 3 h) on the texture, ultrastructure and in vitro digestibility of meat from the yellow-feathered chicken, which is a popular broiler chicken in Asia. Results indicated that longer stewing considerably increased cooking loss of the chicken carcass and tenderness of thigh meat. After 3 h of stewing, protein digestibility decreased from 90.5% to 80.3% and fiber diameter decreased by 8.63 μm. The shear force value of breast meat decreased from 32.34 N at 1 h to 10.29 N at 2 h, and then increased to 39.98 N at 3 h. The texture profile of breast meat remarkably decreased during stewing. Moreover, increased stewing time induced longitudinal and transversal shrinkage of muscle fibers and the degradation of the myosin heavy chain. These findings suggested that prolonged stewing (3 h) resulted in decreased meat qualities, based on the changes in cooking loss, digestibility and texture profile, but that stewing for 2 h increased thigh and breast tenderness. Producers could utilize this information to stew yellow-feathered chicken meat with desirable qualities. © 2017 Japanese Society of Animal Science.

Enhanced photon management in silicon thin film solar cells with different front and back interface texture

PubMed Central

Tamang, Asman; Hongsingthong, Aswin; Jovanov, Vladislav; Sichanugrist, Porponth; Khan, Bakhtiar A.; Dewan, Rahul; Konagai, Makoto; Knipp, Dietmar

2016-01-01

Light trapping and photon management of silicon thin film solar cells can be improved by a separate optimization of the front and back contact textures. A separate optimization of the front and back contact textures is investigated by optical simulations taking realistic device geometries into consideration. The optical simulations are confirmed by experimentally realized 1 μm thick microcrystalline silicon solar cells. The different front and back contact textures lead to an enhancement of the short circuit current by 1.2 mA/cm2 resulting in a total short circuit current of 23.65 mA/cm2 and an energy conversion efficiency of 8.35%. PMID:27481226

Field-Scale Evaluation of Infiltration Parameters From Soil Texture for Hydrologic Analysis

NASA Astrophysics Data System (ADS)

Springer, Everett P.; Cundy, Terrance W.

1987-02-01

Recent interest in predicting soil hydraulic properties from simple physical properties such as texture has major implications in the parameterization of physically based models of surface runoff. This study was undertaken to (1) compare, on a field scale, soil hydraulic parameters predicted from texture to those derived from field measurements and (2) compare simulated overland flow response using these two parameter sets. The parameters for the Green-Ampt infiltration equation were obtained from field measurements and using texture-based predictors for two agricultural fields, which were mapped as single soil units. Results of the analyses were that (1) the mean and variance of the field-based parameters were not preserved by the texture-based estimates, (2) spatial and cross correlations between parameters were induced by the texture-based estimation procedures, (3) the overland flow simulations using texture-based parameters were significantly different than those from field-based parameters, and (4) simulations using field-measured hydraulic conductivities and texture-based storage parameters were very close to simulations using only field-based parameters.

Association between pathology and texture features of multi parametric MRI of the prostate

NASA Astrophysics Data System (ADS)

Kuess, Peter; Andrzejewski, Piotr; Nilsson, David; Georg, Petra; Knoth, Johannes; Susani, Martin; Trygg, Johan; Helbich, Thomas H.; Polanec, Stephan H.; Georg, Dietmar; Nyholm, Tufve

2017-10-01

The role of multi-parametric (mp)MRI in the diagnosis and treatment of prostate cancer has increased considerably. An alternative to visual inspection of mpMRI is the evaluation using histogram-based (first order statistics) parameters and textural features (second order statistics). The aims of the present work were to investigate the relationship between benign and malignant sub-volumes of the prostate and textures obtained from mpMR images. The performance of tumor prediction was investigated based on the combination of histogram-based and textural parameters. Subsequently, the relative importance of mpMR images was assessed and the benefit of additional imaging analyzed. Finally, sub-structures based on the PI-RADS classification were investigated as potential regions to automatically detect maligned lesions. Twenty-five patients who received mpMRI prior to radical prostatectomy were included in the study. The imaging protocol included T2, DWI, and DCE. Delineation of tumor regions was performed based on pathological information. First and second order statistics were derived from each structure and for all image modalities. The resulting data were processed with multivariate analysis, using PCA (principal component analysis) and OPLS-DA (orthogonal partial least squares discriminant analysis) for separation of malignant and healthy tissue. PCA showed a clear difference between tumor and healthy regions in the peripheral zone for all investigated images. The predictive ability of the OPLS-DA models increased for all image modalities when first and second order statistics were combined. The predictive value reached a plateau after adding ADC and T2, and did not increase further with the addition of other image information. The present study indicates a distinct difference in the signatures between malign and benign prostate tissue. This is an absolute prerequisite for automatic tumor segmentation, but only the first step in that direction. For the specific identified signature, DCE did not add complementary information to T2 and ADC maps.

Computer-based objective quantitative assessment of pulmonary parenchyma via x-ray CT

NASA Astrophysics Data System (ADS)

Uppaluri, Renuka; McLennan, Geoffrey; Sonka, Milan; Hoffman, Eric A.

1998-07-01

This paper is a review of our recent studies using a texture- based tissue characterization method called the Adaptive Multiple Feature Method. This computerized method is automated and performs tissue classification based upon the training acquired on a set of representative examples. The AMFM has been applied to several different discrimination tasks including normal subjects, subjects with interstitial lung disease, smokers, asbestos-exposed subjects, and subjects with cystic fibrosis. The AMFM has also been applied to data acquired using different scanners and scanning protocols. The AMFM has shown to be successful and better than other existing techniques in discriminating the tissues under consideration. We demonstrate that the AMFM is considerably more sensitive and specific in characterizing the lung, especially in the presence of mixed pathology, as compared to more commonly used methods. Evidence is presented suggesting that the AMFM is highly sensitive to some of the earliest disease processes.

Development and testing of texture discriminators for the analysis of trabecular bone in proximal femur radiographs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huber, M. B.; Carballido-Gamio, J.; Fritscher, K.

2009-11-15

Purpose: Texture analysis of femur radiographs may serve as a potential low cost technique to predict osteoporotic fracture risk and has received considerable attention in the past years. A further application of this technique may be the measurement of the quality of specific bone compartments to provide useful information for treatment of bone fractures. Two challenges of texture analysis are the selection of the best suitable texture measure and reproducible placement of regions of interest (ROIs). The goal of this in vitro study was to automatically place ROIs in radiographs of proximal femur specimens and to calculate correlations between variousmore » different texture analysis methods and the femurs' anchorage strength. Methods: Radiographs were obtained from 14 femoral specimens and bone mineral density (BMD) was measured in the femoral neck. Biomechanical testing was performed to assess the anchorage strength in terms of failure load, breakaway torque, and number of cycles. Images were segmented using a framework that is based on the usage of level sets and statistical in-shape models. Five ROIs were automatically placed in the head, upper and lower neck, trochanteric, and shaft compartment in an atlas subject. All other subjects were registered rigidly, affinely, and nonlinearly, and the resulting transformation was used to map the five ROIs onto the individual femora. Results: In each ROI, texture features were extracted using gray level co-occurence matrices (GLCM), third-order GLCM, morphological gradients (MGs), Minkowski dimensions (MDs), Minkowski functionals (MFs), Gaussian Markov random fields, and scaling index method (SIM). Coefficients of determination for each texture feature with parameters of anchorage strength were computed. In a stepwise multiregression analysis, the most predictive parameters were identified in different models. Texture features were highly correlated with anchorage strength estimated by the failure load of up to R{sup 2}=0.61 (MF and MG features, p<0.01) and were partially independent of BMD. The correlations were dependent on the choice of the ROI and the texture measure. The best predictive multiregression model for failure load R{sub adj}{sup 2}=0.86 (p<0.001) included a set of recently developed texture methods (MF and SIM) but excluded bone mineral density and commonly used texture measures. Conclusions: The results suggest that texture information contained in trabecular bone structure visualized on radiographs may predict whether an implant anchorage can be used and may determine the local bone quality from preoperative radiographs.« less

Through-process modelling of texture and anisotropy in AA5182

NASA Astrophysics Data System (ADS)

Crumbach, M.; Neumann, L.; Goerdeler, M.; Aretz, H.; Gottstein, G.; Kopp, R.

2006-07-01

A through-process texture and anisotropy prediction for AA5182 sheet production from hot rolling through cold rolling and annealing is reported. Thermo-mechanical process data predicted by the finite element method (FEM) package T-Pack based on the software LARSTRAN were fed into a combination of physics based microstructure models for deformation texture (GIA), work hardening (3IVM), nucleation texture (ReNuc), and recrystallization texture (StaRT). The final simulated sheet texture was fed into a FEM simulation of cup drawing employing a new concept of interactively updated texture based yield locus predictions. The modelling results of texture development and anisotropy were compared to experimental data. The applicability to other alloys and processes is discussed.

Effect of layerwise structural inhomogeneity on stress- corrosion cracking of steel tubes

NASA Astrophysics Data System (ADS)

Perlovich, Yu A.; Krymskaya, O. A.; Isaenkova, M. G.; Morozov, N. S.; Fesenko, V. A.; Ryakhovskikh, I. V.; Esiev, T. S.

2016-04-01

Based on X-ray texture and structure analysis data of the material of main gas pipelines it was shown that the layerwise inhomogeneity of tubes is formed during their manufacturing. The degree of this inhomogeneity affects on the tendency of tubes to stress- corrosion cracking under exploitation. Samples of tubes were cut out from gas pipelines located under various operating conditions. Herewith the study was conducted both for sections with detected stress-corrosion defects and without them. Distributions along tube wall thickness for lattice parameters and half-width of X-ray lines were constructed. Crystallographic texture analysis of external and internal tube layers was also carried out. Obtained data testifies about considerable layerwise inhomogeneity of all samples. Despite the different nature of the texture inhomogeneity of gas pipeline tubes, the more inhomogeneous distribution of texture or structure features causes the increasing of resistance to stress- corrosion. The observed effect can be explained by saturation with interstitial impurities of the surface layer of the hot-rolled sheet and obtained therefrom tube. This results in rising of lattice parameters in the external layer of tube as compared to those in underlying metal. Thus, internal layers have a compressive effect on external layers in the rolling plane that prevents cracks opening at the tube surface. Moreover, the high mutual misorientation of grains within external and internal layers of tube results in the necessity to change the moving crack plane, so that the crack growth can be inhibited when reaching the layer with a modified texture.

Texture-based segmentation and analysis of emphysema depicted on CT images

NASA Astrophysics Data System (ADS)

Tan, Jun; Zheng, Bin; Wang, Xingwei; Lederman, Dror; Pu, Jiantao; Sciurba, Frank C.; Gur, David; Leader, J. Ken

2011-03-01

In this study we present a texture-based method of emphysema segmentation depicted on CT examination consisting of two steps. Step 1, a fractal dimension based texture feature extraction is used to initially detect base regions of emphysema. A threshold is applied to the texture result image to obtain initial base regions. Step 2, the base regions are evaluated pixel-by-pixel using a method that considers the variance change incurred by adding a pixel to the base in an effort to refine the boundary of the base regions. Visual inspection revealed a reasonable segmentation of the emphysema regions. There was a strong correlation between lung function (FEV1%, FEV1/FVC, and DLCO%) and fraction of emphysema computed using the texture based method, which were -0.433, -.629, and -0.527, respectively. The texture-based method produced more homogeneous emphysematous regions compared to simple thresholding, especially for large bulla, which can appear as speckled regions in the threshold approach. In the texture-based method, single isolated pixels may be considered as emphysema only if neighboring pixels meet certain criteria, which support the idea that single isolated pixels may not be sufficient evidence that emphysema is present. One of the strength of our complex texture-based approach to emphysema segmentation is that it goes beyond existing approaches that typically extract a single or groups texture features and individually analyze the features. We focus on first identifying potential regions of emphysema and then refining the boundary of the detected regions based on texture patterns.

Large Strain Behaviour of ZEK100 Magnesium Alloy at Various Strain Rates

NASA Astrophysics Data System (ADS)

Lévesque, Julie; Kurukuri, Srihari; Mishra, Raja; Worswick, Michael; Inal, Kaan

A constitutive framework based on a rate-dependent crystal plasticity theory is employed to simulate large strain deformation in hexagonal closed-packed metals that deform by slip and twinning. The model allows the twinned zones and the parent matrix to rotate independently. ZEK100 magnesium alloy sheets which significant texture weakening compared to AZ31 sheets are investigated using the model. There is considerable in-plane anisotropy and tension compression asymmetry in the flow behavior of ZEK100. Simulations of uniaxial tension in different directions at various strain rates and the accompanying texture evolution are performed and they are in very good agreement with experimental measurements. The effect of strain rate on the activation of the various slip systems and twinning show that differences in the strain rate dependence of yield stress and Rvalues in ZEK100 have their origin in the activation of different deformation mechanisms.

A hybrid CNN feature model for pulmonary nodule malignancy risk differentiation.

PubMed

Wang, Huafeng; Zhao, Tingting; Li, Lihong Connie; Pan, Haixia; Liu, Wanquan; Gao, Haoqi; Han, Fangfang; Wang, Yuehai; Qi, Yifan; Liang, Zhengrong

2018-01-01

The malignancy risk differentiation of pulmonary nodule is one of the most challenge tasks of computer-aided diagnosis (CADx). Most recently reported CADx methods or schemes based on texture and shape estimation have shown relatively satisfactory on differentiating the risk level of malignancy among the nodules detected in lung cancer screening. However, the existing CADx schemes tend to detect and analyze characteristics of pulmonary nodules from a statistical perspective according to local features only. Enlightened by the currently prevailing learning ability of convolutional neural network (CNN), which simulates human neural network for target recognition and our previously research on texture features, we present a hybrid model that takes into consideration of both global and local features for pulmonary nodule differentiation using the largest public database founded by the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI). By comparing three types of CNN models in which two of them were newly proposed by us, we observed that the multi-channel CNN model yielded the best discrimination in capacity of differentiating malignancy risk of the nodules based on the projection of distributions of extracted features. Moreover, CADx scheme using the new multi-channel CNN model outperformed our previously developed CADx scheme using the 3D texture feature analysis method, which increased the computed area under a receiver operating characteristic curve (AUC) from 0.9441 to 0.9702.

Effect of texturing on polarization switching dynamics in ferroelectric ceramics

NASA Astrophysics Data System (ADS)

Zhukov, Sergey; Genenko, Yuri A.; Koruza, Jurij; Schultheiß, Jan; von Seggern, Heinz; Sakamoto, Wataru; Ichikawa, Hiroki; Murata, Tatsuro; Hayashi, Koichiro; Yogo, Toshinobu

2016-01-01

Highly (100),(001)-oriented (Ba0.85Ca0.15)TiO3 (BCT) lead-free piezoelectric ceramics were fabricated by the reactive templated grain growth method using a mixture of plate-like CaTiO3 and BaTiO3 particles. Piezoelectric properties of the ceramics with a high degree of texture were found to be considerably enhanced compared with the BCT ceramics with a low degree of texture. With increasing the Lotgering factor from 26% up to 94%, the piezoelectric properties develop towards the properties of a single crystal. The dynamics of polarization switching was studied over a broad time domain of 8 orders of magnitude and was found to strongly depend on the degree of orientation of the ceramics. Samples with a high degree of texture exhibited 2-3 orders of magnitude faster polarization switching, as compared with the ones with a low degree of texture. This was rationalized by means of the Inhomogeneous Field Mechanism model as a result of the narrower statistical distribution of the local electric field values in textured media, which promotes a more coherent switching process. The extracted microscopic parameters of switching revealed a decrease of the critical nucleus energy in systems with a high degree of texture providing more favorable switching conditions related to the enhanced ferroelectric properties of the textured material.

Wavelet-based image analysis system for soil texture analysis

NASA Astrophysics Data System (ADS)

Sun, Yun; Long, Zhiling; Jang, Ping-Rey; Plodinec, M. John

2003-05-01

Soil texture is defined as the relative proportion of clay, silt and sand found in a given soil sample. It is an important physical property of soil that affects such phenomena as plant growth and agricultural fertility. Traditional methods used to determine soil texture are either time consuming (hydrometer), or subjective and experience-demanding (field tactile evaluation). Considering that textural patterns observed at soil surfaces are uniquely associated with soil textures, we propose an innovative approach to soil texture analysis, in which wavelet frames-based features representing texture contents of soil images are extracted and categorized by applying a maximum likelihood criterion. The soil texture analysis system has been tested successfully with an accuracy of 91% in classifying soil samples into one of three general categories of soil textures. In comparison with the common methods, this wavelet-based image analysis approach is convenient, efficient, fast, and objective.

Diagnostic Performance of Mammographic Texture Analysis in the Differential Diagnosis of Benign and Malignant Breast Tumors.

PubMed

Li, Zhiming; Yu, Lan; Wang, Xin; Yu, Haiyang; Gao, Yuanxiang; Ren, Yande; Wang, Gang; Zhou, Xiaoming

2017-11-09

The purpose of this study was to investigate the diagnostic performance of mammographic texture analysis in the differential diagnosis of benign and malignant breast tumors. Digital mammography images were obtained from the Picture Archiving and Communication System at our institute. Texture features of mammographic images were calculated. Mann-Whitney U test was used to identify differences between the benign and malignant group. The receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic performance of texture features. Significant differences of texture features of histogram, gray-level co-occurrence matrix (GLCM) and run length matrix (RLM) were found between the benign and malignant breast group (P < .05). The area under the ROC (AUROC) of histogram, GLCM, and RLM were 0.800, 0.787, and 0.761, with no differences between them (P > .05). The AUROCs of imaging-based diagnosis, texture analysis, and imaging-based diagnosis combined with texture analysis were 0.873, 0.863, and 0.961, respectively. When imaging-based diagnosis was combined with texture analysis, the AUROC was higher than that of imaging-based diagnosis or texture analysis (P < .05). Mammographic texture analysis is a reliable technique for differential diagnosis of benign and malignant breast tumors. Furthermore, the combination of imaging-based diagnosis and texture analysis can significantly improve diagnostic performance. Copyright © 2017 Elsevier Inc. All rights reserved.

Evaluation of left ventricular assist device pump bladders cast from ion-sputtered polytetrafluorethylene mandrels

NASA Technical Reports Server (NTRS)

1982-01-01

A highly thromboresistant blood contacting interface for use in implanatable blood pump is investigated. Biomaterials mechanics, dynamics, durability, surface morphology, and chemistry are among the critical consideration pertinent to the choice of an appropriate blood pump bladder material. The use of transfer cast biopolymers from ion beam textured surfaces is investigated to detect subtle variations in blood pump surface morphology using Biomer as the biomaterial of choice. The efficacy of ion beam sputtering as an acceptable method of fabricating textured blood interfaces is evaluated. Aortic grafts and left ventricular assist devices were implanted in claves; the blood interfaces were fabricated by transfer casting methods from ion beam textured polytetrafluorethylene mandrels. The mandrels were textured by superimposing a 15 micron screen mesh; ion sputtering conditions were 300 volts beam energy, 40 to 50 mA beam, and a mandrel to source distance of 25 microns.

Textural-Contextual Labeling and Metadata Generation for Remote Sensing Applications

NASA Technical Reports Server (NTRS)

Kiang, Richard K.

1999-01-01

Despite the extensive research and the advent of several new information technologies in the last three decades, machine labeling of ground categories using remotely sensed data has not become a routine process. Considerable amount of human intervention is needed to achieve a level of acceptable labeling accuracy. A number of fundamental reasons may explain why machine labeling has not become automatic. In addition, there may be shortcomings in the methodology for labeling ground categories. The spatial information of a pixel, whether textural or contextual, relates a pixel to its surroundings. This information should be utilized to improve the performance of machine labeling of ground categories. Landsat-4 Thematic Mapper (TM) data taken in July 1982 over an area in the vicinity of Washington, D.C. are used in this study. On-line texture extraction by neural networks may not be the most efficient way to incorporate textural information into the labeling process. Texture features are pre-computed from cooccurrence matrices and then combined with a pixel's spectral and contextual information as the input to a neural network. The improvement in labeling accuracy with spatial information included is significant. The prospect of automatic generation of metadata consisting of ground categories, textural and contextual information is discussed.

Some aerodynamic considerations related to wind tunnel model surface definition

NASA Technical Reports Server (NTRS)

Gloss, B. B.

1980-01-01

The aerodynamic considerations related to model surface definition are examined with particular emphasis in areas of fabrication tolerances, model surface finish, and orifice induced pressure errors. The effect of model surface roughness texture on skin friction is also discussed. It is shown that at a given Reynolds number, any roughness will produce no skin friction penalty.

Semantic attributes based texture generation

NASA Astrophysics Data System (ADS)

Chi, Huifang; Gan, Yanhai; Qi, Lin; Dong, Junyu; Madessa, Amanuel Hirpa

2018-04-01

Semantic attributes are commonly used for texture description. They can be used to describe the information of a texture, such as patterns, textons, distributions, brightness, and so on. Generally speaking, semantic attributes are more concrete descriptors than perceptual features. Therefore, it is practical to generate texture images from semantic attributes. In this paper, we propose to generate high-quality texture images from semantic attributes. Over the last two decades, several works have been done on texture synthesis and generation. Most of them focusing on example-based texture synthesis and procedural texture generation. Semantic attributes based texture generation still deserves more devotion. Gan et al. proposed a useful joint model for perception driven texture generation. However, perceptual features are nonobjective spatial statistics used by humans to distinguish different textures in pre-attentive situations. To give more describing information about texture appearance, semantic attributes which are more in line with human description habits are desired. In this paper, we use sigmoid cross entropy loss in an auxiliary model to provide enough information for a generator. Consequently, the discriminator is released from the relatively intractable mission of figuring out the joint distribution of condition vectors and samples. To demonstrate the validity of our method, we compare our method to Gan et al.'s method on generating textures by designing experiments on PTD and DTD. All experimental results show that our model can generate textures from semantic attributes.

Neuromorphic VLSI vision system for real-time texture segregation.

PubMed

Shimonomura, Kazuhiro; Yagi, Tetsuya

2008-10-01

The visual system of the brain can perceive an external scene in real-time with extremely low power dissipation, although the response speed of an individual neuron is considerably lower than that of semiconductor devices. The neurons in the visual pathway generate their receptive fields using a parallel and hierarchical architecture. This architecture of the visual cortex is interesting and important for designing a novel perception system from an engineering perspective. The aim of this study is to develop a vision system hardware, which is designed inspired by a hierarchical visual processing in V1, for real time texture segregation. The system consists of a silicon retina, orientation chip, and field programmable gate array (FPGA) circuit. The silicon retina emulates the neural circuits of the vertebrate retina and exhibits a Laplacian-Gaussian-like receptive field. The orientation chip selectively aggregates multiple pixels of the silicon retina in order to produce Gabor-like receptive fields that are tuned to various orientations by mimicking the feed-forward model proposed by Hubel and Wiesel. The FPGA circuit receives the output of the orientation chip and computes the responses of the complex cells. Using this system, the neural images of simple cells were computed in real-time for various orientations and spatial frequencies. Using the orientation-selective outputs obtained from the multi-chip system, a real-time texture segregation was conducted based on a computational model inspired by psychophysics and neurophysiology. The texture image was filtered by the two orthogonally oriented receptive fields of the multi-chip system and the filtered images were combined to segregate the area of different texture orientation with the aid of FPGA. The present system is also useful for the investigation of the functions of the higher-order cells that can be obtained by combining the simple and complex cells.

High-Temperature Thermoelectric and Microstructural Characteristics of Cobalt-Based Oxides with Ga Substituted on the Co-Site

NASA Astrophysics Data System (ADS)

Nong, N. V.; Yanagiya, S.; Monica, S.; Pryds, N.; Ohtaki, M.

2011-05-01

The effects of Ga substitution on the Co-site on the high-temperature thermoelectric properties and microstructure are investigated for the misfitlayered Ca3Co4O9 and the complex perovskite-related Sr3RECo4O10.5 (RE = rare earth) cobalt-based oxides. For both systems, substitution of Ga for Co results in a simultaneous increase in the Seebeck coefficient ( S) and the electrical conductivity ( σ), and the influence is more significant in the high temperature region. The power factor ( S 2 σ) is thereby remarkably improved by Ga substitution, particularly at high temperatures. Texture factor calculations using x-ray diffraction pattern data for pressed and powder samples reveal that the Ga-doped samples are highly textured. Microstructure observed by scanning electron microscopy shows very well-crystallized grains for the samples with Ga substitution for Co. Among the Ga-doped samples, Ca3Co3.95Ga0.05O9 shows the best ZT value of 0.45 at 1200 K, which is about 87.5% higher than the nondoped one, a considerable improvement.

Experiments and improvements of ear recognition based on local texture descriptors

NASA Astrophysics Data System (ADS)

Benzaoui, Amir; Adjabi, Insaf; Boukrouche, Abdelhani

2017-04-01

The morphology of the human ear presents rich and stable information embedded on the curved 3-D surface and has as a result attracted considerable attention from forensic scientists and engineers as a biometric recognition modality. However, recognizing a person's identity from the morphology of the human ear in unconstrained environments, with insufficient and incomplete training data, strong person-specificity, and high within-range variance, can be very challenging. Following our previous work on ear recognition based on local texture descriptors, we propose to use anatomical and embryological information about the human ear in order to find the autonomous components and the locations where large interindividual variations can be detected. Embryology is particularly relevant to our approach as it provides information on the possible changes that can be observed in the external structure of the ear. We experimented with three publicly available databases, namely: IIT Delhi-1, IIT Delhi-2, and USTB-1, consisting of several ear benchmarks acquired under varying conditions and imaging qualities. The experiments show excellent results, beyond the state of the art.

Visual texture perception via graph-based semi-supervised learning

NASA Astrophysics Data System (ADS)

Zhang, Qin; Dong, Junyu; Zhong, Guoqiang

2018-04-01

Perceptual features, for example direction, contrast and repetitiveness, are important visual factors for human to perceive a texture. However, it needs to perform psychophysical experiment to quantify these perceptual features' scale, which requires a large amount of human labor and time. This paper focuses on the task of obtaining perceptual features' scale of textures by small number of textures with perceptual scales through a rating psychophysical experiment (what we call labeled textures) and a mass of unlabeled textures. This is the scenario that the semi-supervised learning is naturally suitable for. This is meaningful for texture perception research, and really helpful for the perceptual texture database expansion. A graph-based semi-supervised learning method called random multi-graphs, RMG for short, is proposed to deal with this task. We evaluate different kinds of features including LBP, Gabor, and a kind of unsupervised deep features extracted by a PCA-based deep network. The experimental results show that our method can achieve satisfactory effects no matter what kind of texture features are used.

Natural texture retrieval based on perceptual similarity measurement

NASA Astrophysics Data System (ADS)

Gao, Ying; Dong, Junyu; Lou, Jianwen; Qi, Lin; Liu, Jun

2018-04-01

A typical texture retrieval system performs feature comparison and might not be able to make human-like judgments of image similarity. Meanwhile, it is commonly known that perceptual texture similarity is difficult to be described by traditional image features. In this paper, we propose a new texture retrieval scheme based on texture perceptual similarity. The key of the proposed scheme is that prediction of perceptual similarity is performed by learning a non-linear mapping from image features space to perceptual texture space by using Random Forest. We test the method on natural texture dataset and apply it on a new wallpapers dataset. Experimental results demonstrate that the proposed texture retrieval scheme with perceptual similarity improves the retrieval performance over traditional image features.

Structure-guided statistical textural distinctiveness for salient region detection in natural images.

PubMed

Scharfenberger, Christian; Wong, Alexander; Clausi, David A

2015-01-01

We propose a simple yet effective structure-guided statistical textural distinctiveness approach to salient region detection. Our method uses a multilayer approach to analyze the structural and textural characteristics of natural images as important features for salient region detection from a scale point of view. To represent the structural characteristics, we abstract the image using structured image elements and extract rotational-invariant neighborhood-based textural representations to characterize each element by an individual texture pattern. We then learn a set of representative texture atoms for sparse texture modeling and construct a statistical textural distinctiveness matrix to determine the distinctiveness between all representative texture atom pairs in each layer. Finally, we determine saliency maps for each layer based on the occurrence probability of the texture atoms and their respective statistical textural distinctiveness and fuse them to compute a final saliency map. Experimental results using four public data sets and a variety of performance evaluation metrics show that our approach provides promising results when compared with existing salient region detection approaches.

Fabrication and electrical properties of textured strontium(0.53)barium(0.47)niobium(2)oxygen(6) ceramics prepared by templated grain growth

NASA Astrophysics Data System (ADS)

Duran, Cihangir

Sr0.53Ba0.47Nb2O6 (SBN53) ceramics were textured by the templated grain growth (TGG), in a matrix of SrNb2O6 and BaNb2O6 powders. Acicular KSr2Nb5O15 (KSN) template particles, synthesized by a molten salt process, were used to texture the samples in the c direction (i.e., [001]). Template growth was assisted by adding V2O5 as a liquid phase former for some compositions. The texture fraction also increased with higher sintering temperatures or times and with initial template concentration due to the preferential growth of the template particles. When V2O5 was present, SBN53 phase formation initiated on the KSN templates and texture development started at temperatures as low as 950°C. Phase formation in the V2O5-free samples, however, initiated in the matrix (i.e., independent of the KSN templates). The liquid phase adversely affected the template growth by favoring anisotropic grain growth in the matrix, which caused lower texture fraction and broader texture distribution in [001] at low template concentrations. Increased template-template interaction (e.g., tangling) during tape casting also resulted in broader texture distribution. Therefore, an optimum template content was found to be ˜10--15 wt%. However, a texture fraction of 0.93 to 0.98 was obtained using only 5 wt% templates when anisotropic matrix grain growth was prevented. Phase evolution was studied in the randomly oriented samples as a function of quenching temperature, heating rate, and liquid phase, using KSN powder (rather than acicular particles) as a seed material. The formation temperature for SBN53 was lowered substantially by adding more seeds, decreasing the heating rate, and introducing a liquid. The temperature decreased from 1260°C for the samples with no seeds to 1130°C for the samples with 15.4 wt% seeds + 0.8 mol% V2O5 at a heating rate of 4°C/min. For the V2O5-free samples, the activation energy was considerably lowered from 554 +/- 15 kJ/mol for the samples with no seeds to 241 +/- 17 kJ/mol for the samples with 15.4 wt% seeds. The dielectric and piezoelectric properties were enhanced in samples with better orientation (i.e., high texture fraction (f) and narrow degree of orientation parameter (r) in the texture direction). The presence of nonferroelectric phases (V2O5 or Nb2O5-based) at the grain boundaries suppressed the observed dielectric properties, especially at the transition temperature. (Abstract shortened by UMI.)

A Study for Texture Feature Extraction of High-Resolution Satellite Images Based on a Direction Measure and Gray Level Co-Occurrence Matrix Fusion Algorithm

PubMed Central

Zhang, Xin; Cui, Jintian; Wang, Weisheng; Lin, Chao

2017-01-01

To address the problem of image texture feature extraction, a direction measure statistic that is based on the directionality of image texture is constructed, and a new method of texture feature extraction, which is based on the direction measure and a gray level co-occurrence matrix (GLCM) fusion algorithm, is proposed in this paper. This method applies the GLCM to extract the texture feature value of an image and integrates the weight factor that is introduced by the direction measure to obtain the final texture feature of an image. A set of classification experiments for the high-resolution remote sensing images were performed by using support vector machine (SVM) classifier with the direction measure and gray level co-occurrence matrix fusion algorithm. Both qualitative and quantitative approaches were applied to assess the classification results. The experimental results demonstrated that texture feature extraction based on the fusion algorithm achieved a better image recognition, and the accuracy of classification based on this method has been significantly improved. PMID:28640181

The Lingering Effects of an Artificial Blind Spot

PubMed Central

Morgan, Michael J.; McEwan, William; Solomon, Joshua

2007-01-01

Background When steady fixation is maintained on the centre of a large patch of texture, holes in the periphery of the texture rapidly fade from awareness, producing artificial scotomata (i.e., invisible areas of reduced vision, like the natural ‘blind spot’). There has been considerable controversy about whether this apparent ‘filling in’ depends on a low-level or high-level visual process. Evidence for an active process is that when the texture around the scotomata is suddenly removed, phantasms of the texture appear within the previous scotomata. Methodology To see if these phantasms were equivalent to real low-level signals, we measured contrast discrimination for real dynamic texture patches presented on top of the phantasms. Principal Findings Phantasm intensity varied with adapting contrast. Contrast discrimination depended on both (real) pedestal contrast and phantasm intensity, in a manner indicative of a common sensory threshold. The phantasms showed inter-ocular transfer, proving that their effects are cortical rather than retinal. Conclusions We show that this effect is consistent with a tonic spreading of the adapting texture into the scotomata, coupled with some overall loss of sensitivity. Our results support the view that ‘filling in’ happens at an early stage of visual processing, quite possibly in primary visual cortex (V1). PMID:17327917

Effect of slice thickness on brain magnetic resonance image texture analysis

PubMed Central

2010-01-01

Background The accuracy of texture analysis in clinical evaluation of magnetic resonance images depends considerably on imaging arrangements and various image quality parameters. In this paper, we study the effect of slice thickness on brain tissue texture analysis using a statistical approach and classification of T1-weighted images of clinically confirmed multiple sclerosis patients. Methods We averaged the intensities of three consecutive 1-mm slices to simulate 3-mm slices. Two hundred sixty-four texture parameters were calculated for both the original and the averaged slices. Wilcoxon's signed ranks test was used to find differences between the regions of interest representing white matter and multiple sclerosis plaques. Linear and nonlinear discriminant analyses were applied with several separate training and test sets to determine the actual classification accuracy. Results Only moderate differences in distributions of the texture parameter value for 1-mm and simulated 3-mm-thick slices were found. Our study also showed that white matter areas are well separable from multiple sclerosis plaques even if the slice thickness differs between training and test sets. Conclusions Three-millimeter-thick magnetic resonance image slices acquired with a 1.5 T clinical magnetic resonance scanner seem to be sufficient for texture analysis of multiple sclerosis plaques and white matter tissue. PMID:20955567

Electrodeposition of biaxially textured layers on a substrate

DOEpatents

Bhattacharya, Raghu N; Phok, Sovannary; Spagnol, Priscila; Chaudhuri, Tapas

2013-11-19

Methods of producing one or more biaxially textured layer on a substrate, and articles produced by the methods, are disclosed. An exemplary method may comprise electrodepositing on the substrate a precursor material selected from the group consisting of rare earths, transition metals, actinide, lanthanides, and oxides thereof. An exemplary article (150) may comprise a biaxially textured base material (130), and at least one biaxially textured layer (110) selected from the group consisting of rare earths, transition metals, actinides, lanthanides, and oxides thereof. The at least one biaxially textured layer (110) is formed by electrodeposition on the biaxially textured base material (130).

Modulating Thin Film Transistor Characteristics by Texturing the Gate Metal.

PubMed

Nair, Aswathi; Bhattacharya, Prasenjit; Sambandan, Sanjiv

2017-12-20

The development of reliable, high performance integrated circuits based on thin film transistors (TFTs) is of interest for the development of flexible electronic circuits. In this work we illustrate the modulation of TFT transconductance via the texturing of the gate metal created by the addition of a conductive pattern on top of a planar gate. Texturing results in the semiconductor-insulator interface acquiring a non-planar geometry with local variations in the radius of curvature. This influences various TFT parameters such as the subthreshold slope, gate voltage at the onset of conduction, contact resistance and gate capacitance. Specific studies are performed on textures based on periodic striations oriented along different directions. Textured TFTs showed upto ±40% variation in transconductance depending on the texture orientation as compared to conventional planar gate TFTs. Analytical models are developed and compared with experiments. Gain boosting in common source amplifiers based on textured TFTs as compared to conventional TFTs is demonstrated.

Precision of quantitative computed tomography texture analysis using image filtering: A phantom study for scanner variability.

PubMed

Yasaka, Koichiro; Akai, Hiroyuki; Mackin, Dennis; Court, Laurence; Moros, Eduardo; Ohtomo, Kuni; Kiryu, Shigeru

2017-05-01

Quantitative computed tomography (CT) texture analyses for images with and without filtration are gaining attention to capture the heterogeneity of tumors. The aim of this study was to investigate how quantitative texture parameters using image filtering vary among different computed tomography (CT) scanners using a phantom developed for radiomics studies.A phantom, consisting of 10 different cartridges with various textures, was scanned under 6 different scanning protocols using four CT scanners from four different vendors. CT texture analyses were performed for both unfiltered images and filtered images (using a Laplacian of Gaussian spatial band-pass filter) featuring fine, medium, and coarse textures. Forty-five regions of interest were placed for each cartridge (x) in a specific scan image set (y), and the average of the texture values (T(x,y)) was calculated. The interquartile range (IQR) of T(x,y) among the 6 scans was calculated for a specific cartridge (IQR(x)), while the IQR of T(x,y) among the 10 cartridges was calculated for a specific scan (IQR(y)), and the median IQR(y) was then calculated for the 6 scans (as the control IQR, IQRc). The median of their quotient (IQR(x)/IQRc) among the 10 cartridges was defined as the variability index (VI).The VI was relatively small for the mean in unfiltered images (0.011) and for standard deviation (0.020-0.044) and entropy (0.040-0.044) in filtered images. Skewness and kurtosis in filtered images featuring medium and coarse textures were relatively variable across different CT scanners, with VIs of 0.638-0.692 and 0.430-0.437, respectively.Various quantitative CT texture parameters are robust and variable among different scanners, and the behavior of these parameters should be taken into consideration.

Quantitative analysis of domain texture in polycrystalline barium titanate by polarized Raman microprobe spectroscopy

NASA Astrophysics Data System (ADS)

Sakashita, Tatsuo; Chazono, Hirokazu; Pezzotti, Giuseppe

2007-12-01

A quantitative determination of domain distribution in polycrystalline barium titanate (BaTiO3, henceforth BT) ceramics has been pursued with the aid of a microprobe polarized Raman spectrometer. The crystallographic texture and domain orientation distribution of BT ceramics, which switched upon applying stress according to ferroelasticity principles, were determined from the relative intensity of selected phonon modes, taking into consideration a theoretical analysis of the angular dependence of phonon mode intensity for the tetragonal BT phase. Furthermore, the angular dependence of Raman intensity measured in polycrystalline BT depended on the statistical distribution of domain angles in the laser microprobe, which was explicitly taken into account in this work for obtaining a quantitative analysis of domain orientation for in-plane textured BT polycrystalline materials.

Slippage on a particle-laden liquid-gas interface in textured microchannels

NASA Astrophysics Data System (ADS)

Gaddam, Anvesh; Agrawal, Amit; Joshi, Suhas S.; Thompson, Mark C.

2018-03-01

Despite numerous investigations in the literature on slip flows in textured microchannels, experimental results were seldom in agreement with the theory. It is conjectured that contamination of the liquid-gas interface by impurities might be one of the sources of this discrepancy. However, the effect of impurities on slippage at the liquid-gas interface is neither understood nor previously reported. To this end, this work presents numerical investigation on the flow past a liquid-gas interface embedded with solid particles in textured microchannels. Initially, we present numerical simulations past transverse ribs with cylindrical particles on the liquid-gas interface. A reduction in effective slip length (or slip loss) with respect to the particle-free interface as a function of gas fraction, constriction ratio, and particle position was quantified. A significant slip loss (˜20-80%) was induced, owing to acceleration-deceleration cycles experienced by the liquid advecting across the particle-laden liquid-gas interface. Even a small number of solid particles adsorbed on a liquid-gas interface were shown to reduce the effective slip length considerably. This renders a textured microchannel with the particle-laden interface to be ineffective as compared to a completely wetted textured microchannel under certain conditions. Furthermore, a flow past two bi-dimensional textures, viz. posts and holes, with their interfaces embedded with spherical particles was also simulated. Our results show that texture configurations with an unbounded liquid-gas interface can mitigate the detrimental effects of particles adsorbed at the interface. The results presented here will help guide in designing efficient textured surfaces in future.

Method of Forming Textured Silicon Substrate by Maskless Cryogenic Etching

NASA Technical Reports Server (NTRS)

Yee, Karl Y. (Inventor); Homyk, Andrew P. (Inventor)

2014-01-01

Disclosed herein is a textured substrate comprising a base comprising silicon, the base having a plurality of needle like structures depending away from the base, wherein at least one of the needle like structures has a depth of greater than or equal to about 50 micrometers determined perpendicular to the base, and wherein at least one of the needle like structures has a width of less than or equal to about 50 micrometers determined parallel to the base. An anode and a lithium ion battery comprising the textured substrate, and a method of producing the textured substrate are also disclosed.

Texture analysis of MR images of patients with Mild Traumatic Brain Injury

PubMed Central

2010-01-01

Background Our objective was to study the effect of trauma on texture features in cerebral tissue in mild traumatic brain injury (MTBI). Our hypothesis was that a mild trauma may cause microstructural changes, which are not necessarily perceptible by visual inspection but could be detected with texture analysis (TA). Methods We imaged 42 MTBI patients by using 1.5 T MRI within three weeks of onset of trauma. TA was performed on the area of mesencephalon, cerebral white matter at the levels of mesencephalon, corona radiata and centrum semiovale and in different segments of corpus callosum (CC) which have been found to be sensitive to damage. The same procedure was carried out on a control group of ten healthy volunteers. Patients' TA data was compared with the TA results of the control group comparing the amount of statistically significantly differing TA parameters between the left and right sides of the cerebral tissue and comparing the most discriminative parameters. Results There were statistically significant differences especially in several co-occurrence and run-length matrix based parameters between left and right side in the area of mesencephalon, in cerebral white matter at the level of corona radiata and in the segments of CC in patients. Considerably less difference was observed in the healthy controls. Conclusions TA revealed significant changes in texture parameters of cerebral tissue between hemispheres and CC segments in TBI patients. TA may serve as a novel additional tool for detecting the conventionally invisible changes in cerebral tissue in MTBI and help the clinicians to make an early diagnosis. PMID:20462439

Texture-Based Analysis of 100 MR Examinations of Head and Neck Tumors - Is It Possible to Discriminate Between Benign and Malignant Masses in a Multicenter Trial?

PubMed

Fruehwald-Pallamar, J; Hesselink, J R; Mafee, M F; Holzer-Fruehwald, L; Czerny, C; Mayerhoefer, M E

2016-02-01

To evaluate whether texture-based analysis of standard MRI sequences can help in the discrimination between benign and malignant head and neck tumors. The MR images of 100 patients with a histologically clarified head or neck mass, from two different institutions, were analyzed. Texture-based analysis was performed using texture analysis software, with region of interest measurements for 2 D and 3 D evaluation independently for all axial sequences. COC, RUN, GRA, ARM, and WAV features were calculated for all ROIs. 10 texture feature subsets were used for a linear discriminant analysis, in combination with k-nearest-neighbor classification. Benign and malignant tumors were compared with regard to texture-based values. There were differences in the images from different field-strength scanners, as well as from different vendors. For the differentiation of benign and malignant tumors, we found differences on STIR and T2-weighted images for 2 D, and on contrast-enhanced T1-TSE with fat saturation for 3 D evaluation. In a separate analysis of the subgroups 1.5 and 3 Tesla, more discriminating features were found. Texture-based analysis is a useful tool in the discrimination of benign and malignant tumors when performed on one scanner with the same protocol. We cannot recommend this technique for the use of multicenter studies with clinical data. 2 D/3 D texture-based analysis can be performed in head and neck tumors. Texture-based analysis can differentiate between benign and malignant masses. Analyzed MR images should originate from one scanner with an identical protocol. © Georg Thieme Verlag KG Stuttgart · New York.

Texturing of sodium bismuth titanate-barium titanate ceramics by templated grain growth

NASA Astrophysics Data System (ADS)

Yilmaz, Huseyin

2002-01-01

Sodium bismuth titanate modified with barium titanate, (Na1/2Bi 1/2)TiO3-BaTiO3 (NBT-BT), is a candidate lead-free piezoelectric material which has been shown to have comparatively high piezoelectric response. In this work, textured (Na1/2Bi1/2)TiO 3-BaTiO3 (5.5mol% BaTiO3) ceramics with <100> pc (where pc denotes the pseudocubic perovskite cell) orientation were fabricated by Templated Grain Growth (TGG) or Reactive Templated Grain Growth (RTGG) using anisotropically shaped template particles. In the case of TGG, molten salt synthesized SrTiO3 platelets were tape cast with a (Na1/2Bi1/2)TiO3-5.5mol%BaTiO3 powder and sintered at 1200°C for up to 12 hours. For the RTGG approach, Bi4Ti3O12 (BiT) platelets were tape cast with a Na2CO3, Bi2O3, TiO 2, and BaCO3 powder mixture and reactively sintered. The TGG approach using SrTiO3 templates gave stronger texture along [001] compared to the RTGG approach using BiT templates. The textured ceramics were characterized by X-ray and electron backscatter diffraction for the quality of texture. The texture function was quantified by the Lotgering factor, rocking curve, pole figures, inverse pole figures, and orientation imaging microscopy. Electrical and electromechanical property characterization of randomly oriented and <001>pc textured (Na1/2Bi1/2)TiO 3-5.5 mol% BaTiO3 rhombohedral ceramics showed 0.26% strain at 70 kV/cm, d33 coefficients over 500 pC/N have been obtained for highly textured samples (f ˜ 90%). The piezoelectric coefficient from Berlincourt was d33 ˜ 200 pC/N. The materials show considerable hysteresis. The presence of hysteresis in the unipolar-electric field curve is probably linked to the ferroelastic phase transition seen in the (Na 1/2Bi1/2)TiO3 system on cooling from high temperature at ˜520°C. The macroscopic physical properties (remanent polarization, dielectric constant, and piezoelectric coefficient) of random and textured ([001] pc) rhombohedral perovskites were estimated by linear averaging of single crystal data. However, the complete polarization, dielectric, and piezoelectric tensors are not available for NBT-BT single crystals. Therefore, the properties of lead based (PZT, 52/48) rhombohedral ferroelectric single domain-single crystals, whose properties (polarization, dielectric and piezoelectric) were computed using Landau-Ginsburg-Devonshire phenomenological theory (by Haun et. al.), were used in the calculations for random and textured cases. (Abstract shortened by UMI.)

Experimental study of grain interactions on rolling texture development in face-centered cubic metals

NASA Astrophysics Data System (ADS)

Kumar Ray, Atish

There exists considerable debate in the texture community about whether grain interactions are a necessary factor to explain the development of deformation textures in polycrystalline metals. Computer simulations indicate that grain interactions play a significant role, while experimental evidence shows that the material type and starting orientation are more important in the development of texture and microstructure. A balanced review of the literature on face-centered cubic metals shows that the opposing viewpoints have developed due to the lack of any complete experimental study which considers both the intrinsic (material type and starting orientation) and extrinsic (grain interaction) factors. In this study, a novel method was developed to assemble ideally orientated crystalline aggregates in 99.99% aluminum (Al) or copper (Cu) to experimentally evaluate the effect of grain interactions on room temperature deformation texture. Ideal orientations relevant to face-centered cubic rolling textures, Cube {100} <001>, Goss {110} <001>, Brass {110} <11¯2> and Copper {112} <111¯> were paired in different combinations and deformed by plane strain compression to moderate strain levels of 1.0 to 1.5. Orientation dependent mechanical behavior was distinguishable from that of the neighbor-influenced behavior. In interacting crystals the constraint on the rolling direction shear strains (gammaXY , gammaXZ) was found to be most critical to show the effect of interactions via the evolution of local microstructure and microtexture. Interacting crystals with increasing deformations were observed to gradually rotate towards the S-component, {123} <634>. Apart from the average lattice reorientations, the interacting crystals also developed strong long-range orientation gradients inside the bulk of the crystal, which were identified as accumulating misorientations across the deformation boundaries. Based on a statistical procedure using quaternions, the orientation and interaction related heterogeneous deformations were characterized by three principal component vectors and their respective eigenvalues for both the orientation and misorientation distributions. For the case of a medium stacking fault energy metal like Cu, the texture and microstructure development depends wholly on the starting orientations. Microstructural instabilities in Cu are explained through a local slip clustering process, and the possible role of grain interactions on such instabilities is proposed. In contrast, the texture and microstructure development in a high stacking fault energy metal like Al is found to be dependent on the grain interactions. In general, orientation, grain interaction and material type were found to be key factors in the development of rolling textures in face-centered cubic metals and alloys. Moreso, in the texture development not any single parameter can be held responsible, rather, the interdependency of each of the three parameters must be considered. In this frame-work polycrystalline grains can be classified into four types according to their stability and susceptibility during deformation.

The effect of texture granularity on texture synthesis quality

NASA Astrophysics Data System (ADS)

Golestaneh, S. Alireza; Subedar, Mahesh M.; Karam, Lina J.

2015-09-01

Natural and artificial textures occur frequently in images and in video sequences. Image/video coding systems based on texture synthesis can make use of a reliable texture synthesis quality assessment method in order to improve the compression performance in terms of perceived quality and bit-rate. Existing objective visual quality assessment methods do not perform satisfactorily when predicting the synthesized texture quality. In our previous work, we showed that texture regularity can be used as an attribute for estimating the quality of synthesized textures. In this paper, we study the effect of another texture attribute, namely texture granularity, on the quality of synthesized textures. For this purpose, subjective studies are conducted to assess the quality of synthesized textures with different levels (low, medium, high) of perceived texture granularity using different types of texture synthesis methods.

Texture in steel plates revealed by laser ultrasonic surface acoustic waves velocity dispersion analysis.

PubMed

Yin, Anmin; Wang, Xiaochen; Glorieux, Christ; Yang, Quan; Dong, Feng; He, Fei; Wang, Yanlong; Sermeus, Jan; Van der Donck, Tom; Shu, Xuedao

2017-07-01

A photoacoustic, laser ultrasonics based approach in an Impulsive Stimulated Scattering (ISS) implementation was used to investigate the texture in polycrystalline metal plates. The angular dependence of the 'polycrystalline' surface acoustic wave (SAW) velocity measured along regions containing many grains was experimentally determined and compared with simulated results that were based on the angular dependence of the 'single grain' SAW velocity within single grains and the grain orientation distribution. The polycrystalline SAW velocities turn out to vary with texture. The SAW velocities and their angular variations for {110} texture were found to be larger than that the ones for {111} texture or the strong γ fiber texture. The SAW velocities for {001} texture were larger than for {111} texture, but with almost the same angular dependence. The results infer the feasibility to apply angular SAW angular dispersion measurements by laser ultrasonics for on-line texture monitoring. Copyright © 2017 Elsevier B.V. All rights reserved.

Early classification of Alzheimer's disease using hippocampal texture from structural MRI

NASA Astrophysics Data System (ADS)

Zhao, Kun; Ding, Yanhui; Wang, Pan; Dou, Xuejiao; Zhou, Bo; Yao, Hongxiang; An, Ningyu; Zhang, Yongxin; Zhang, Xi; Liu, Yong

2017-03-01

Convergent evidence has been collected to support that Alzheimer's disease (AD) is associated with reduction in hippocampal volume based on anatomical magnetic resonance imaging (MRI) and impaired functional connectivity based on functional MRI. Radiomics texture analysis has been previously successfully used to identify MRI biomarkers of several diseases, including AD, mild cognitive impairment and multiple sclerosis. In this study, our goal was to determine if MRI hippocampal textures, including the intensity, shape, texture and wavelet features, could be served as an MRI biomarker of AD. For this purpose, the texture marker was trained and evaluated from MRI data of 48 AD and 39 normal samples. The result highlights the presence of hippocampal texture abnormalities in AD, and the possibility that texture may serve as a neuroimaging biomarker for AD.

Objective measurement of bread crumb texture

NASA Astrophysics Data System (ADS)

Wang, Jian; Coles, Graeme D.

1995-01-01

Evaluation of bread crumb texture plays an important role in judging bread quality. This paper discusses the application of image analysis methods to the objective measurement of the visual texture of bread crumb. The application of Fast Fourier Transform and mathematical morphology methods have been discussed by the authors in their previous work, and a commercial bread texture measurement system has been developed. Based on the nature of bread crumb texture, we compare the advantages and disadvantages of the two methods, and a third method based on features derived directly from statistics of edge density in local windows of the bread image. The analysis of various methods and experimental results provides an insight into the characteristics of the bread texture image and interconnection between texture measurement algorithms. The usefulness of the application of general stochastic process modelling of texture is thus revealed; it leads to more reliable and accurate evaluation of bread crumb texture. During the development of these methods, we also gained useful insights into how subjective judges form opinions about bread visual texture. These are discussed here.

Formation mechanisms of periodic longitudinal microstructure and texture patterns in friction stir welded magnesium AZ80

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hiscocks, J., E-mail: j.hiscocks@queensu.ca

Many studies of friction stir welding have shown that periodicity of metal flow around the tool pin may result in the formation of periodic differences in microstructure and texture in the weld nugget area correlated with the weld pitch. The current work investigates the periodicity of magnesium weld microtexture in the nugget region and its association with material flow using optical and electron microscopy. Two welds created in AZ80 at different processing conditions are presented in detail, one illustrating periodic longitudinal texture change, and one showing for the first time that periodic variations in texture, grain size, or composition aremore » not defining features of periodic nugget flow. While nugget texture is dominated by shear deformation, it was found here to be affected to a lesser degree by compaction of material behind the welding tool, which led to reduction in intensity of the shear texture fiber. The decreased tendency for magnesium based alloys to form periodic patterns as compared to aluminum based alloys is explained with reference to the shear textures. - Highlights: •It is shown here that periodic material flow in the nugget does not necessitate longitudinal texture patterns. •Longitudinal texture patterns are shown to be present or absent in Mg AZ80 based on processing conditions. •Texture in the nugget is mainly dictated by shear deformation, but has measurable effects from other deformation modes. •Explanation of why longitudinal texture change is frequently reported in aluminum but not magnesium alloys is provided. •A new vector visualization of material flow based on EBSD data analysis is shown.« less

Automated video-based assessment of surgical skills for training and evaluation in medical schools.

PubMed

Zia, Aneeq; Sharma, Yachna; Bettadapura, Vinay; Sarin, Eric L; Ploetz, Thomas; Clements, Mark A; Essa, Irfan

2016-09-01

Routine evaluation of basic surgical skills in medical schools requires considerable time and effort from supervising faculty. For each surgical trainee, a supervisor has to observe the trainees in person. Alternatively, supervisors may use training videos, which reduces some of the logistical overhead. All these approaches however are still incredibly time consuming and involve human bias. In this paper, we present an automated system for surgical skills assessment by analyzing video data of surgical activities. We compare different techniques for video-based surgical skill evaluation. We use techniques that capture the motion information at a coarser granularity using symbols or words, extract motion dynamics using textural patterns in a frame kernel matrix, and analyze fine-grained motion information using frequency analysis. We were successfully able to classify surgeons into different skill levels with high accuracy. Our results indicate that fine-grained analysis of motion dynamics via frequency analysis is most effective in capturing the skill relevant information in surgical videos. Our evaluations show that frequency features perform better than motion texture features, which in-turn perform better than symbol-/word-based features. Put succinctly, skill classification accuracy is positively correlated with motion granularity as demonstrated by our results on two challenging video datasets.

Combined Effect of Textured Patterns and Graphene Flake Additives on Tribological Behavior under Boundary Lubrication

PubMed Central

Cai, Zhen-bing; Zhao, Lei; Zhang, Xu; Yue, Wen; Zhu, Min-hao

2016-01-01

A ball-on-plate wear test was employed to investigate the effectiveness of graphene (GP) nanoparticles dispersed in a synthetic-oil-based lubricant in reducing wear. The effect by area ratio of elliptically shaped dimple textures and elevated temperatures were also explored. Pure PAO4 based oil and a mixture of this oil with 0.01 wt% GP were compared as lubricants. At pit area ratio of 5%, GP-base oil effectively reduced friction and wear, especially at 60 and 100°C. Under pure PAO4 oil lubrication, the untextured surfaces gained low friction coefficients (COFs) and wear rates under 60 and 100°C. With increasing laser—texture area ratio, the COF and wear rate decreased at 25 and 150°C but increased at 60 and 100°C. Under the GP-based oil lubrication, the textured surface with 5% area ratio achieved the lowest COF among those of the area ratios tested at all test temperatures. Meanwhile, the textured surface with 20% area ratio obtained the highest COF among those of the area ratios. With the joint action of GP and texture, the textured surface with 10% area ratio exhibited the best anti-wear performance among all of the textured surfaces at all test temperatures. PMID:27054762

High temperature microstructural stability and recrystallization mechanisms in 14YWT alloys

DOE PAGES

Aydogan, E.; El-Atwani, O.; Takajo, S.; ...

2018-02-09

In-situ neutron diffraction experiments were performed on room temperature compressed 14YWT nanostructured ferritic alloys at 1100°C and 1150°C to understand their thermally activated static recrystallization mechanisms. The existence of high density of Y-Ti-O rich nano-oxides (<5 nm) shift the recrystallization temperature up due to Zener pinning of the grain boundaries, making these materials attractive for high temperature applications. This study serves to quantify the texture evolution in-situ and understand the effect of particles on the recrystallization mechanisms in 14YWT alloys. We have shown, both experimentally and theoretically, that there is considerable recovery in the 20% compressed sample after 6.5 hmore » annealing at 1100°C while recrystallization occurs within an hour of annealing at 1100°C and 1150°C in the 60% compressed samples. Moreover, the 60% compressed samples show {112}<110> and {112}<111> texture components during annealing, in contrast to the conventional recrystallization textures in body centered cubic alloys. Furthermore, nano-oxide size, shape, density and distribution are considerably different in unrecrystallized and abnormally grown grains. Transmission electron microscopy analysis shows that oxide particles having a size between 5 and 30 nm play a critical role for recrystallization mechanisms in 14YWT nanostructured ferritic alloys.« less

High temperature microstructural stability and recrystallization mechanisms in 14YWT alloys

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aydogan, E.; El-Atwani, O.; Takajo, S.

In-situ neutron diffraction experiments were performed on room temperature compressed 14YWT nanostructured ferritic alloys at 1100°C and 1150°C to understand their thermally activated static recrystallization mechanisms. The existence of high density of Y-Ti-O rich nano-oxides (<5 nm) shift the recrystallization temperature up due to Zener pinning of the grain boundaries, making these materials attractive for high temperature applications. This study serves to quantify the texture evolution in-situ and understand the effect of particles on the recrystallization mechanisms in 14YWT alloys. We have shown, both experimentally and theoretically, that there is considerable recovery in the 20% compressed sample after 6.5 hmore » annealing at 1100°C while recrystallization occurs within an hour of annealing at 1100°C and 1150°C in the 60% compressed samples. Moreover, the 60% compressed samples show {112}<110> and {112}<111> texture components during annealing, in contrast to the conventional recrystallization textures in body centered cubic alloys. Furthermore, nano-oxide size, shape, density and distribution are considerably different in unrecrystallized and abnormally grown grains. Transmission electron microscopy analysis shows that oxide particles having a size between 5 and 30 nm play a critical role for recrystallization mechanisms in 14YWT nanostructured ferritic alloys.« less

Textural variations and impact history of the Millbillillie eucrite

NASA Technical Reports Server (NTRS)

Yamaguchi, Akira; Takeda, Hiroshi; Bogard, Donald D.; Garrison, Daniel

1994-01-01

We have investigated 10 new specimens of the Millbillillie eucrite to study its textures and mineral compositions by electron probe microanalyser and scanning electron microscope. Although originally described as having fine-grained texture, the new specimens show diversity of texture. The compositions (Mg/Fe ratios) of the host pigeonites and augite lamellae are homogeneous, respectively, in spite of the textural variation. In addition to their chemical homogeneity, pyroxenes in coarse and fine-grained clasts are partly inverted to orthopyroxene. Chemical zoning of plagioclase during crystal growth is preserved. This eucrite includes areas of granulitic breccias and impact melts. Large scale textures show a subparallel layering suggesting incomplete mixing and deposition of impact melt and lithic fragments. An Ar-39-Ar-40 age determination for a coarse-grained clast indicates a strong degassing event at 3.55 +/- 0.02 Ga. We conclude that Millbillillie is among the most equilibriated eucrites produced by thermal annealing after impact brecciation. According to the classificcation of impact breccias, Millbillillie can be classified as a mixture of granulitic breccias and impact melts. The last significant thermal event is characterized by network-like glassy veins that run through clasts and matrices. Consideration of textual observations and requirements for Ar-degassing suggests that the Ar-39-Ar-40 age could in principle date either the earlier brecciation and annealing event or the event which produced the veins.

Dissociations between Featural versus Conjunction-based Texture Processing in Infancy: Analyses of Three Potential Contributing Factors.

ERIC Educational Resources Information Center

Bertin, Evelin; Bhatt, Ramesh S.

2001-01-01

Examined three possible explanations for findings that infants detect textural discrepancies based on individual features more readily than on feature conjunctions. Found that none of the proposed factors could explain 5.5-month-olds' superior processing of featural over conjunction-based textural discrepancies. Findings suggest that in infancy,…

Scattering properties of natural snow and frost - Comparison with icy satellite photometry

NASA Technical Reports Server (NTRS)

Verbiscer, Anne J.; Veverka, Joseph

1990-01-01

The Hapke (1986) equation is presently fit to ascertain the single-scattering albedo of the icy satellites of Uranus and Neptune and the one-term Henyey-Greenstein particle-phase function g for each of the Middleton and Mungall (1952) goniophotometric data samples. There emerge both very high single-scattering albedos and strongly forward-scattering particle phase functions; while these are in keeping with Mie theory-based theoretical considerations, they contrast with the observed backscattering behavior of icy satellites. It is suggested the icy satellite frost grains are aggregated into particles of complex texture, which produce the unusual backscattering behavior.

A Review on Inertia and Linear Friction Welding of Ni-Based Superalloys

NASA Astrophysics Data System (ADS)

Chamanfar, Ahmad; Jahazi, Mohammad; Cormier, Jonathan

2015-04-01

Inertia and linear friction welding are being increasingly used for near-net-shape manufacturing of high-value materials in aerospace and power generation gas turbines because of providing a better quality joint and offering many advantages over conventional fusion welding and mechanical joining techniques. In this paper, the published works up-to-date on inertia and linear friction welding of Ni-based superalloys are reviewed with the objective to make clarifications on discrepancies and uncertainties reported in literature regarding issues related to these two friction welding processes as well as microstructure, texture, and mechanical properties of the Ni-based superalloy weldments. Initially, the chemical composition and microstructure of Ni-based superalloys that contribute to the quality of the joint are reviewed briefly. Then, problems related to fusion welding of these alloys are addressed with due consideration of inertia and linear friction welding as alternative techniques. The fundamentals of inertia and linear friction welding processes are analyzed next with emphasis on the bonding mechanisms and evolution of temperature and strain rate across the weld interface. Microstructural features, texture development, residual stresses, and mechanical properties of similar and dissimilar polycrystalline and single crystal Ni-based superalloy weldments are discussed next. Then, application of inertia and linear friction welding for joining Ni-based superalloys and related advantages over fusion welding, mechanical joining, and machining are explained briefly. Finally, present scientific and technological challenges facing inertia and linear friction welding of Ni-based superalloys including those related to modeling of these processes are addressed.

Design, fabrication, and implementation of voxel-based 3D printed textured phantoms for task-based image quality assessment in CT

NASA Astrophysics Data System (ADS)

Solomon, Justin; Ba, Alexandre; Diao, Andrew; Lo, Joseph; Bier, Elianna; Bochud, François; Gehm, Michael; Samei, Ehsan

2016-03-01

In x-ray computed tomography (CT), task-based image quality studies are typically performed using uniform background phantoms with low-contrast signals. Such studies may have limited clinical relevancy for modern non-linear CT systems due to possible influence of background texture on image quality. The purpose of this study was to design and implement anatomically informed textured phantoms for task-based assessment of low-contrast detection. Liver volumes were segmented from 23 abdominal CT cases. The volumes were characterized in terms of texture features from gray-level co-occurrence and run-length matrices. Using a 3D clustered lumpy background (CLB) model, a fitting technique based on a genetic optimization algorithm was used to find the CLB parameters that were most reflective of the liver textures, accounting for CT system factors of spatial blurring and noise. With the modeled background texture as a guide, a cylinder phantom (165 mm in diameter and 30 mm height) was designed, containing 20 low-contrast spherical signals (6 mm in diameter at targeted contrast levels of ~3.2, 5.2, 7.2, 10, and 14 HU, 4 repeats per signal). The phantom was voxelized and input into a commercial multi-material 3D printer (Object Connex 350), with custom software for voxel-based printing. Using principles of digital half-toning and dithering, the 3D printer was programmed to distribute two base materials (VeroWhite and TangoPlus, nominal voxel size of 42x84x30 microns) to achieve the targeted spatial distribution of x-ray attenuation properties. The phantom was used for task-based image quality assessment of a clinically available iterative reconstruction algorithm (Sinogram Affirmed Iterative Reconstruction, SAFIRE) using a channelized Hotelling observer paradigm. Images of the textured phantom and a corresponding uniform phantom were acquired at six dose levels and observer model performance was estimated for each condition (5 contrasts x 6 doses x 2 reconstructions x 2 backgrounds = 120 total conditions). Based on the observer model results, the dose reduction potential of SAFIRE was computed and compared between the uniform and textured phantom. The dose reduction potential of SAFIRE was found to be 23% based on the uniform phantom and 17% based on the textured phantom. This discrepancy demonstrates the need to consider background texture when assessing non-linear reconstruction algorithms.

Texture control of zircaloy tubing during tube reduction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nagai, N.; Kakuma, T.; Fujita, K.

1982-01-01

Seven batches of Zircaloy-2 nuclear fuel cladding tubes with different textures were processed from tube shells of the same size, by different reduction routes, using pilger and 3-roll mills. Based on the texture data of these tubes, the texture control of Zircaloy tubing, the texture gradient across the wall, and the texture change during annealing were studied. The deformation texture of Zicaloy-2 tubing was dependent on the tool's curvature and was independent of the dimensions of the mother tubes. The different slopes of texture gradients were observed between the tubing of higher strain ration and that of lower strain ratio.

Light extraction efficiency of GaN-based LED with pyramid texture by using ray path analysis.

PubMed

Pan, Jui-Wen; Wang, Chia-Shen

2012-09-10

We study three different gallium-nitride (GaN) based light emitting diode (LED) cases based on the different locations of the pyramid textures. In case 1, the pyramid texture is located on the sapphire top surface, in case 2, the pyramid texture is locate on the P-GaN top surface, while in case 3, the pyramid texture is located on both the sapphire and P-GaN top surfaces. We study the relationship between the light extraction efficiency (LEE) and angle of slant of the pyramid texture. The optimization of total LEE was highest for case 3 among the three cases. Moreover, the seven escape paths along which most of the escaped photon flux propagated were selected in a simulation of the LEDs. The seven escape paths were used to estimate the slant angle for the optimization of LEE and to precisely analyze the photon escape path.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sorensen, J; Duran, C; Stingo, F

Purpose: To characterize the effect of virtual monochromatic reconstructions on several commonly used texture analysis features in DECT of the chest. Further, to assess the effect of monochromatic energy levels on the ability of these textural features to identify tissue types. Methods: 20 consecutive patients underwent chest CTs for evaluation of lung nodules using Siemens Somatom Definition Flash DECT. Virtual monochromatic images were constructed at 10keV intervals from 40–190keV. For each patient, an ROI delineated the lesion under investigation, and cylindrical ROI’s were placed within 5 different healthy tissues (blood, fat, muscle, lung, and liver). Several histogram- and Grey Levelmore » Cooccurrence Matrix (GLCM)-based texture features were then evaluated in each ROI at each energy level. As a means of validation, these feature values were then used in a random forest classifier to attempt to identify the tissue types present within each ROI. Their predictive accuracy at each energy level was recorded. Results: All textural features changed considerably with virtual monochromatic energy, particularly below 70keV. Most features exhibited a global minimum or maximum around 80keV, and while feature values changed with energy above this, patient ranking was generally unaffected. As expected, blood demonstrated the lowest inter-patient variability, for all features, while lung lesions (encompassing many different pathologies) exhibited the highest. The accuracy of these features in identifying tissues (76% accuracy) was highest at 80keV, but no clear relationship between energy and classification accuracy was found. Two common misclassifications (blood vs liver and muscle vs fat) accounted for the majority (24 of the 28) errors observed. Conclusion: All textural features were highly dependent on virtual monochromatic energy level, especially below 80keV, and were more stable above this energy. However, in a random forest model, these commonly used features were able to reliably differentiate between most tissues types regardless of energy level. Dr Godoy has received a dual-energy CT research grant from Siemens Healthcare. That grant did not directly fund this research.« less

Detecting perceptual groupings in textures by continuity considerations

NASA Technical Reports Server (NTRS)

Greene, Richard J.

1990-01-01

A generalization is presented for the second derivative of a Gaussian D(sup 2)G operator to apply to problems of perceptual organization involving textures. Extensions to other problems of perceptual organization are evident and a new research direction can be established. The technique presented is theoretically pleasing since it has the potential of unifying the entire area of image segmentation under the mathematical notion of continuity and presents a single algorithm to form perceptual groupings where many algorithms existed previously. The eventual impact on both the approach and technique of image processing segmentation operations could be significant.

Experimental Study on the Perception Characteristics of Haptic Texture by Multidimensional Scaling.

PubMed

Wu, Juan; Li, Na; Liu, Wei; Song, Guangming; Zhang, Jun

2015-01-01

Recent works regarding real texture perception demonstrate that physical factors such as stiffness and spatial period play a fundamental role in texture perception. This research used a multidimensional scaling (MDS) analysis to further characterize and quantify the effects of the simulation parameters on haptic texture rendering and perception. In a pilot experiment, 12 haptic texture samples were generated by using a 3-degrees-of-freedom (3-DOF) force-feedback device with varying spatial period, height, and stiffness coefficient parameter values. The subjects' perceptions of the virtual textures indicate that roughness, denseness, flatness and hardness are distinguishing characteristics of texture. In the main experiment, 19 participants rated the dissimilarities of the textures and estimated the magnitudes of their characteristics. The MDS method was used to recover the underlying perceptual space and reveal the significance of the space from the recorded data. The physical parameters and their combinations have significant effects on the perceptual characteristics. A regression model was used to quantitatively analyze the parameters and their effects on the perceptual characteristics. This paper is to illustrate that haptic texture perception based on force feedback can be modeled in two- or three-dimensional space and provide suggestions on improving perception-based haptic texture rendering.

A neural network detection model of spilled oil based on the texture analysis of SAR image

NASA Astrophysics Data System (ADS)

An, Jubai; Zhu, Lisong

2006-01-01

A Radial Basis Function Neural Network (RBFNN) Model is investigated for the detection of spilled oil based on the texture analysis of SAR imagery. In this paper, to take the advantage of the abundant texture information of SAR imagery, the texture features are extracted by both wavelet transform and the Gray Level Co-occurrence matrix. The RBFNN Model is fed with a vector of these texture features. The RBFNN Model is trained and tested by the sample data set of the feature vectors. Finally, a SAR image is classified by this model. The classification results of a spilled oil SAR image show that the classification accuracy for oil spill is 86.2 by the RBFNN Model using both wavelet texture and gray texture, while the classification accuracy for oil spill is 78.0 by same RBFNN Model using only wavelet texture as the input of this RBFNN model. The model using both wavelet transform and the Gray Level Co-occurrence matrix is more effective than that only using wavelet texture. Furthermore, it keeps the complicated proximity and has a good performance of classification.

Applying neutron transmission physics and 3D statistical full-field model to understand 2D Bragg-edge imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xie, Qingge; Song, Gian; Gorti, Sarma B.

Bragg-edge imaging, which is also known as neutron radiography, has recently emerged as a novel crystalline characterization technique. Modelling of this novel technique by incorporating various features of the underlying microstructure (including the crystallographic texture, the morphological texture, and the grain size) of the material remains a subject of considerable research and development. In this paper, Inconel 718 samples made by additive manufacturing were investigated by neutron diffraction and neutron radiography techniques. The specimen features strong morphological and crystallographic textures and a highly heterogeneous microstructure. A 3D statistical full-field model is introduced by taking details of the microstructure into accountmore » to understand the experimental neutron radiography results. The Bragg-edge imaging and the total cross section were calculated based on the neutron transmission physics. A good match was obtained between the model predictions and experimental results at different incident beam angles with respect to the sample build direction. The current theoretical approach has the ability to incorporate 3D spatially resolved microstructural heterogeneity information and shows promise in understanding the 2D neutron radiography of bulk samples. With further development to incorporate the heterogeneity in lattice strain in the model, it can be used as a powerful tool in the future to better understand the neutron radiography data.« less

The making of the architecture of the plant cell wall: how cells exploit geometry.

PubMed

Emons, A M; Mulder, B M

1998-06-09

Cell wall deposition is a key process in the formation, growth, and differentiation of plant cells. The most important structural components of the wall are long cellulose microfibrils, which are synthesized by synthases embedded in the plasma membrane. A fundamental question is how the microfibrils become oriented during deposition at the plasma membrane. The current textbook explanation for the orientation mechanism is a guidance system mediated by cortical microtubules. However, too many contraindications are known in secondary cell walls for this to be a universal mechanism, particularly in the case of helicoidal arrangements, which occur in many situations. An additional construction mechanism involves liquid crystalline self-assembly [A. C. Neville (1993) Biology of Fibrous Composites: Development Beyond the Cell Membrane (Cambridge Univ. Press, Cambridge, U.K.)], but the required amount of bulk material that is able to equilibrate thermally is not normally present at any stage of the wall deposition process. Therefore, we have asked whether the complex ordered texture of helicoidal cell walls can be formed in the absence of direct cellular guidance mechanisms. We propose that they can be formed by a mechanism that is based on geometrical considerations. It explains the genesis of the complicated helicoidal texture and shows that the cell has intrinsic, versatile tools for creating a variety of textures. A compelling feature of the model is that local rules generate global order, a typical phenomenon of life.

Applying neutron transmission physics and 3D statistical full-field model to understand 2D Bragg-edge imaging

DOE PAGES

Xie, Qingge; Song, Gian; Gorti, Sarma B.; ...

2018-02-21

Bragg-edge imaging, which is also known as neutron radiography, has recently emerged as a novel crystalline characterization technique. Modelling of this novel technique by incorporating various features of the underlying microstructure (including the crystallographic texture, the morphological texture, and the grain size) of the material remains a subject of considerable research and development. In this paper, Inconel 718 samples made by additive manufacturing were investigated by neutron diffraction and neutron radiography techniques. The specimen features strong morphological and crystallographic textures and a highly heterogeneous microstructure. A 3D statistical full-field model is introduced by taking details of the microstructure into accountmore » to understand the experimental neutron radiography results. The Bragg-edge imaging and the total cross section were calculated based on the neutron transmission physics. A good match was obtained between the model predictions and experimental results at different incident beam angles with respect to the sample build direction. The current theoretical approach has the ability to incorporate 3D spatially resolved microstructural heterogeneity information and shows promise in understanding the 2D neutron radiography of bulk samples. With further development to incorporate the heterogeneity in lattice strain in the model, it can be used as a powerful tool in the future to better understand the neutron radiography data.« less

Analysis of microstructures and macrotextures for different apple cultivars based on parenchyma morphology.

PubMed

Hou, Jumin; Sun, Yonghai; Chen, Fangyuan; Yu, Libo; Mao, Qian; Wang, Lu; Guo, Xiaolei; Liu, Chao

2016-04-01

Fuji, Golden Delicious, and Jonagold parenchyma were imaged by confocal laser scanning microscopy to be extracted morphology characteristics, which were used to analyze the relationship with macrotexture of apples tested by penetration and compression. Before analyzing the relationship, the significantly different morphology parameters were reduced in dimensions by principal component analysis and were proved to be availably used for distinguishing the different apple cultivars. For compression results, cell did not absolutely determine the hardness in different apple cultivars, and the pore should also be taken into consideration. With the same size in cell feret diameter, the bigger the pore feret diameter was, the softer the apple became. If no difference existed in pore feret diameter size, the cultivar became harder with a narrower distribution in cell feret diameter. The texture parameters were compared with the roundness parameters in the same or inverse changing trends to explore the relationship. High correlations were found between the texture parameters (energy required in whole penetration (Wt), fracture force (Fp), crispness) and pore solidity (R(2)  > 0.924, P < 0.001). Compactness of parenchyma played an important role in fruit texture. This research could provide the comprehension about relationship between microstructure and macrotexture of apple cultivars and morphological values for modeling apple parenchyma, contributing to numerical simulation for constitutive relation of fruit. © 2016 Wiley Periodicals, Inc.

[Visual Texture Agnosia in Humans].

PubMed

Suzuki, Kyoko

2015-06-01

Visual object recognition requires the processing of both geometric and surface properties. Patients with occipital lesions may have visual agnosia, which is impairment in the recognition and identification of visually presented objects primarily through their geometric features. An analogous condition involving the failure to recognize an object by its texture may exist, which can be called visual texture agnosia. Here we present two cases with visual texture agnosia. Case 1 had left homonymous hemianopia and right upper quadrantanopia, along with achromatopsia, prosopagnosia, and texture agnosia, because of damage to his left ventromedial occipitotemporal cortex and right lateral occipito-temporo-parietal cortex due to multiple cerebral embolisms. Although he showed difficulty matching and naming textures of real materials, he could readily name visually presented objects by their contours. Case 2 had right lower quadrantanopia, along with impairment in stereopsis and recognition of texture in 2D images, because of subcortical hemorrhage in the left occipitotemporal region. He failed to recognize shapes based on texture information, whereas shape recognition based on contours was well preserved. Our findings, along with those of three reported cases with texture agnosia, indicate that there are separate channels for processing texture, color, and geometric features, and that the regions around the left collateral sulcus are crucial for texture processing.

Chemometric approach to texture profile analysis of kombucha fermented milk products.

PubMed

Malbaša, Radomir; Jevrić, Lidija; Lončar, Eva; Vitas, Jasmina; Podunavac-Kuzmanović, Sanja; Milanović, Spasenija; Kovačević, Strahinja

2015-09-01

In the present work, relationships between the textural characteristics of fermented milk products obtained by kombucha inoculums with various teas were investigated by using chemometric analysis. The presented data which describe numerically the textural characteristics (firmness, consistency, cohesiveness and index of viscosity) were analysed. The quadratic correlation was determined between the textural characteristics of fermented milk products obtained at fermentation temperatures of 40 and 43 °C, using milk with 0.8, 1.6 and 2.8% milk fat and kombucha inoculums cultivated on the extracts of peppermint, stinging nettle, wild thyme and winter savory. Hierarchical cluster analysis (HCA) was performed to identify the similarities among the fermented products. The best mathematical models predicting the textural characteristics of investigated samples were developed. The results of this study indicate that textural characteristics of sample based on winter savory have a significant effect on textural characteristics of samples based on peppermint, stinging nettle and wild thyme, which can be very useful in the determination of products texture profile.

Texture-specific bag of visual words model and spatial cone matching-based method for the retrieval of focal liver lesions using multiphase contrast-enhanced CT images.

PubMed

Xu, Yingying; Lin, Lanfen; Hu, Hongjie; Wang, Dan; Zhu, Wenchao; Wang, Jian; Han, Xian-Hua; Chen, Yen-Wei

2018-01-01

The bag of visual words (BoVW) model is a powerful tool for feature representation that can integrate various handcrafted features like intensity, texture, and spatial information. In this paper, we propose a novel BoVW-based method that incorporates texture and spatial information for the content-based image retrieval to assist radiologists in clinical diagnosis. This paper presents a texture-specific BoVW method to represent focal liver lesions (FLLs). Pixels in the region of interest (ROI) are classified into nine texture categories using the rotation-invariant uniform local binary pattern method. The BoVW-based features are calculated for each texture category. In addition, a spatial cone matching (SCM)-based representation strategy is proposed to describe the spatial information of the visual words in the ROI. In a pilot study, eight radiologists with different clinical experience performed diagnoses for 20 cases with and without the top six retrieved results. A total of 132 multiphase computed tomography volumes including five pathological types were collected. The texture-specific BoVW was compared to other BoVW-based methods using the constructed dataset of FLLs. The results show that our proposed model outperforms the other three BoVW methods in discriminating different lesions. The SCM method, which adds spatial information to the orderless BoVW model, impacted the retrieval performance. In the pilot trial, the average diagnosis accuracy of the radiologists was improved from 66 to 80% using the retrieval system. The preliminary results indicate that the texture-specific features and the SCM-based BoVW features can effectively characterize various liver lesions. The retrieval system has the potential to improve the diagnostic accuracy and the confidence of the radiologists.

Standardizing texture and facies codes for a process-based classification of clastic sediment and rock

USGS Publications Warehouse

Farrell, K.M.; Harris, W.B.; Mallinson, D.J.; Culver, S.J.; Riggs, S.R.; Pierson, J.; ,; Lautier, J.C.

2012-01-01

Proposed here is a universally applicable, texturally based classification of clastic sediment that is independent from composition, cementation, and geologic environment, is closely allied to process sedimentology, and applies to all compartments in the source-to-sink system. The classification is contingent on defining the term "clastic" so that it is independent from composition or origin and includes any particles or grains that are subject to erosion, transportation, and deposition. Modifications to Folk's (1980) texturally based classification that include applying new assumptions and defining a broader array of textural fields are proposed to accommodate this. The revised ternary diagrams include additional textural fields that better define poorly sorted and coarse-grained deposits, so that all end members (gravel, sand, and mud size fractions) are included in textural codes. Revised textural fields, or classes, are based on a strict adherence to volumetric estimates of percentages of gravel, sand, and mud size grain populations, which by definition must sum to 100%. The new classification ensures that descriptors are applied consistently to all end members in the ternary diagram (gravel, sand, and mud) according to several rules, and that none of the end members are ignored. These modifications provide bases for standardizing vertical displays of texture in graphic logs, lithofacies codes, and their derivatives- hydrofacies. Hydrofacies codes are nondirectional permeability indicators that predict aquifer or reservoir potential. Folk's (1980) ternary diagram for fine-grained clastic sediments (sand, silt, and clay size fractions) is also revised to preserve consistency with the revised diagram for gravel, sand, and mud. Standardizing texture ensures that the principles of process sedimentology are consistently applied to compositionally variable rock sequences, such as mixed carbonate-siliciclastic ramp settings, and the extreme ends of depositional systems.

Mechanical and Metallurgical Evolution of Stainless Steel 321 in a Multi-step Forming Process

NASA Astrophysics Data System (ADS)

Anderson, M.; Bridier, F.; Gholipour, J.; Jahazi, M.; Wanjara, P.; Bocher, P.; Savoie, J.

2016-04-01

This paper examines the metallurgical evolution of AISI Stainless Steel 321 (SS 321) during multi-step forming, a process that involves cycles of deformation with intermediate heat treatment steps. The multi-step forming process was simulated by implementing interrupted uniaxial tensile testing experiments. Evolution of the mechanical properties as well as the microstructural features, such as twins and textures of the austenite and martensite phases, was studied as a function of the multi-step forming process. The characteristics of the Strain-Induced Martensite (SIM) were also documented for each deformation step and intermediate stress relief heat treatment. The results indicated that the intermediate heat treatments considerably increased the formability of SS 321. Texture analysis showed that the effect of the intermediate heat treatment on the austenite was minor and led to partial recrystallization, while deformation was observed to reinforce the crystallographic texture of austenite. For the SIM, an Olson-Cohen equation type was identified to analytically predict its formation during the multi-step forming process. The generated SIM was textured and weakened with increasing deformation.

Temporal evolution of soil moisture statistical fractal and controls by soil texture and regional groundwater flow

NASA Astrophysics Data System (ADS)

Ji, Xinye; Shen, Chaopeng; Riley, William J.

2015-12-01

Soil moisture statistical fractal is an important tool for downscaling remotely-sensed observations and has the potential to play a key role in multi-scale hydrologic modeling. The fractal was first introduced two decades ago, but relatively little is known regarding how its scaling exponents evolve in time in response to climatic forcings. Previous studies have neglected the process of moisture re-distribution due to regional groundwater flow. In this study we used a physically-based surface-subsurface processes model and numerical experiments to elucidate the patterns and controls of fractal temporal evolution in two U.S. Midwest basins. Groundwater flow was found to introduce large-scale spatial structure, thereby reducing the scaling exponents (τ), which has implications for the transferability of calibrated parameters to predict τ. However, the groundwater effects depend on complex interactions with other physical controls such as soil texture and land use. The fractal scaling exponents, while in general showing a seasonal mode that correlates with mean moisture content, display hysteresis after storm events that can be divided into three phases, consistent with literature findings: (a) wetting, (b) re-organizing, and (c) dry-down. Modeling experiments clearly show that the hysteresis is attributed to soil texture, whose "patchiness" is the primary contributing factor. We generalized phenomenological rules for the impacts of rainfall, soil texture, groundwater flow, and land use on τ evolution. Grid resolution has a mild influence on the results and there is a strong correlation between predictions of τ from different resolutions. Overall, our results suggest that groundwater flow should be given more consideration in studies of the soil moisture statistical fractal, especially in regions with a shallow water table.

Identification of tectonically controlled serpentinite intrusion: Examples from Franciscan serpentinites, Gorda, California

NASA Astrophysics Data System (ADS)

Hirauchi, K.

2006-12-01

Serpentinite bodies, zonally occurring as a component of fault zones, without any association with ophiolitic rocks might be a mantle in origin tectonically intruded from a considerable depth. Typical occurrences of serpentinites that experienced a unique emplacement process different from surrounding rocks are found in the Sand Dollar Beach, Gorda, California. The serpentinite bodies are widely outcropped in the Franciscan Complex. All the serpentinites exhibit a block-in-matrix fabric, the blocks of which are classified into either massive or schistose types. The former retains relict minerals such as olivine, orthopyroxene and clinopyroxene and chromian spinel, and has serpentine minerals (lizardite and chrysotile) of mesh texture and bastite. The latter is characterized by ribbon textures as ductilely deformed mesh textures. The matrix is composed of aligned tabular lizardite, penetrating into the interior core of the blocks. The schistosities in the blocks and the attitude of the foliated matrix are both consistent with the elongate direction of the larger serpentinite bodies. The massive mesh textures is converted by the schistose ribbon textures with ductile deformation, further penetrated by tabular lizardite of the matrix. These series of the continuous deformation and recrystallization may occur along a regional deep fault zone, after undergoing partial serpentinization at lower crust and upper mantle.

The texture, sensory properties and stability of cookies prepared with wax oleogels.

PubMed

Yılmaz, Emin; Öğütcü, Mustafa

2015-04-01

Shortening is the essential component of high quality baked foods. Its effects on dough structure formation and the desired final product attributes depend mostly on its solid fat content and β' crystalline polymorphs. Saturated and trans fatty acids present in shortening pose some important negative health considerations. Hence, alternative plastic fats with lower or zero quantity of saturated and trans fatty acids are in high demand. Oleogels are gel networks of liquid edible oils with no trans and very low saturated fatty acids. In this study, sunflower wax (SW) and beeswax (BW) oleogels of hazelnut oil were used in cookie preparation against commercial bakery shortening (CBS) as the control, to compare the textural, sensory and stability properties of the cookies. The basic chemical composition, textural properties, and some physical attributes of the cookies were compared. Sensory texture/flavor profile analysis (T/FPA) and consumer hedonic tests were also accomplished. Furthermore, the changes in cookie texture and stability were monitored during 30 day storage at room temperature. It was found out that in almost all properties, the oleogel cookies resembled CBS cookies. T/FPA results present detailed data for literature. Consumer hedonic scores indicated that oleogel cookies were better than CBS cookies and were also well accepted by consumers. Wax oleogels can be used as cookie shortening successfully.

Numerosity but not texture-density discrimination correlates with math ability in children.

PubMed

Anobile, Giovanni; Castaldi, Elisa; Turi, Marco; Tinelli, Francesca; Burr, David C

2016-08-01

Considerable recent work suggests that mathematical abilities in children correlate with the ability to estimate numerosity. Does math correlate only with numerosity estimation, or also with other similar tasks? We measured discrimination thresholds of school-age (6- to 12.5-years-old) children in 3 tasks: numerosity of patterns of relatively sparse, segregatable items (24 dots); numerosity of very dense textured patterns (250 dots); and discrimination of direction of motion. Thresholds in all tasks improved with age, but at different rates, implying the action of different mechanisms: In particular, in young children, thresholds were lower for sparse than textured patterns (the opposite of adults), suggesting earlier maturation of numerosity mechanisms. Importantly, numerosity thresholds for sparse stimuli correlated strongly with math skills, even after controlling for the influence of age, gender and nonverbal IQ. However, neither motion-direction discrimination nor numerosity discrimination of texture patterns showed a significant correlation with math abilities. These results provide further evidence that numerosity and texture-density are perceived by independent neural mechanisms, which develop at different rates; and importantly, only numerosity mechanisms are related to math. As developmental dyscalculia is characterized by a profound deficit in discriminating numerosity, it is fundamental to understand the mechanism behind the discrimination. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Aesthetics by Numbers: Links between Perceived Texture Qualities and Computed Visual Texture Properties.

PubMed

Jacobs, Richard H A H; Haak, Koen V; Thumfart, Stefan; Renken, Remco; Henson, Brian; Cornelissen, Frans W

2016-01-01

Our world is filled with texture. For the human visual system, this is an important source of information for assessing environmental and material properties. Indeed-and presumably for this reason-the human visual system has regions dedicated to processing textures. Despite their abundance and apparent relevance, only recently the relationships between texture features and high-level judgments have captured the interest of mainstream science, despite long-standing indications for such relationships. In this study, we explore such relationships, as these might be used to predict perceived texture qualities. This is relevant, not only from a psychological/neuroscience perspective, but also for more applied fields such as design, architecture, and the visual arts. In two separate experiments, observers judged various qualities of visual textures such as beauty, roughness, naturalness, elegance, and complexity. Based on factor analysis, we find that in both experiments, ~75% of the variability in the judgments could be explained by a two-dimensional space, with axes that are closely aligned to the beauty and roughness judgments. That a two-dimensional judgment space suffices to capture most of the variability in the perceived texture qualities suggests that observers use a relatively limited set of internal scales on which to base various judgments, including aesthetic ones. Finally, for both of these judgments, we determined the relationship with a large number of texture features computed for each of the texture stimuli. We find that the presence of lower spatial frequencies, oblique orientations, higher intensity variation, higher saturation, and redness correlates with higher beauty ratings. Features that captured image intensity and uniformity correlated with roughness ratings. Therefore, a number of computational texture features are predictive of these judgments. This suggests that perceived texture qualities-including the aesthetic appreciation-are sufficiently universal to be predicted-with reasonable accuracy-based on the computed feature content of the textures.

Aesthetics by Numbers: Links between Perceived Texture Qualities and Computed Visual Texture Properties

PubMed Central

Jacobs, Richard H. A. H.; Haak, Koen V.; Thumfart, Stefan; Renken, Remco; Henson, Brian; Cornelissen, Frans W.

2016-01-01

Our world is filled with texture. For the human visual system, this is an important source of information for assessing environmental and material properties. Indeed—and presumably for this reason—the human visual system has regions dedicated to processing textures. Despite their abundance and apparent relevance, only recently the relationships between texture features and high-level judgments have captured the interest of mainstream science, despite long-standing indications for such relationships. In this study, we explore such relationships, as these might be used to predict perceived texture qualities. This is relevant, not only from a psychological/neuroscience perspective, but also for more applied fields such as design, architecture, and the visual arts. In two separate experiments, observers judged various qualities of visual textures such as beauty, roughness, naturalness, elegance, and complexity. Based on factor analysis, we find that in both experiments, ~75% of the variability in the judgments could be explained by a two-dimensional space, with axes that are closely aligned to the beauty and roughness judgments. That a two-dimensional judgment space suffices to capture most of the variability in the perceived texture qualities suggests that observers use a relatively limited set of internal scales on which to base various judgments, including aesthetic ones. Finally, for both of these judgments, we determined the relationship with a large number of texture features computed for each of the texture stimuli. We find that the presence of lower spatial frequencies, oblique orientations, higher intensity variation, higher saturation, and redness correlates with higher beauty ratings. Features that captured image intensity and uniformity correlated with roughness ratings. Therefore, a number of computational texture features are predictive of these judgments. This suggests that perceived texture qualities—including the aesthetic appreciation—are sufficiently universal to be predicted—with reasonable accuracy—based on the computed feature content of the textures. PMID:27493628

Power spectral ensity of markov texture fields

NASA Technical Reports Server (NTRS)

Shanmugan, K. S.; Holtzman, J. C.

1984-01-01

Texture is an important image characteristic. A variety of spatial domain techniques were proposed for extracting and utilizing textural features for segmenting and classifying images. for the most part, these spatial domain techniques are ad hos in nature. A markov random field model for image texture is discussed. A frequency domain description of image texture is derived in terms of the power spectral density. This model is used for designing optimum frequency domain filters for enhancing, restoring and segmenting images based on their textural properties.

Evolution of solidification texture during additive manufacturing.

PubMed

Wei, H L; Mazumder, J; DebRoy, T

2015-11-10

Striking differences in the solidification textures of a nickel based alloy owing to changes in laser scanning pattern during additive manufacturing are examined based on theory and experimental data. Understanding and controlling texture are important because it affects mechanical and chemical properties. Solidification texture depends on the local heat flow directions and competitive grain growth in one of the six <100> preferred growth directions in face centered cubic alloys. Therefore, the heat flow directions are examined for various laser beam scanning patterns based on numerical modeling of heat transfer and fluid flow in three dimensions. Here we show that numerical modeling can not only provide a deeper understanding of the solidification growth patterns during the additive manufacturing, it also serves as a basis for customizing solidification textures which are important for properties and performance of components.

Artificial intelligence systems based on texture descriptors for vaccine development.

PubMed

Nanni, Loris; Brahnam, Sheryl; Lumini, Alessandra

2011-02-01

The aim of this work is to analyze and compare several feature extraction methods for peptide classification that are based on the calculation of texture descriptors starting from a matrix representation of the peptide. This texture-based representation of the peptide is then used to train a support vector machine classifier. In our experiments, the best results are obtained using local binary patterns variants and the discrete cosine transform with selected coefficients. These results are better than those previously reported that employed texture descriptors for peptide representation. In addition, we perform experiments that combine standard approaches based on amino acid sequence. The experimental section reports several tests performed on a vaccine dataset for the prediction of peptides that bind human leukocyte antigens and on a human immunodeficiency virus (HIV-1). Experimental results confirm the usefulness of our novel descriptors. The matlab implementation of our approaches is available at http://bias.csr.unibo.it/nanni/TexturePeptide.zip.

Orientation selectivity based structure for texture classification

NASA Astrophysics Data System (ADS)

Wu, Jinjian; Lin, Weisi; Shi, Guangming; Zhang, Yazhong; Lu, Liu

2014-10-01

Local structure, e.g., local binary pattern (LBP), is widely used in texture classification. However, LBP is too sensitive to disturbance. In this paper, we introduce a novel structure for texture classification. Researches on cognitive neuroscience indicate that the primary visual cortex presents remarkable orientation selectivity for visual information extraction. Inspired by this, we investigate the orientation similarities among neighbor pixels, and propose an orientation selectivity based pattern for local structure description. Experimental results on texture classification demonstrate that the proposed structure descriptor is quite robust to disturbance.

Image segmentation using association rule features.

PubMed

Rushing, John A; Ranganath, Heggere; Hinke, Thomas H; Graves, Sara J

2002-01-01

A new type of texture feature based on association rules is described. Association rules have been used in applications such as market basket analysis to capture relationships present among items in large data sets. It is shown that association rules can be adapted to capture frequently occurring local structures in images. The frequency of occurrence of these structures can be used to characterize texture. Methods for segmentation of textured images based on association rule features are described. Simulation results using images consisting of man made and natural textures show that association rule features perform well compared to other widely used texture features. Association rule features are used to detect cumulus cloud fields in GOES satellite images and are found to achieve higher accuracy than other statistical texture features for this problem.

Research of second harmonic generation images based on texture analysis

NASA Astrophysics Data System (ADS)

Liu, Yao; Li, Yan; Gong, Haiming; Zhu, Xiaoqin; Huang, Zufang; Chen, Guannan

2014-09-01

Texture analysis plays a crucial role in identifying objects or regions of interest in an image. It has been applied to a variety of medical image processing, ranging from the detection of disease and the segmentation of specific anatomical structures, to differentiation between healthy and pathological tissues. Second harmonic generation (SHG) microscopy as a potential noninvasive tool for imaging biological tissues has been widely used in medicine, with reduced phototoxicity and photobleaching. In this paper, we clarified the principles of texture analysis including statistical, transform, structural and model-based methods and gave examples of its applications, reviewing studies of the technique. Moreover, we tried to apply texture analysis to the SHG images for the differentiation of human skin scar tissues. Texture analysis method based on local binary pattern (LBP) and wavelet transform was used to extract texture features of SHG images from collagen in normal and abnormal scars, and then the scar SHG images were classified into normal or abnormal ones. Compared with other texture analysis methods with respect to the receiver operating characteristic analysis, LBP combined with wavelet transform was demonstrated to achieve higher accuracy. It can provide a new way for clinical diagnosis of scar types. At last, future development of texture analysis in SHG images were discussed.

Chicken eggshell as suitable calcium source at home.

PubMed

Brun, Lucas R; Lupo, Maela; Delorenzi, Damián A; Di Loreto, Verónica E; Rigalli, Alfredo

2013-09-01

Taken into consideration that the deficiency of calcium (Ca) in the diet is a common problem, the aim of this work was to study the chicken eggshell as Ca source at home. It was evaluated: (1) different mechanisms to process eggshells and find an easy way to determine the required amount of Ca at home and; (2) the flavor and the texture for eggshell fortified food. Chemical and mechanical methods of eggshell processing were evaluated. Changes in flavor and texture were evaluated in volunteers coordinated by a professional chef. A single eggshell contains 2.07 ± 0.18 g of Ca; therefore half an eggshell could provide the amount of Ca needed by adult human beings per day. The best way to use chicken eggshell as Ca dietary supplement is powdered to add to bread, pizza or spaghetti as there were small changes in texture and no changes in flavor.

Inertial effects in systems with magnetic charge

NASA Astrophysics Data System (ADS)

Armitage, N. P.

2018-05-01

This short article sets out some of the basic considerations that go into detecting the mass of quasiparticles with effective magnetic charge in solids. Effective magnetic charges may be appear as defects in particular magnetic textures. A magnetic monopole is a defect in this texture and as such these are not monopoles in the actual magnetic field B, but instead in the auxiliary field H. They may have particular properties expected for such quasiparticles such as magnetic charge and mass. This effective mass may-in principle-be detected in the same fashion that the mass is detected of other particles classically e.g. through their inertial response to time-dependent electromagnetic fields. I discuss this physics in the context of the "simple" case of the quantum spin ices, but aspects are broadly applicable. Based on extensions to Ryzkhin's model for classical spin ice, a hydrodynamic formulation can be given that takes into account inertial and entropic forces. Ultimately, a form for the susceptibility is obtained that is equivalent to the Rocard equation, which is a classic form used to account for inertial effects in the context of Debye-like relaxation.

Microcapsule Structure with a Tunable Textured Surface via the Assembly of Polyoxomolybdate Clusters: A Bioinspired Strategy and Enhanced Activities in Alkene Oxidation.

PubMed

Chilivery, Rakesh; Rana, Rohit Kumar

2017-01-25

A polyamine-mediated bioinspired strategy to assemble Keggin-type phosphomolybdic acid (PMA) clusters is demonstrated for the fabrication of microcapsule (MC) structures with unique surface textures. It involves supramolecular aggregation of polyamines with multivalent anions, which then allows the assembly of negatively charged PMA into MCs in an aqueous medium under ambient conditions. Resembling the role of polyamines in biosilicification of diatoms, the polyamine-anion interaction is shown to be the key for the assembly process. It not only provides structural stability but also facilitates an interesting transition from a smooth to a wrinkled surface alongside a change in the Keggin form to its lacunary form depending on the pH of the medium. Moreover, the presence of isolated PMA units in the hybrid structure enables them to be active in catalyzing the aerobic oxidation of alkenes under solvent-free conditions with better selectivity and reusability. Hence, the assembly approach represents an effective way for heterogenization of PMA-based materials and is expected to find considerable application in the wider hybrid-cluster field.

A methodology for the semi-automatic digital image analysis of fragmental impactites

NASA Astrophysics Data System (ADS)

Chanou, A.; Osinski, G. R.; Grieve, R. A. F.

2014-04-01

A semi-automated digital image analysis method is developed for the comparative textural study of impact melt-bearing breccias. This method uses the freeware software ImageJ developed by the National Institute of Health (NIH). Digital image analysis is performed on scans of hand samples (10-15 cm across), based on macroscopic interpretations of the rock components. All image processing and segmentation are done semi-automatically, with the least possible manual intervention. The areal fraction of components is estimated and modal abundances can be deduced, where the physical optical properties (e.g., contrast, color) of the samples allow it. Other parameters that can be measured include, for example, clast size, clast-preferred orientations, average box-counting dimension or fragment shape complexity, and nearest neighbor distances (NnD). This semi-automated method allows the analysis of a larger number of samples in a relatively short time. Textures, granulometry, and shape descriptors are of considerable importance in rock characterization. The methodology is used to determine the variations of the physical characteristics of some examples of fragmental impactites.

Cloud field classification based on textural features

NASA Technical Reports Server (NTRS)

Sengupta, Sailes Kumar

1989-01-01

An essential component in global climate research is accurate cloud cover and type determination. Of the two approaches to texture-based classification (statistical and textural), only the former is effective in the classification of natural scenes such as land, ocean, and atmosphere. In the statistical approach that was adopted, parameters characterizing the stochastic properties of the spatial distribution of grey levels in an image are estimated and then used as features for cloud classification. Two types of textural measures were used. One is based on the distribution of the grey level difference vector (GLDV), and the other on a set of textural features derived from the MaxMin cooccurrence matrix (MMCM). The GLDV method looks at the difference D of grey levels at pixels separated by a horizontal distance d and computes several statistics based on this distribution. These are then used as features in subsequent classification. The MaxMin tectural features on the other hand are based on the MMCM, a matrix whose (I,J)th entry give the relative frequency of occurrences of the grey level pair (I,J) that are consecutive and thresholded local extremes separated by a given pixel distance d. Textural measures are then computed based on this matrix in much the same manner as is done in texture computation using the grey level cooccurrence matrix. The database consists of 37 cloud field scenes from LANDSAT imagery using a near IR visible channel. The classification algorithm used is the well known Stepwise Discriminant Analysis. The overall accuracy was estimated by the percentage or correct classifications in each case. It turns out that both types of classifiers, at their best combination of features, and at any given spatial resolution give approximately the same classification accuracy. A neural network based classifier with a feed forward architecture and a back propagation training algorithm is used to increase the classification accuracy, using these two classes of features. Preliminary results based on the GLDV textural features alone look promising.

Reframing Children's Spaces

ERIC Educational Resources Information Center

Duncan, Sandra

2011-01-01

Like professional photographers, early childhood teachers can reframe their perspectives to create innovative and inspiring spaces for young children by concentrating on reframing two design elements: color and texture. When thinking about designing spaces for young children, one of the first considerations is the equipment and its arrangement.…

Evolution of solidification texture during additive manufacturing

PubMed Central

Wei, H. L.; Mazumder, J.; DebRoy, T.

2015-01-01

Striking differences in the solidification textures of a nickel based alloy owing to changes in laser scanning pattern during additive manufacturing are examined based on theory and experimental data. Understanding and controlling texture are important because it affects mechanical and chemical properties. Solidification texture depends on the local heat flow directions and competitive grain growth in one of the six <100> preferred growth directions in face centered cubic alloys. Therefore, the heat flow directions are examined for various laser beam scanning patterns based on numerical modeling of heat transfer and fluid flow in three dimensions. Here we show that numerical modeling can not only provide a deeper understanding of the solidification growth patterns during the additive manufacturing, it also serves as a basis for customizing solidification textures which are important for properties and performance of components. PMID:26553246

Evolution of solidification texture during additive manufacturing

DOE PAGES

Wei, H. L.; Mazumder, J.; DebRoy, T.

2015-11-10

Striking differences in the solidification textures of a nickel based alloy owing to changes in laser scanning pattern during additive manufacturing are examined based on theory and experimental data. Understanding and controlling texture are important because it affects mechanical and chemical properties. Solidification texture depends on the local heat flow directions and competitive grain growth in one of the six <100> preferred growth directions in face centered cubic alloys. Furthermore, the heat flow directions are examined for various laser beam scanning patterns based on numerical modeling of heat transfer and fluid flow in three dimensions. Here we show that numericalmore » modeling can not only provide a deeper understanding of the solidification growth patterns during the additive manufacturing, it also serves as a basis for customizing solidification textures which are important for properties and performance of components.« less

Detection of small bowel tumors in capsule endoscopy frames using texture analysis based on the discrete wavelet transform.

PubMed

Barbosa, Daniel J C; Ramos, Jaime; Lima, Carlos S

2008-01-01

Capsule endoscopy is an important tool to diagnose tumor lesions in the small bowel. The capsule endoscopic images possess vital information expressed by color and texture. This paper presents an approach based in the textural analysis of the different color channels, using the wavelet transform to select the bands with the most significant texture information. A new image is then synthesized from the selected wavelet bands, trough the inverse wavelet transform. The features of each image are based on second-order textural information, and they are used in a classification scheme using a multilayer perceptron neural network. The proposed methodology has been applied in real data taken from capsule endoscopic exams and reached 98.7% sensibility and 96.6% specificity. These results support the feasibility of the proposed algorithm.

An automatically generated texture-based atlas of the lungs

NASA Astrophysics Data System (ADS)

Dicente Cid, Yashin; Puonti, Oula; Platon, Alexandra; Van Leemput, Koen; Müller, Henning; Poletti, Pierre-Alexandre

2018-02-01

Many pulmonary diseases can be characterized by visual abnormalities on lung CT scans. Some diseases manifest similar defects but require completely different treatments, as is the case for Pulmonary Hypertension (PH) and Pulmonary Embolism (PE): both present hypo- and hyper-perfused regions but with different distribution across the lung and require different treatment protocols. Finding these distributions by visual inspection is not trivial even for trained radiologists who currently use invasive catheterism to diagnose PH. A Computer-Aided Diagnosis (CAD) tool that could facilitate the non-invasive diagnosis of these diseases can benefit both the radiologists and the patients. Most of the visual differences in the parenchyma can be characterized using texture descriptors. Current CAD systems often use texture information but the texture is either computed in a patch-based fashion, or based on an anatomical division of the lung. The difficulty of precisely finding these divisions in abnormal lungs calls for new tools for obtaining new meaningful divisions of the lungs. In this paper we present a method for unsupervised segmentation of lung CT scans into subregions that are similar in terms of texture and spatial proximity. To this extent, we combine a previously validated Riesz-wavelet texture descriptor with a well-known superpixel segmentation approach that we extend to 3D. We demonstrate the feasibility and accuracy of our approach on a simulated texture dataset, and show preliminary results for CT scans of the lung comparing subjects suffering either from PH or PE. The resulting texture-based atlas of individual lungs can potentially help physicians in diagnosis or be used for studying common texture distributions related to other diseases.

Parenchymal texture analysis in digital mammography: A fully automated pipeline for breast cancer risk assessment.

PubMed

Zheng, Yuanjie; Keller, Brad M; Ray, Shonket; Wang, Yan; Conant, Emily F; Gee, James C; Kontos, Despina

2015-07-01

Mammographic percent density (PD%) is known to be a strong risk factor for breast cancer. Recent studies also suggest that parenchymal texture features, which are more granular descriptors of the parenchymal pattern, can provide additional information about breast cancer risk. To date, most studies have measured mammographic texture within selected regions of interest (ROIs) in the breast, which cannot adequately capture the complexity of the parenchymal pattern throughout the whole breast. To better characterize patterns of the parenchymal tissue, the authors have developed a fully automated software pipeline based on a novel lattice-based strategy to extract a range of parenchymal texture features from the entire breast region. Digital mammograms from 106 cases with 318 age-matched controls were retrospectively analyzed. The lattice-based approach is based on a regular grid virtually overlaid on each mammographic image. Texture features are computed from the intersection (i.e., lattice) points of the grid lines within the breast, using a local window centered at each lattice point. Using this strategy, a range of statistical (gray-level histogram, co-occurrence, and run-length) and structural (edge-enhancing, local binary pattern, and fractal dimension) features are extracted. To cover the entire breast, the size of the local window for feature extraction is set equal to the lattice grid spacing and optimized experimentally by evaluating different windows sizes. The association between their lattice-based texture features and breast cancer was evaluated using logistic regression with leave-one-out cross validation and further compared to that of breast PD% and commonly used single-ROI texture features extracted from the retroareolar or the central breast region. Classification performance was evaluated using the area under the curve (AUC) of the receiver operating characteristic (ROC). DeLong's test was used to compare the different ROCs in terms of AUC performance. The average univariate performance of the lattice-based features is higher when extracted from smaller than larger window sizes. While not every individual texture feature is superior to breast PD% (AUC: 0.59, STD: 0.03), their combination in multivariate analysis has significantly better performance (AUC: 0.85, STD: 0.02, p < 0.001). The lattice-based texture features also outperform the single-ROI texture features when extracted from the retroareolar or the central breast region (AUC: 0.60-0.74, STD: 0.03). Adding breast PD% does not make a significant performance improvement to the lattice-based texture features or the single-ROI features (p > 0.05). The proposed lattice-based strategy for mammographic texture analysis enables to characterize the parenchymal pattern over the entire breast. As such, these features provide richer information compared to currently used descriptors and may ultimately improve breast cancer risk assessment. Larger studies are warranted to validate these findings and also compare to standard demographic and reproductive risk factors.

On soil textural classifications and soil-texture-based estimations

NASA Astrophysics Data System (ADS)

Ángel Martín, Miguel; Pachepsky, Yakov A.; García-Gutiérrez, Carlos; Reyes, Miguel

2018-02-01

The soil texture representation with the standard textural fraction triplet sand-silt-clay is commonly used to estimate soil properties. The objective of this work was to test the hypothesis that other fraction sizes in the triplets may provide a better representation of soil texture for estimating some soil parameters. We estimated the cumulative particle size distribution and bulk density from an entropy-based representation of the textural triplet with experimental data for 6240 soil samples. The results supported the hypothesis. For example, simulated distributions were not significantly different from the original ones in 25 and 85 % of cases when the sand-silt-clay and very coarse+coarse + medium sand - fine + very fine sand - silt+clay were used, respectively. When the same standard and modified triplets were used to estimate the average bulk density, the coefficients of determination were 0.001 and 0.967, respectively. Overall, the textural triplet selection appears to be application and data specific.

Development of Thin-Walled Magnesium Alloy Extrusions for Improved Crash Performance Based Upon Texture Control

NASA Astrophysics Data System (ADS)

Williams, Bruce W.; Agnew, Sean R.; Klein, Robert W.; McKinley, Jonathan

Recent investigations suggest that it is possible to achieve dramatic modifications to both strength and ductility of magnesium alloys through a combination of alloying, grain refinement, and texture control. The current work explores the possibility of altering the texture in extruded thin-walled magnesium alloy tubes for improved ductility during axial crush in which energy is absorbed through progressive buckling. The texture evolution was predicted using the viscoplastic self-consistent (VPSC) crystal plasticity model, with strain path input from continuum-based finite element simulations of extrusion. A limited diversity of textures can be induced by altering the strain path through the extrusion die design. In some cases, such as for simple bar extrusion, the textures predicted can be connected with simple shape change. In other cases, a subtle influence of strain path involving shear-reverse-shear is predicted. The most promising textures predicted for a variety of strain paths are selected for subsequent experimental study.

Prediction of troponin-T degradation using color image texture features in 10d aged beef longissimus steaks.

PubMed

Sun, X; Chen, K J; Berg, E P; Newman, D J; Schwartz, C A; Keller, W L; Maddock Carlin, K R

2014-02-01

The objective was to use digital color image texture features to predict troponin-T degradation in beef. Image texture features, including 88 gray level co-occurrence texture features, 81 two-dimension fast Fourier transformation texture features, and 48 Gabor wavelet filter texture features, were extracted from color images of beef strip steaks (longissimus dorsi, n = 102) aged for 10d obtained using a digital camera and additional lighting. Steaks were designated degraded or not-degraded based on troponin-T degradation determined on d 3 and d 10 postmortem by immunoblotting. Statistical analysis (STEPWISE regression model) and artificial neural network (support vector machine model, SVM) methods were designed to classify protein degradation. The d 3 and d 10 STEPWISE models were 94% and 86% accurate, respectively, while the d 3 and d 10 SVM models were 63% and 71%, respectively, in predicting protein degradation in aged meat. STEPWISE and SVM models based on image texture features show potential to predict troponin-T degradation in meat. © 2013.

Texture-Based Correspondence Display

NASA Technical Reports Server (NTRS)

Gerald-Yamasaki, Michael

2004-01-01

Texture-based correspondence display is a methodology to display corresponding data elements in visual representations of complex multidimensional, multivariate data. Texture is utilized as a persistent medium to contain a visual representation model and as a means to create multiple renditions of data where color is used to identify correspondence. Corresponding data elements are displayed over a variety of visual metaphors in a normal rendering process without adding extraneous linking metadata creation and maintenance. The effectiveness of visual representation for understanding data is extended to the expression of the visual representation model in texture.

Analyzing and improving surface texture by dual-rotation magnetorheological finishing

NASA Astrophysics Data System (ADS)

Wang, Yuyue; Zhang, Yun; Feng, Zhijing

2016-01-01

The main advantages of magnetorheological finishing (MRF) are its high convergence rate of surface error, the ability of polishing aspheric surfaces and nearly no subsurface damage. However, common MRF produces directional surface texture due to the constant flow direction of the magnetorheological (MR) polishing fluid. This paper studies the mechanism of surface texture formation by texture modeling. Dual-rotation magnetorheological finishing (DRMRF) is presented to suppress directional surface texture after analyzing the results of the texture model for common MRF. The results of the surface texture model for DRMRF and the proposed quantitative method based on mathematical statistics indicate the effective suppression of directional surface texture. An experimental setup is developed and experiments show directional surface texture and no directional surface texture in common MRF and DRMRF, respectively. As a result, the surface roughness of DRMRF is 0.578 nm (root-mean-square value) which is lower than 1.109 nm in common MRF.

Hybrid texture generator

NASA Astrophysics Data System (ADS)

Miyata, Kazunori; Nakajima, Masayuki

1995-04-01

A method is given for synthesizing a texture by using the interface of a conventional drawing tool. The majority of conventional texture generation methods are based on the procedural approach, and can generate a variety of textures that are adequate for generating a realistic image. But it is hard for a user to imagine what kind of texture will be generated simply by looking at its parameters. Furthermore, it is difficult to design a new texture freely without a knowledge of all the procedures for texture generation. Our method offers a solution to these problems, and has the following four merits: First, a variety of textures can be obtained by combining a set of feature lines and attribute functions. Second, data definitions are flexible. Third, the user can preview a texture together with its feature lines. Fourth, people can design their own textures interactively and freely by using the interface of a conventional drawing tool. For users who want to build this texture generation method into their own programs, we also give the language specifications for generating a texture. This method can interactively provide a variety of textures, and can also be used for typographic design.

Accuracy in breast shape alignment with 3D surface fitting algorithms.

PubMed

Riboldi, Marco; Gierga, David P; Chen, George T Y; Baroni, Guido

2009-04-01

Surface imaging is in use in radiotherapy clinical practice for patient setup optimization and monitoring. Breast alignment is accomplished by searching for a tentative spatial correspondence between the reference and daily surface shape models. In this study, the authors quantify whole breast shape alignment by relying on texture features digitized on 3D surface models. Texture feature localization was validated through repeated measurements in a silicone breast phantom, mounted on a high precision mechanical stage. Clinical investigations on breast shape alignment included 133 fractions in 18 patients treated with accelerated partial breast irradiation. The breast shape was detected with a 3D video based surface imaging system so that breathing was compensated. An in-house algorithm for breast alignment, based on surface fitting constrained by nipple matching (constrained surface fitting), was applied. Results were compared with a commercial software where no constraints are utilized (unconstrained surface fitting). Texture feature localization was validated within 2 mm in each anatomical direction. Clinical data show that unconstrained surface fitting achieves adequate accuracy in most cases, though nipple mismatch is considerably higher than residual surface distances (3.9 mm vs 0.6 mm on average). Outliers beyond 1 cm can be experienced as the result of a degenerate surface fit, where unconstrained surface fitting is not sufficient to establish spatial correspondence. In the constrained surface fitting algorithm, average surface mismatch within 1 mm was obtained when nipple position was forced to match in the [1.5; 5] mm range. In conclusion, optimal results can be obtained by trading off the desired overall surface congruence vs matching of selected landmarks (constraint). Constrained surface fitting is put forward to represent an improvement in setup accuracy for those applications where whole breast positional reproducibility is an issue.

An approach to accidents modeling based on compounds road environments.

PubMed

Fernandes, Ana; Neves, Jose

2013-04-01

The most common approach to study the influence of certain road features on accidents has been the consideration of uniform road segments characterized by a unique feature. However, when an accident is related to the road infrastructure, its cause is usually not a single characteristic but rather a complex combination of several characteristics. The main objective of this paper is to describe a methodology developed in order to consider the road as a complete environment by using compound road environments, overcoming the limitations inherented in considering only uniform road segments. The methodology consists of: dividing a sample of roads into segments; grouping them into quite homogeneous road environments using cluster analysis; and identifying the influence of skid resistance and texture depth on road accidents in each environment by using generalized linear models. The application of this methodology is demonstrated for eight roads. Based on real data from accidents and road characteristics, three compound road environments were established where the pavement surface properties significantly influence the occurrence of accidents. Results have showed clearly that road environments where braking maneuvers are more common or those with small radii of curvature and high speeds require higher skid resistance and texture depth as an important contribution to the accident prevention. Copyright © 2013 Elsevier Ltd. All rights reserved.

Adhesive behavior of micro/nano-textured surfaces

NASA Astrophysics Data System (ADS)

Zhang, Yuyan; Wang, Xiaoli; Li, Hanqing; Wang, Ben

2015-02-01

A numerical model of the adhesive contact between a rigid smooth sphere and an elastic textured surface based on the Lennard-Jones interatomic potential law and the Hamaker summation method is established. Textures are considered by introducing the texture height distribution into the gap equation. Simulation results show that the pull-off force on textured surfaces decreases compared to that on smooth surfaces. Furthermore, effects of sphere-shaped textures on reducing adhesion are more obvious than cylinder-shaped or cube-shaped textures when the coverage area ratio, maximum height and interval of textures are fixed. For surfaces with sphere-shaped textures, variation trends of the mean pull-off force with texture density are not monotonous, and there exists a certain range of texture densities in which the mean pull-off force is small and its variation is insignificant. In addition, the pull-off force depends also on the maximum height and radius of textures. On one hand, if the texture radius is fixed, larger maximum height results in smaller pull-off force, and if the maximum height is fixed, the pull-off force tends to increase almost linearly with increases in texture radius. On the other hand, if the height-diameter ratio of textures is fixed, the pull-off force reaches a minimum at an optimum texture radius or maximum height.

Multi Texture Analysis of Colorectal Cancer Continuum Using Multispectral Imagery

PubMed Central

Chaddad, Ahmad; Desrosiers, Christian; Bouridane, Ahmed; Toews, Matthew; Hassan, Lama; Tanougast, Camel

2016-01-01

Purpose This paper proposes to characterize the continuum of colorectal cancer (CRC) using multiple texture features extracted from multispectral optical microscopy images. Three types of pathological tissues (PT) are considered: benign hyperplasia, intraepithelial neoplasia and carcinoma. Materials and Methods In the proposed approach, the region of interest containing PT is first extracted from multispectral images using active contour segmentation. This region is then encoded using texture features based on the Laplacian-of-Gaussian (LoG) filter, discrete wavelets (DW) and gray level co-occurrence matrices (GLCM). To assess the significance of textural differences between PT types, a statistical analysis based on the Kruskal-Wallis test is performed. The usefulness of texture features is then evaluated quantitatively in terms of their ability to predict PT types using various classifier models. Results Preliminary results show significant texture differences between PT types, for all texture features (p-value < 0.01). Individually, GLCM texture features outperform LoG and DW features in terms of PT type prediction. However, a higher performance can be achieved by combining all texture features, resulting in a mean classification accuracy of 98.92%, sensitivity of 98.12%, and specificity of 99.67%. Conclusions These results demonstrate the efficiency and effectiveness of combining multiple texture features for characterizing the continuum of CRC and discriminating between pathological tissues in multispectral images. PMID:26901134

Surface Texture-Based Surface Treatments on Ti6Al4V Titanium Alloys for Tribological and Biological Applications: A Mini Review

PubMed Central

Li, Dali; Zou, Jiaojuan; Xie, Ruizhen; Wang, Zhihua; Tang, Bin

2018-01-01

Surface texture (ST) has been confirmed as an effective and economical surface treatment technique that can be applied to a great range of materials and presents growing interests in various engineering fields. Ti6Al4V which is the most frequently and successfully used titanium alloy has long been restricted in tribological-related operations due to the shortcomings of low surface hardness, high friction coefficient, and poor abrasive wear resistance. Ti6Al4V has benefited from surface texture-based surface treatments over the last decade. This review begins with a brief introduction, analysis approaches, and processing methods of surface texture. The specific applications of the surface texture-based surface treatments for improving surface performance of Ti6Al4V are thoroughly reviewed from the point of view of tribology and biology. PMID:29587358

Texture analysis of ultrahigh field T2*-weighted MR images of the brain: application to Huntington's disease.

PubMed

Doan, Nhat Trung; van den Bogaard, Simon J A; Dumas, Eve M; Webb, Andrew G; van Buchem, Mark A; Roos, Raymund A C; van der Grond, Jeroen; Reiber, Johan H C; Milles, Julien

2014-03-01

To develop a framework for quantitative detection of between-group textural differences in ultrahigh field T2*-weighted MR images of the brain. MR images were acquired using a three-dimensional (3D) T2*-weighted gradient echo sequence on a 7 Tesla MRI system. The phase images were high-pass filtered to remove phase wraps. Thirteen textural features were computed for both the magnitude and phase images of a region of interest based on 3D Gray-Level Co-occurrence Matrix, and subsequently evaluated to detect between-group differences using a Mann-Whitney U-test. We applied the framework to study textural differences in subcortical structures between premanifest Huntington's disease (HD), manifest HD patients, and controls. In premanifest HD, four phase-based features showed a difference in the caudate nucleus. In manifest HD, 7 magnitude-based features showed a difference in the pallidum, 6 phase-based features in the caudate nucleus, and 10 phase-based features in the putamen. After multiple comparison correction, significant differences were shown in the putamen in manifest HD by two phase-based features (both adjusted P values=0.04). This study provides the first evidence of textural heterogeneity of subcortical structures in HD. Texture analysis of ultrahigh field T2*-weighted MR images can be useful for noninvasive monitoring of neurodegenerative diseases. Copyright © 2013 Wiley Periodicals, Inc.

Against the grain: The physical properties of anisotropic partially molten rocks

NASA Astrophysics Data System (ADS)

Ghanbarzadeh, S.; Hesse, M. A.; Prodanovic, M.

2014-12-01

Partially molten rocks commonly develop textures that appear close to textural equilibrium, where the melt network evolves to minimize the energy of the melt-solid interfaces, while maintaining the dihedral angle θ at solid-solid-melt contact lines. Textural equilibrium provides a powerful model for the melt distribution that controls the petro-physical properties of partially molten rocks, e.g., permeability, elastic moduli, and electrical resistivity. We present the first level-set computations of three-dimensional texturally equilibrated melt networks in rocks with an anisotropic fabric. Our results show that anisotropy induces wetting of smaller grain boundary faces for θ > 0 at realistic porosities ϕ < 3%. This was previously not thought to be possible at textural equilibrium and reconciles the theory with experimental observations. Wetting of the grain boundary faces leads to a dramatic redistribution of the melt from the edges to the faces that introduces strong anisotropy in the petro-physical properties such as permeability, effective electrical conductivity and mechanical properties. Figure, on left, shows that smaller grain boundaries become wetted at relatively low melt fractions of 3% in stretched polyhedral grains with elongation factor 1.5. Right plot represents the ratio of melt electrical conductivity to effective conductivity of medium (known as formation factor) as an example of anisotropy in physical properties. The plot shows that even slight anisotropy in grains induces considerable anisotropy in electrical properties.

Textured Na x CoO2 Ceramics Sintered from Hydrothermal Platelet Nanocrystals: Growth Mechanism and Transport Properties

NASA Astrophysics Data System (ADS)

Zhang, Wei; Liu, Pengcheng; Wang, Yifeng; Zhu, Kongjun; Tai, Guoan; Liu, Jinsong; Wang, Jing; Yan, Kang; Zhang, Jianhui

2018-05-01

Nanostructuring is an effective approach to improve thermoelectric (TE) performance, which is caused by the interface and quantum effects on electron and phonon transport. For a typical layered structure such as sodium cobalt (NCO), a highly textured ceramic with nanostructure is beneficial for the carrier transport properties due to the strong anisotropy. In this paper, we established a textured NCO ceramic with highly oriented single crystals in nanoscale. The Na0.6CoO2 platelet crystals were prepared by a one-step hydrothermal method. The growth mechanism was revealed to involve dissolution-recrystallization and exchange reactions. NCO TE ceramics fabricated by a press-aided spark plasma sintering method showed a high degree of texturing, with the platelet crystals basically lying along the in-plane direction perpendicular to the press direction. TE properties of the textured NCO ceramics showed a strong anisotropic behavior. The in-plane electrical conductivity was considerably larger than the out-of-plane data because of fewer grain boundaries and interfaces that existed in the in-plane direction. Moreover, the in-plane Seebeck coefficient was higher because of the anisotropic electronic nature of NCO. Although the in-plane thermal conductivity was high, a prior ZT value was enabled for these NCO ceramics along this direction because of the dominant electrical transport. This finding provides a new approach to prepare highly oriented ceramics.

Description of textures by a structural analysis.

PubMed

Tomita, F; Shirai, Y; Tsuji, S

1982-02-01

A structural analysis system for describing natural textures is introduced. The analyzer automatically extracts the texture elements in an input image, measures their properties, classifies them into some distinctive classes (one ``ground'' class and some ``figure'' classes), and computes the distributions of the gray level, the shape, and the placement of the texture elements in each class. These descriptions are used for classification of texture images. An analysis-by-synthesis method for evaluating texture analyzers is also presented. We propose a synthesizer which generates a texture image based on the descriptions. By comparing the reconstructed image with the original one, we can see what information is preserved and what is lost in the descriptions.

Strong, non-magnetic, cube textured alloy substrates

DOEpatents

Goyal, Amit [Knoxville, TN

2011-02-01

A warm-rolled, annealed, polycrystalline, cube-textured, {100}<100>, FCC-based alloy substrate is characterized by a yield strength greater than 200 MPa and a biaxial texture characterized by a FWHM of less than 15.degree. in all directions.

TU-G-204-05: The Effects of CT Acquisition and Reconstruction Conditions On Computed Texture Feature Values of Lung Lesions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lo, P; Young, S; Kim, G

2015-06-15

Purpose: Texture features have been investigated as a biomarker of response and malignancy. Because these features reflect local differences in density, they may be influenced by acquisition and reconstruction parameters. The purpose of this study was to investigate the effects of radiation dose level and reconstruction method on features derived from lung lesions. Methods: With IRB approval, 33 lung tumor cases were identified from clinically indicated thoracic CT scans in which the raw projection (sinogram) data were available. Based on a previously-published technique, noise was added to the raw data to simulate reduced-dose versions of each case at 25%, 10%more » and 3% of the original dose. Original and simulated reduced dose projection data were reconstructed with conventional and two iterative-reconstruction settings, yielding 12 combinations of dose/recon conditions. One lesion from each case was contoured. At the reference condition (full dose, conventional recon), 17 lesions were randomly selected for repeat contouring (repeatability). For each lesion at each dose/recon condition, 151 texture measures were calculated. A paired differences approach was employed to compare feature variation from repeat contours at the reference condition to the variation observed in other dose/recon conditions (reproducibility). The ratio of standard deviation of the reproducibility to repeatability was used as the variation measure for each feature. Results: The mean variation (standard deviation) across dose levels and kernel was significantly different with a ratio of 2.24 (±5.85) across texture features (p=0.01). The mean variation (standard deviation) across dose levels with conventional recon was also significantly different with 2.30 (7.11) (p=0.025). The mean variation across reconstruction settings of original dose has a trend in showing difference with 1.35 (2.60) among all features (p=0.09). Conclusion: Texture features varied considerably with variations in dose and reconstruction condition. Care should be taken to standardize these conditions when using texture as a quantitative feature. This effort supported in part by a grant from the National Cancer Institute’s Quantitative Imaging Network (QIN): U01 CA181156; The UCLA Department of Radiology has a Master Research Agreement with Siemens Healthcare; Dr. McNitt-Gray has previously received research support from Siemens Healthcare.« less

Wall-based measurement features provides an improved IVUS coronary artery risk assessment when fused with plaque texture-based features during machine learning paradigm.

PubMed

Banchhor, Sumit K; Londhe, Narendra D; Araki, Tadashi; Saba, Luca; Radeva, Petia; Laird, John R; Suri, Jasjit S

2017-12-01

Planning of percutaneous interventional procedures involves a pre-screening and risk stratification of the coronary artery disease. Current screening tools use stand-alone plaque texture-based features and therefore lack the ability to stratify the risk. This IRB approved study presents a novel strategy for coronary artery disease risk stratification using an amalgamation of IVUS plaque texture-based and wall-based measurement features. Due to common genetic plaque makeup, carotid plaque burden was chosen as a gold standard for risk labels during training-phase of machine learning (ML) paradigm. Cross-validation protocol was adopted to compute the accuracy of the ML framework. A set of 59 plaque texture-based features was padded with six wall-based measurement features to show the improvement in stratification accuracy. The ML system was executed using principle component analysis-based framework for dimensionality reduction and uses support vector machine classifier for training and testing-phases. The ML system produced a stratification accuracy of 91.28%, demonstrating an improvement of 5.69% when wall-based measurement features were combined with plaque texture-based features. The fused system showed an improvement in mean sensitivity, specificity, positive predictive value, and area under the curve by: 6.39%, 4.59%, 3.31% and 5.48%, respectively when compared to the stand-alone system. While meeting the stability criteria of 5%, the ML system also showed a high average feature retaining power and mean reliability of 89.32% and 98.24%, respectively. The ML system showed an improvement in risk stratification accuracy when the wall-based measurement features were fused with the plaque texture-based features. Copyright © 2017 Elsevier Ltd. All rights reserved.

Assessment of visual landscape quality using IKONOS imagery.

PubMed

Ozkan, Ulas Yunus

2014-07-01

The assessment of visual landscape quality is of importance to the management of urban woodlands. Satellite remote sensing may be used for this purpose as a substitute for traditional survey techniques that are both labour-intensive and time-consuming. This study examines the association between the quality of the perceived visual landscape in urban woodlands and texture measures extracted from IKONOS satellite data, which features 4-m spatial resolution and four spectral bands. The study was conducted in the woodlands of Istanbul (the most important element of urban mosaic) lying along both shores of the Bosporus Strait. The visual quality assessment applied in this study is based on the perceptual approach and was performed via a survey of expressed preferences. For this purpose, representative photographs of real scenery were used to elicit observers' preferences. A slide show comprising 33 images was presented to a group of 153 volunteers (all undergraduate students), and they were asked to rate the visual quality of each on a 10-point scale (1 for very low visual quality, 10 for very high). Average visual quality scores were calculated for landscape. Texture measures were acquired using the two methods: pixel-based and object-based. Pixel-based texture measures were extracted from the first principle component (PC1) image. Object-based texture measures were extracted by using the original four bands. The association between image texture measures and perceived visual landscape quality was tested via Pearson's correlation coefficient. The analysis found a strong linear association between image texture measures and visual quality. The highest correlation coefficient was calculated between standard deviation of gray levels (SDGL) (one of the pixel-based texture measures) and visual quality (r = 0.82, P < 0.05). The results showed that perceived visual quality of urban woodland landscapes can be estimated by using texture measures extracted from satellite data in combination with appropriate modelling techniques.

Evaluation of soil processing conditions on mineralizable C and N across a textural gradient

USDA-ARS?s Scientific Manuscript database

Soil biological activity is an important component of a well-functioning soil. Methodologies for estimating this process in soil vary due to a variety of theoretical, functional, and expediency considerations. We tested the effects of soil processing (sieve size), water delivery method (from top a...

Texture segmentation by genetic programming.

PubMed

Song, Andy; Ciesielski, Vic

2008-01-01

This paper describes a texture segmentation method using genetic programming (GP), which is one of the most powerful evolutionary computation algorithms. By choosing an appropriate representation texture, classifiers can be evolved without computing texture features. Due to the absence of time-consuming feature extraction, the evolved classifiers enable the development of the proposed texture segmentation algorithm. This GP based method can achieve a segmentation speed that is significantly higher than that of conventional methods. This method does not require a human expert to manually construct models for texture feature extraction. In an analysis of the evolved classifiers, it can be seen that these GP classifiers are not arbitrary. Certain textural regularities are captured by these classifiers to discriminate different textures. GP has been shown in this study as a feasible and a powerful approach for texture classification and segmentation, which are generally considered as complex vision tasks.

The Study of Residential Areas Extraction Based on GF-3 Texture Image Segmentation

NASA Astrophysics Data System (ADS)

Shao, G.; Luo, H.; Tao, X.; Ling, Z.; Huang, Y.

2018-04-01

The study chooses the standard stripe and dual polarization SAR images of GF-3 as the basic data. Residential areas extraction processes and methods based upon GF-3 images texture segmentation are compared and analyzed. GF-3 images processes include radiometric calibration, complex data conversion, multi-look processing, images filtering, and then conducting suitability analysis for different images filtering methods, the filtering result show that the filtering method of Kuan is efficient for extracting residential areas, then, we calculated and analyzed the texture feature vectors using the GLCM (the Gary Level Co-occurrence Matrix), texture feature vectors include the moving window size, step size and angle, the result show that window size is 11*11, step is 1, and angle is 0°, which is effective and optimal for the residential areas extracting. And with the FNEA (Fractal Net Evolution Approach), we segmented the GLCM texture images, and extracted the residential areas by threshold setting. The result of residential areas extraction verified and assessed by confusion matrix. Overall accuracy is 0.897, kappa is 0.881, and then we extracted the residential areas by SVM classification based on GF-3 images, the overall accuracy is less 0.09 than the accuracy of extraction method based on GF-3 Texture Image Segmentation. We reached the conclusion that residential areas extraction based on GF-3 SAR texture image multi-scale segmentation is simple and highly accurate. although, it is difficult to obtain multi-spectrum remote sensing image in southern China, in cloudy and rainy weather throughout the year, this paper has certain reference significance.

Transfer of the nationwide Czech soil survey data to a foreign soil classification - generating input parameters for a process-based soil erosion modelling approach

NASA Astrophysics Data System (ADS)

Beitlerová, Hana; Hieke, Falk; Žížala, Daniel; Kapička, Jiří; Keiser, Andreas; Schmidt, Jürgen; Schindewolf, Marcus

2017-04-01

Process-based erosion modelling is a developing and adequate tool to assess, simulate and understand the complex mechanisms of soil loss due to surface runoff. While the current state of available models includes powerful approaches, a major drawback is given by complex parametrization. A major input parameter for the physically based soil loss and deposition model EROSION 3D is represented by soil texture. However, as the model has been developed in Germany it is dependent on the German soil classification. To exploit data generated during a massive nationwide soil survey campaign taking place in the 1960s across the entire Czech Republic, a transfer from the Czech to the German or at least international (e.g. WRB) system is mandatory. During the survey the internal differentiation of grain sizes was realized in a two fractions approach, separating texture into solely above and below 0.01 mm rather than into clayey, silty and sandy textures. Consequently, the Czech system applies a classification of seven different textures based on the respective percentage of large and small particles, while in Germany 31 groups are essential. The followed approach of matching Czech soil survey data to the German system focusses on semi-logarithmic interpolation of the cumulative soil texture curve additionally on a regression equation based on a recent database of 128 soil pits. Furthermore, for each of the seven Czech texture classes a group of typically suitable classes of the German system was derived. A GIS-based spatial analysis to test approaches of interpolation the soil texture was carried out. First results show promising matches and pave the way to a Czech model application of EROSION 3D.

SU-F-R-36: Validating Quantitative Radiomic Texture Features for Oncologic PET: A Digital Phantom Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, F; Yang, Y; Young, L

Purpose: Radiomic texture features derived from the oncologic PET have recently been brought under intense investigation within the context of patient stratification and treatment outcome prediction in a variety of cancer types; however, their validity has not yet been examined. This work is aimed to validate radiomic PET texture metrics through the use of realistic simulations in the ground truth setting. Methods: Simulation of FDG-PET was conducted by applying the Zubal phantom as an attenuation map to the SimSET software package that employs Monte Carlo techniques to model the physical process of emission imaging. A total of 15 irregularly-shaped lesionsmore » featuring heterogeneous activity distribution were simulated. For each simulated lesion, 28 texture features in relation to the intensity histograms (GLIH), grey-level co-occurrence matrices (GLCOM), neighborhood difference matrices (GLNDM), and zone size matrices (GLZSM) were evaluated and compared with their respective values extracted from the ground truth activity map. Results: In reference to the values from the ground truth images, texture parameters appearing on the simulated data varied with a range of 0.73–3026.2% for GLIH-based, 0.02–100.1% for GLCOM-based, 1.11–173.8% for GLNDM-based, and 0.35–66.3% for GLZSM-based. For majority of the examined texture metrics (16/28), their values on the simulated data differed significantly from those from the ground truth images (P-value ranges from <0.0001 to 0.04). Features not exhibiting significant difference comprised of GLIH-based standard deviation, GLCO-based energy and entropy, GLND-based coarseness and contrast, and GLZS-based low gray-level zone emphasis, high gray-level zone emphasis, short zone low gray-level emphasis, long zone low gray-level emphasis, long zone high gray-level emphasis, and zone size nonuniformity. Conclusion: The extent to which PET imaging disturbs texture appearance is feature-dependent and could be substantial. It is thus advised that use of PET texture parameters for predictive and prognostic measurements in oncologic setting awaits further systematic and critical evaluation.« less

Clustering document fragments using background color and texture information

NASA Astrophysics Data System (ADS)

Chanda, Sukalpa; Franke, Katrin; Pal, Umapada

2012-01-01

Forensic analysis of questioned documents sometimes can be extensively data intensive. A forensic expert might need to analyze a heap of document fragments and in such cases to ensure reliability he/she should focus only on relevant evidences hidden in those document fragments. Relevant document retrieval needs finding of similar document fragments. One notion of obtaining such similar documents could be by using document fragment's physical characteristics like color, texture, etc. In this article we propose an automatic scheme to retrieve similar document fragments based on visual appearance of document paper and texture. Multispectral color characteristics using biologically inspired color differentiation techniques are implemented here. This is done by projecting document color characteristics to Lab color space. Gabor filter-based texture analysis is used to identify document texture. It is desired that document fragments from same source will have similar color and texture. For clustering similar document fragments of our test dataset we use a Self Organizing Map (SOM) of dimension 5×5, where the document color and texture information are used as features. We obtained an encouraging accuracy of 97.17% from 1063 test images.

A research of selected textural features for detection of asbestos-cement roofing sheets using orthoimages

NASA Astrophysics Data System (ADS)

Książek, Judyta

2015-10-01

At present, there has been a great interest in the development of texture based image classification methods in many different areas. This study presents the results of research carried out to assess the usefulness of selected textural features for detection of asbestos-cement roofs in orthophotomap classification. Two different orthophotomaps of southern Poland (with ground resolution: 5 cm and 25 cm) were used. On both orthoimages representative samples for two classes: asbestos-cement roofing sheets and other roofing materials were selected. Estimation of texture analysis usefulness was conducted using machine learning methods based on decision trees (C5.0 algorithm). For this purpose, various sets of texture parameters were calculated in MaZda software. During the calculation of decision trees different numbers of texture parameters groups were considered. In order to obtain the best settings for decision trees models cross-validation was performed. Decision trees models with the lowest mean classification error were selected. The accuracy of the classification was held based on validation data sets, which were not used for the classification learning. For 5 cm ground resolution samples, the lowest mean classification error was 15.6%. The lowest mean classification error in the case of 25 cm ground resolution was 20.0%. The obtained results confirm potential usefulness of the texture parameter image processing for detection of asbestos-cement roofing sheets. In order to improve the accuracy another extended study should be considered in which additional textural features as well as spectral characteristics should be analyzed.

Texture analysis based on the Hermite transform for image classification and segmentation

NASA Astrophysics Data System (ADS)

Estudillo-Romero, Alfonso; Escalante-Ramirez, Boris; Savage-Carmona, Jesus

2012-06-01

Texture analysis has become an important task in image processing because it is used as a preprocessing stage in different research areas including medical image analysis, industrial inspection, segmentation of remote sensed imaginary, multimedia indexing and retrieval. In order to extract visual texture features a texture image analysis technique is presented based on the Hermite transform. Psychovisual evidence suggests that the Gaussian derivatives fit the receptive field profiles of mammalian visual systems. The Hermite transform describes locally basic texture features in terms of Gaussian derivatives. Multiresolution combined with several analysis orders provides detection of patterns that characterizes every texture class. The analysis of the local maximum energy direction and steering of the transformation coefficients increase the method robustness against the texture orientation. This method presents an advantage over classical filter bank design because in the latter a fixed number of orientations for the analysis has to be selected. During the training stage, a subset of the Hermite analysis filters is chosen in order to improve the inter-class separability, reduce dimensionality of the feature vectors and computational cost during the classification stage. We exhaustively evaluated the correct classification rate of real randomly selected training and testing texture subsets using several kinds of common used texture features. A comparison between different distance measurements is also presented. Results of the unsupervised real texture segmentation using this approach and comparison with previous approaches showed the benefits of our proposal.

Texture classification using autoregressive filtering

NASA Technical Reports Server (NTRS)

Lawton, W. M.; Lee, M.

1984-01-01

A general theory of image texture models is proposed and its applicability to the problem of scene segmentation using texture classification is discussed. An algorithm, based on half-plane autoregressive filtering, which optimally utilizes second order statistics to discriminate between texture classes represented by arbitrary wide sense stationary random fields is described. Empirical results of applying this algorithm to natural and sysnthesized scenes are presented and future research is outlined.

Structures having enhanced biaxial texture

DOEpatents

Goyal, Amit; Budai, John D.; Kroeger, Donald M.; Norton, David P.; Specht, Eliot D.; Christen, David K.

1999-01-01

A biaxially textured alloy article includes a rolled and annealed biaxially textured base metal substrate characterized by an x-ray diffraction phi scan peak of no more than 20.degree. FWHM; and a biaxially textured layer of an alloy or another material on a surface thereof. The article further includes at least one of an electromagnetic device or an electro-optical device epitaxially joined to the alloy.

Rock classification based on resistivity patterns in electrical borehole wall images

NASA Astrophysics Data System (ADS)

Linek, Margarete; Jungmann, Matthias; Berlage, Thomas; Pechnig, Renate; Clauser, Christoph

2007-06-01

Electrical borehole wall images represent grey-level-coded micro-resistivity measurements at the borehole wall. Different scientific methods have been implemented to transform image data into quantitative log curves. We introduce a pattern recognition technique applying texture analysis, which uses second-order statistics based on studying the occurrence of pixel pairs. We calculate so-called Haralick texture features such as contrast, energy, entropy and homogeneity. The supervised classification method is used for assigning characteristic texture features to different rock classes and assessing the discriminative power of these image features. We use classifiers obtained from training intervals to characterize the entire image data set recovered in ODP hole 1203A. This yields a synthetic lithology profile based on computed texture data. We show that Haralick features accurately classify 89.9% of the training intervals. We obtained misclassification for vesicular basaltic rocks. Hence, further image analysis tools are used to improve the classification reliability. We decompose the 2D image signal by the application of wavelet transformation in order to enhance image objects horizontally, diagonally and vertically. The resulting filtered images are used for further texture analysis. This combined classification based on Haralick features and wavelet transformation improved our classification up to a level of 98%. The application of wavelet transformation increases the consistency between standard logging profiles and texture-derived lithology. Texture analysis of borehole wall images offers the potential to facilitate objective analysis of multiple boreholes with the same lithology.

Electromagnetic Spectrum Analysis and Its Influence on the Photoelectric Conversion Efficiency of Solar Cells.

PubMed

Hu, Kexiang; Ding, Enjie; Wangyang, Peihua; Wang, Qingkang

2016-06-01

The electromagnetic spectrum and the photoelectric conversion efficiency of the silicon hexagonal nanoconical hole (SiHNH) arrays based solar cells is systematically analyzed according to Rigorous Coupled Wave Analysis (RCWA) and Modal Transmission Line (MTL) theory. An ultimate efficiency of the optimized SiHNH arrays based solar cell is up to 31.92% in consideration of the absorption spectrum, 4.52% higher than that of silicon hexagonal nanoconical frustum (SiHNF) arrays. The absorption enhancement of the SiHNH arrays is due to its lower reflectance and more supported guided-mode resonances, and the enhanced ultimate efficiency is insensitive to bottom diameter (D(bot)) of nanoconical hole and the incident angle. The result provides an additional guideline for the nanostructure surface texturing fabrication design for photovoltaic applications.

An extensive analysis of various texture feature extractors to detect Diabetes Mellitus using facial specific regions.

PubMed

Shu, Ting; Zhang, Bob; Yan Tang, Yuan

2017-04-01

Researchers have recently discovered that Diabetes Mellitus can be detected through non-invasive computerized method. However, the focus has been on facial block color features. In this paper, we extensively study the effects of texture features extracted from facial specific regions at detecting Diabetes Mellitus using eight texture extractors. The eight methods are from four texture feature families: (1) statistical texture feature family: Image Gray-scale Histogram, Gray-level Co-occurance Matrix, and Local Binary Pattern, (2) structural texture feature family: Voronoi Tessellation, (3) signal processing based texture feature family: Gaussian, Steerable, and Gabor filters, and (4) model based texture feature family: Markov Random Field. In order to determine the most appropriate extractor with optimal parameter(s), various parameter(s) of each extractor are experimented. For each extractor, the same dataset (284 Diabetes Mellitus and 231 Healthy samples), classifiers (k-Nearest Neighbors and Support Vector Machines), and validation method (10-fold cross validation) are used. According to the experiments, the first and third families achieved a better outcome at detecting Diabetes Mellitus than the other two. The best texture feature extractor for Diabetes Mellitus detection is the Image Gray-scale Histogram with bin number=256, obtaining an accuracy of 99.02%, a sensitivity of 99.64%, and a specificity of 98.26% by using SVM. Copyright © 2017 Elsevier Ltd. All rights reserved.

Muscle Protein Profiles Used for Prediction of Texture of Farmed Salmon (Salmo salar L.).

PubMed

Ørnholt-Johansson, Gine; Frosch, Stina; Gudjónsdóttir, María; Wulff, Tune; Jessen, Flemming

2017-04-26

A soft texture is undesired in Atlantic salmon as it leads to downgrading and reduced yield, yet it is a factor for which the cause is not fully understood. This lack of understanding highlights the need for identifying the cause of the soft texture and developing solutions by which the processing industry can improve the yield. Changes in muscle protein profiles can occur both pre- and postharvest and constitute an overall characterization of the muscle properties including texture. The aim of this study was to investigate this relationship between specific muscle proteins and the texture of the salmon fillet. Samples for 2D-gel-based proteomics were taken from the fillet above the lateral line at the same position as where the texture had been measured. The resulting protein profiles were analyzed using multivariate data analysis. Sixteen proteins were found to correlate to the measured texture, showing that it is possible to predict peak force based on a small subset of proteins. Additionally, eight of the 16 proteins were identified by tandem mass spectrometry including serum albumin, dipeptidyl peptidase 3, heat shock protein 70, annexins, and a protein presumed to be a titin fragment. It is contemplated that the identification of these proteins and their significance for the measured texture will contribute to further understanding of the Atlantic salmon muscle texture.

Hydrologic-Process-Based Soil Texture Classifications for Improved Visualization of Landscape Function

PubMed Central

Groenendyk, Derek G.; Ferré, Ty P.A.; Thorp, Kelly R.; Rice, Amy K.

2015-01-01

Soils lie at the interface between the atmosphere and the subsurface and are a key component that control ecosystem services, food production, and many other processes at the Earth’s surface. There is a long-established convention for identifying and mapping soils by texture. These readily available, georeferenced soil maps and databases are used widely in environmental sciences. Here, we show that these traditional soil classifications can be inappropriate, contributing to bias and uncertainty in applications from slope stability to water resource management. We suggest a new approach to soil classification, with a detailed example from the science of hydrology. Hydrologic simulations based on common meteorological conditions were performed using HYDRUS-1D, spanning textures identified by the United States Department of Agriculture soil texture triangle. We consider these common conditions to be: drainage from saturation, infiltration onto a drained soil, and combined infiltration and drainage events. Using a k-means clustering algorithm, we created soil classifications based on the modeled hydrologic responses of these soils. The hydrologic-process-based classifications were compared to those based on soil texture and a single hydraulic property, Ks. Differences in classifications based on hydrologic response versus soil texture demonstrate that traditional soil texture classification is a poor predictor of hydrologic response. We then developed a QGIS plugin to construct soil maps combining a classification with georeferenced soil data from the Natural Resource Conservation Service. The spatial patterns of hydrologic response were more immediately informative, much simpler, and less ambiguous, for use in applications ranging from trafficability to irrigation management to flood control. The ease with which hydrologic-process-based classifications can be made, along with the improved quantitative predictions of soil responses and visualization of landscape function, suggest that hydrologic-process-based classifications should be incorporated into environmental process models and can be used to define application-specific maps of hydrologic function. PMID:26121466

Hydrologic-Process-Based Soil Texture Classifications for Improved Visualization of Landscape Function.

PubMed

Groenendyk, Derek G; Ferré, Ty P A; Thorp, Kelly R; Rice, Amy K

2015-01-01

Soils lie at the interface between the atmosphere and the subsurface and are a key component that control ecosystem services, food production, and many other processes at the Earth's surface. There is a long-established convention for identifying and mapping soils by texture. These readily available, georeferenced soil maps and databases are used widely in environmental sciences. Here, we show that these traditional soil classifications can be inappropriate, contributing to bias and uncertainty in applications from slope stability to water resource management. We suggest a new approach to soil classification, with a detailed example from the science of hydrology. Hydrologic simulations based on common meteorological conditions were performed using HYDRUS-1D, spanning textures identified by the United States Department of Agriculture soil texture triangle. We consider these common conditions to be: drainage from saturation, infiltration onto a drained soil, and combined infiltration and drainage events. Using a k-means clustering algorithm, we created soil classifications based on the modeled hydrologic responses of these soils. The hydrologic-process-based classifications were compared to those based on soil texture and a single hydraulic property, Ks. Differences in classifications based on hydrologic response versus soil texture demonstrate that traditional soil texture classification is a poor predictor of hydrologic response. We then developed a QGIS plugin to construct soil maps combining a classification with georeferenced soil data from the Natural Resource Conservation Service. The spatial patterns of hydrologic response were more immediately informative, much simpler, and less ambiguous, for use in applications ranging from trafficability to irrigation management to flood control. The ease with which hydrologic-process-based classifications can be made, along with the improved quantitative predictions of soil responses and visualization of landscape function, suggest that hydrologic-process-based classifications should be incorporated into environmental process models and can be used to define application-specific maps of hydrologic function.

Evolution of porous structure and texture in nanoporous SiO2/Al2O3 materials during calcination

NASA Astrophysics Data System (ADS)

Glazkova, Elena A.; Bakina, Olga V.

2016-11-01

The study focuses on the evolution of porous structure and texture of silica/alumina xerogels during calcination in the temperature range from 500 to 1200°C. The xerogel was prepared via sol-gel method using subcritical drying. The silica/alumina xerogels were examined using transmission electron microscopy-energy dispersive spectroscopy (TEM-EDS), Brunauer Emmett Teller-Barrett Joyner Halenda (BET-BJH), differential scanning calorimetry (DSC), and Fourier transform infrared (FTIR) spectroscopy. SiO2 primary particles of size about 10 nm are connected with each other to form a porous xerogel structure. Alumina is uniformly distributed over the xerogel volume. The changes of textural characteristics under heat treatment of samples are radical; the specific surface area and pore size attain their maximum at 500-700°C. The heat treatment of samples causes dehydroxylation of the xerogel surface, and at 1200°C the sample is sintered, loses mesoporosity, and its specific surface area reduces considerably down to 78 m2/g.

Effect of oxygen and hydrogen on microstructure of pyrolytic carbon deposited from thermal decomposition of methane and ethanol

NASA Astrophysics Data System (ADS)

Ren, Biyun; Zhang, Shouyang; He, LiQun; Gu, Shengyue

2018-05-01

Chemical vapor infiltration (CVI) is the most extensive industrial preparation of carbon/carbon (C/C) composites. Precursor affects the CVI process considerably. In the present study, using carbon fiber bundles as preforms, methane and ethanol as precursors, the C/C composites were densified by decomposition of various gases in CVI. The thickness and texture of deposited pyrolytic carbon (PyC) were characterized by polarized light microscopy (PLM). The microstructure of PyC was analyzed by Raman spectroscopy. The morphologies of PyC were characterized by scanning electron microscopy (SEM). The composition of PyC was detected by X-ray photoelectron spectroscopy (XPS). Adding hydrogen in methane precursor resulted in a sharp decrease in the deposition rate and texture of PyC. Mixture of methane and ethanol as the precursor improved the deposition rate and texture remarkably. Besides, O element in ethanol was not remained as a constitution of PyC, and it was removed before the formation of PyC.

SU-E-J-249: Characterization of Gynecological Tumor Heterogeneity Using Texture Analysis in the Context of An 18F-FDG PET Adaptive Protocol

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nawrocki, J; Chino, J; Craciunescu, O

Purpose: We propose a method to examine gynecological tumor heterogeneity using texture analysis in the context of an adaptive PET protocol in order to establish if texture metrics from baseline PET-CT predict tumor response better than SUV metrics alone as well as determine texture features correlating with tumor response during radiation therapy. Methods: This IRB approved protocol included 29 women with node positive gynecological cancers visible on FDG-PET treated with EBRT to the PET positive nodes. A baseline and intra-treatment PET-CT was obtained. Tumor outcome was determined based on RECIST on posttreatment PET-CT. Primary GTVs were segmented using 40% thresholdmore » and a semi-automatic gradient-based contouring tool, PET Edge (MIM Software Inc., Cleveland, OH). SUV histogram features, Metabolic Volume (MV), and Total Lesion Glycolysis (TLG) were calculated. Four 3D texture matrices describing local and regional relationships between voxel intensities in the GTV were generated: co-occurrence, run length, size zone, and neighborhood difference. From these, 39 texture features were calculated. Prognostic power of baseline features derived from gradientbased and threshold GTVs were determined using the Wilcoxon rank-sum test. Receiver Operating Characteristics and logistic regression was performed using JMP (SAS Institute Inc., Cary, NC) to find probabilities of predicting response. Changes in features during treatment were determined using the Wilcoxon signed-rank test. Results: Of the 29 patients, there were 16 complete responders, 7 partial responders, and 6 non-responders. Comparing CR/PR vs. NR for gradient-based GTVs, 7 texture values, TLG, and SUV kurtosis had a p < 0.05. Threshold GTVs yielded 4 texture features and TLG with p < 0.05. From baseline to intra-treatment, 14 texture features, SUVmean, SUVmax, MV, and TLG changed with p < 0.05. Conclusion: Texture analysis of PET imaged gynecological tumors is an effective method for early prognosis and should be used complimentary to SUV metrics, especially when using gradient based segmentation.« less

Comparison of low-contrast detectability between two CT reconstruction algorithms using voxel-based 3D printed textured phantoms.

PubMed

Solomon, Justin; Ba, Alexandre; Bochud, François; Samei, Ehsan

2016-12-01

To use novel voxel-based 3D printed textured phantoms in order to compare low-contrast detectability between two reconstruction algorithms, FBP (filtered-backprojection) and SAFIRE (sinogram affirmed iterative reconstruction) and determine what impact background texture (i.e., anatomical noise) has on estimating the dose reduction potential of SAFIRE. Liver volumes were segmented from 23 abdominal CT cases. The volumes were characterized in terms of texture features from gray-level co-occurrence and run-length matrices. Using a 3D clustered lumpy background (CLB) model, a fitting technique based on a genetic optimization algorithm was used to find CLB textures that were reflective of the liver textures, accounting for CT system factors of spatial blurring and noise. With the modeled background texture as a guide, four cylindrical phantoms (Textures A-C and uniform, 165 mm in diameter, and 30 mm height) were designed, each containing 20 low-contrast spherical signals (6 mm diameter at nominal contrast levels of ∼3.2, 5.2, 7.2, 10, and 14 HU with four repeats per signal). The phantoms were voxelized and input into a commercial multimaterial 3D printer (Object Connex 350), with custom software for voxel-based printing (using principles of digital dithering). Images of the textured phantoms and a corresponding uniform phantom were acquired at six radiation dose levels (SOMATOM Flash, Siemens Healthcare) and observer model detection performance (detectability index of a multislice channelized Hotelling observer) was estimated for each condition (5 contrasts × 6 doses × 2 reconstructions × 4 backgrounds = 240 total conditions). A multivariate generalized regression analysis was performed (linear terms, no interactions, random error term, log link function) to assess whether dose, reconstruction algorithm, signal contrast, and background type have statistically significant effects on detectability. Also, fitted curves of detectability (averaged across contrast levels) as a function of dose were constructed for each reconstruction algorithm and background texture. FBP and SAFIRE were compared for each background type to determine the improvement in detectability at a given dose, and the reduced dose at which SAFIRE had equivalent performance compared to FBP at 100% dose. Detectability increased with increasing radiation dose (P = 2.7 × 10 -59 ) and contrast level (P = 2.2 × 10 -86 ) and was higher in the uniform phantom compared to the textured phantoms (P = 6.9 × 10 -51 ). Overall, SAFIRE had higher d' compared to FBP (P = 0.02). The estimated dose reduction potential of SAFIRE was found to be 8%, 10%, 27%, and 8% for Texture-A, Texture-B, Texture-C and uniform phantoms. In all background types, detectability was higher with SAFIRE compared to FBP. However, the relative improvement observed from SAFIRE was highly dependent on the complexity of the background texture. Iterative algorithms such as SAFIRE should be assessed in the most realistic context possible.

Defect Detection in Textures through the Use of Entropy as a Means for Automatically Selecting the Wavelet Decomposition Level.

PubMed

Navarro, Pedro J; Fernández-Isla, Carlos; Alcover, Pedro María; Suardíaz, Juan

2016-07-27

This paper presents a robust method for defect detection in textures, entropy-based automatic selection of the wavelet decomposition level (EADL), based on a wavelet reconstruction scheme, for detecting defects in a wide variety of structural and statistical textures. Two main features are presented. One of the new features is an original use of the normalized absolute function value (NABS) calculated from the wavelet coefficients derived at various different decomposition levels in order to identify textures where the defect can be isolated by eliminating the texture pattern in the first decomposition level. The second is the use of Shannon's entropy, calculated over detail subimages, for automatic selection of the band for image reconstruction, which, unlike other techniques, such as those based on the co-occurrence matrix or on energy calculation, provides a lower decomposition level, thus avoiding excessive degradation of the image, allowing a more accurate defect segmentation. A metric analysis of the results of the proposed method with nine different thresholding algorithms determined that selecting the appropriate thresholding method is important to achieve optimum performance in defect detection. As a consequence, several different thresholding algorithms depending on the type of texture are proposed.

Brownian motion curve-based textural classification and its application in cancer diagnosis.

PubMed

Mookiah, Muthu Rama Krishnan; Shah, Pratik; Chakraborty, Chandan; Ray, Ajoy K

2011-06-01

To develop an automated diagnostic methodology based on textural features of the oral mucosal epithelium to discriminate normal and oral submucous fibrosis (OSF). A total of 83 normal and 29 OSF images from histopathologic sections of the oral mucosa are considered. The proposed diagnostic mechanism consists of two parts: feature extraction using Brownian motion curve (BMC) and design ofa suitable classifier. The discrimination ability of the features has been substantiated by statistical tests. An error back-propagation neural network (BPNN) is used to classify OSF vs. normal. In development of an automated oral cancer diagnostic module, BMC has played an important role in characterizing textural features of the oral images. Fisher's linear discriminant analysis yields 100% sensitivity and 85% specificity, whereas BPNN leads to 92.31% sensitivity and 100% specificity, respectively. In addition to intensity and morphology-based features, textural features are also very important, especially in histopathologic diagnosis of oral cancer. In view of this, a set of textural features are extracted using the BMC for the diagnosis of OSF. Finally, a textural classifier is designed using BPNN, which leads to a diagnostic performance with 96.43% accuracy. (Anal Quant

Automated classification of articular cartilage surfaces based on surface texture.

PubMed

Stachowiak, G P; Stachowiak, G W; Podsiadlo, P

2006-11-01

In this study the automated classification system previously developed by the authors was used to classify articular cartilage surfaces with different degrees of wear. This automated system classifies surfaces based on their texture. Plug samples of sheep cartilage (pins) were run on stainless steel discs under various conditions using a pin-on-disc tribometer. Testing conditions were specifically designed to produce different severities of cartilage damage due to wear. Environmental scanning electron microscope (SEM) (ESEM) images of cartilage surfaces, that formed a database for pattern recognition analysis, were acquired. The ESEM images of cartilage were divided into five groups (classes), each class representing different wear conditions or wear severity. Each class was first examined and assessed visually. Next, the automated classification system (pattern recognition) was applied to all classes. The results of the automated surface texture classification were compared to those based on visual assessment of surface morphology. It was shown that the texture-based automated classification system was an efficient and accurate method of distinguishing between various cartilage surfaces generated under different wear conditions. It appears that the texture-based classification method has potential to become a useful tool in medical diagnostics.

Aesthetic perception of visual textures: a holistic exploration using texture analysis, psychological experiment, and perception modeling.

PubMed

Liu, Jianli; Lughofer, Edwin; Zeng, Xianyi

2015-01-01

Modeling human aesthetic perception of visual textures is important and valuable in numerous industrial domains, such as product design, architectural design, and decoration. Based on results from a semantic differential rating experiment, we modeled the relationship between low-level basic texture features and aesthetic properties involved in human aesthetic texture perception. First, we compute basic texture features from textural images using four classical methods. These features are neutral, objective, and independent of the socio-cultural context of the visual textures. Then, we conduct a semantic differential rating experiment to collect from evaluators their aesthetic perceptions of selected textural stimuli. In semantic differential rating experiment, eights pairs of aesthetic properties are chosen, which are strongly related to the socio-cultural context of the selected textures and to human emotions. They are easily understood and connected to everyday life. We propose a hierarchical feed-forward layer model of aesthetic texture perception and assign 8 pairs of aesthetic properties to different layers. Finally, we describe the generation of multiple linear and non-linear regression models for aesthetic prediction by taking dimensionality-reduced texture features and aesthetic properties of visual textures as dependent and independent variables, respectively. Our experimental results indicate that the relationships between each layer and its neighbors in the hierarchical feed-forward layer model of aesthetic texture perception can be fitted well by linear functions, and the models thus generated can successfully bridge the gap between computational texture features and aesthetic texture properties.

Entropy-Based Adaptive Nuclear Texture Features are Independent Prognostic Markers in a Total Population of Uterine Sarcomas

PubMed Central

Nielsen, Birgitte; Hveem, Tarjei Sveinsgjerd; Kildal, Wanja; Abeler, Vera M; Kristensen, Gunnar B; Albregtsen, Fritz; Danielsen, Håvard E; Rohde, Gustavo K

2015-01-01

Nuclear texture analysis measures the spatial arrangement of the pixel gray levels in a digitized microscopic nuclear image and is a promising quantitative tool for prognosis of cancer. The aim of this study was to evaluate the prognostic value of entropy-based adaptive nuclear texture features in a total population of 354 uterine sarcomas. Isolated nuclei (monolayers) were prepared from 50 µm tissue sections and stained with Feulgen-Schiff. Local gray level entropy was measured within small windows of each nuclear image and stored in gray level entropy matrices, and two superior adaptive texture features were calculated from each matrix. The 5-year crude survival was significantly higher (P < 0.001) for patients with high texture feature values (72%) than for patients with low feature values (36%). When combining DNA ploidy classification (diploid/nondiploid) and texture (high/low feature value), the patients could be stratified into three risk groups with 5-year crude survival of 77, 57, and 34% (Hazard Ratios (HR) of 1, 2.3, and 4.1, P < 0.001). Entropy-based adaptive nuclear texture was an independent prognostic marker for crude survival in multivariate analysis including relevant clinicopathological features (HR = 2.1, P = 0.001), and should therefore be considered as a potential prognostic marker in uterine sarcomas. © The Authors. Published 2014 International Society for Advancement of Cytometry PMID:25483227

Unsupervised consensus cluster analysis of [18F]-fluoroethyl-L-tyrosine positron emission tomography identified textural features for the diagnosis of pseudoprogression in high-grade glioma.

PubMed

Kebir, Sied; Khurshid, Zain; Gaertner, Florian C; Essler, Markus; Hattingen, Elke; Fimmers, Rolf; Scheffler, Björn; Herrlinger, Ulrich; Bundschuh, Ralph A; Glas, Martin

2017-01-31

Timely detection of pseudoprogression (PSP) is crucial for the management of patients with high-grade glioma (HGG) but remains difficult. Textural features of O-(2-[18F]fluoroethyl)-L-tyrosine positron emission tomography (FET-PET) mirror tumor uptake heterogeneity; some of them may be associated with tumor progression. Fourteen patients with HGG and suspected of PSP underwent FET-PET imaging. A set of 19 conventional and textural FET-PET features were evaluated and subjected to unsupervised consensus clustering. The final diagnosis of true progression vs. PSP was based on follow-up MRI using RANO criteria. Three robust clusters have been identified based on 10 predominantly textural FET-PET features. None of the patients with PSP fell into cluster 2, which was associated with high values for textural FET-PET markers of uptake heterogeneity. Three out of 4 patients with PSP were assigned to cluster 3 that was largely associated with low values of textural FET-PET features. By comparison, tumor-to-normal brain ratio (TNRmax) at the optimal cutoff 2.1 was less predictive of PSP (negative predictive value 57% for detecting true progression, p=0.07 vs. 75% with cluster 3, p=0.04). Clustering based on textural O-(2-[18F]fluoroethyl)-L-tyrosine PET features may provide valuable information in assessing the elusive phenomenon of pseudoprogression.

Shape and texture fused recognition of flying targets

NASA Astrophysics Data System (ADS)

Kovács, Levente; Utasi, Ákos; Kovács, Andrea; Szirányi, Tamás

2011-06-01

This paper presents visual detection and recognition of flying targets (e.g. planes, missiles) based on automatically extracted shape and object texture information, for application areas like alerting, recognition and tracking. Targets are extracted based on robust background modeling and a novel contour extraction approach, and object recognition is done by comparisons to shape and texture based query results on a previously gathered real life object dataset. Application areas involve passive defense scenarios, including automatic object detection and tracking with cheap commodity hardware components (CPU, camera and GPS).

SU-E-E-16: The Application of Texture Analysis for Differentiation of Central Cancer From Atelectasis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, M; Fan, T; Duan, J

2015-06-15

Purpose: Prospectively assess the potential utility of texture analysis for differentiation of central cancer from atelectasis. Methods: 0 consecutive central lung cancer patients who were referred for CT imaging and PET-CT were enrolled. Radiotherapy doctor delineate the tumor and atelectasis according to the fusion imaging based on CT image and PET-CT image. The texture parameters (such as energy, correlation, sum average, difference average, difference entropy), were obtained respectively to quantitatively discriminate tumor and atelectasis based on gray level co-occurrence matrix (GLCM) Results: The texture analysis results showed that the parameters of correlation and sum average had an obviously statistical significance(P<0.05).more » Conclusion: the results of this study indicate that texture analysis may be useful for the differentiation of central lung cancer and atelectasis.« less

Tailoring Spin Textures in Complex Oxide Micromagnets

DOE PAGES

Lee, Michael S.; Wynn, Thomas A.; Folven, Erik; ...

2016-09-12

Engineered topological spin textures with submicron dimensions in magnetic materials have emerged in recent years as the building blocks for various spin-based memory devices. Examples of these magnetic configurations include magnetic skyrmions, vortices, and domain walls. Here in this paper, we show the ability to control and characterize the evolution of spin textures in complex oxide micromagnets as a function of temperature through the delicate balance of fundamental materials parameters, micromagnet geometries, and epitaxial strain. These results demonstrate that in order to fully describe the observed spin textures, it is necessary to account for the spatial variation of the magneticmore » parameters within the micromagnet. This study provides the framework to accurately characterize such structures, leading to efficient design of spin-based memory devices based on complex oxide thin films.« less

Decoupling of superposed textures in an electrically biased piezoceramic with a 100 preferred orientation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fancher, Chris M.; Blendell, John E.; Bowman, Keith J.

2017-02-07

A method leveraging Rietveld full-pattern texture analysis to decouple induced domain texture from a preferred grain orientation is presented in this paper. The proposed method is demonstrated by determining the induced domain texture in a polar polymorph of 100 oriented 0.91Bi 1/2Na 1/2TiO 3-0.07BaTiO 3-0.02K 0.5Na 0.5NbO 3. Domain textures determined using the present method are compared with results obtained via single peak fitting. Texture determined using single peak fitting estimated more domain alignment than that determined using the Rietveld based method. These results suggest that the combination of grain texture and phase transitions can lead to single peak fittingmore » under or over estimating domain texture. Finally, while demonstrated for a bulk piezoelectric, the proposed method can be applied to quantify domain textures in multi-component systems and thin films.« less

Shape from texture: an evaluation of visual cues

NASA Astrophysics Data System (ADS)

Mueller, Wolfgang; Hildebrand, Axel

1994-05-01

In this paper an integrated approach is presented to understand and control the influence of texture on shape perception. Following Gibson's hypotheses, which states that texture is a mathematically and psychological sufficient stimulus for surface perception, we evaluate different perceptual cues. Starting out from a perception-based texture classification introduced by Tamura et al., we build up a uniform sampled parameter space. For the synthesis of some of our textures we use the texture description language HiLDTe. To acquire the desired texture specification we take advantage of a genetic algorithm. Employing these textures we practice a number of psychological tests to evaluate the significance of the different texture features. A comprehension of the results derived from the psychological tests is done to constitute new shape analyzing techniques. Since the vanishing point seems to be an important visual cue we introduce the Hough transform. A prospective of future work within the field of visual computing is provided within the final section.

Numerosity but Not Texture-Density Discrimination Correlates with Math Ability in Children

ERIC Educational Resources Information Center

Anobile, Giovanni; Castaldi, Elisa; Turi, Marco; Tinelli, Francesca; Burr, David C.

2016-01-01

Considerable recent work suggests that mathematical abilities in children correlate with the ability to estimate numerosity. Does math correlate only with numerosity estimation, or also with other similar tasks? We measured discrimination thresholds of school-age (6- to 12.5-years-old) children in 3 tasks: numerosity of patterns of relatively…

Method of forming biaxially textured alloy substrates and devices thereon

DOEpatents

Goyal, Amit; Specht, Eliot D.; Kroeger, Donald M.; Paranthaman, Mariappan

2000-01-01

Specific alloys, in particular Ni-based alloys, that can be biaxially textured, with a well-developed, single component texture are disclosed. These alloys have a significantly reduced Curie point, which is very desirable from the point of view of superconductivity applications. The biaxially textured alloy substrates also possess greatly enhanced mechanical properties (yield strength, ultimate tensile strength) which are essential for most applications, in particular, superconductors. A method is disclosed for producing complex multicomponent alloys which have the ideal physical properties for specific applications, such as lattice parameter, degree of magnetism and mechanical strength, and which cannot be in textured form. In addition, a method for making ultra thin biaxially textured substrates with complex compositions is disclosed.

Texture evolution and mechanical behaviour of irradiated face-centred cubic metals

NASA Astrophysics Data System (ADS)

Chen, L. R.; Xiao, X. Z.; Yu, L.; Chu, H. J.; Duan, H. L.

2018-02-01

A physically based theoretical model is proposed to investigate the mechanical behaviour and crystallographic texture evolution of irradiated face-centred cubic metals. This model is capable of capturing the main features of irradiated polycrystalline materials including irradiation hardening, post-yield softening and plasticity localization. Numerical results show a good agreement with experimental data for both unirradiated and irradiated stress-strain relationships. The study of crystallographic texture reveals that the initial randomly distributed texture of unirradiated metals under tensile loading can evolve into a mixture of [111] and [100] textures. Regarding the irradiated case, crystallographic texture develops in a different way, and an extra part of [110] texture evolves into [100] and [111] textures. Thus, [100] and [111] textures become dominant more quickly compared with those of the unirradiated case for the reason that [100] and [111]-oriented crystals have higher strength, and their plastic deformation behaviours are more active than other oriented crystals. It can be concluded that irradiation-induced defects can affect both the mechanical behaviour and texture evolution of metals, both of which are closely related to irradiation hardening.

The effect of addition of selected vegetables on the microbiological, textural and flavour profile properties of yoghurts.

PubMed

Najgebauer-Lejko, Dorota; Tabaszewska, Małgorzata; Grega, Tadeusz

2015-01-01

Vegetables, apart from having high nutritional value, also contain considerable amounts of dietary fibre and other components, which may affect physico-chemical properties of fermented milks, e.g. viscosity, texture, susceptibility to syneresis, flavour profile etc. The present work was established to study the effect of selected vegetables addition on the rheological, textural, microbiological and flavour profile parameters of yoghurts. The vegetable preparations (carrot, pumpkin, broccoli and red sweet pepper) were added (10% w/w) to the processed cow's milk fermented with DVS yoghurt culture. Texture profile analysis, determination of viscosity, susceptibility to syneresis and descriptive flavour evaluation were conducted at the 1st, 7th and 14th day after production. Additionally, microbiological studies were performed for 28 days, at 7-day intervals. The highest apparent viscosity and adhesiveness were obtained for the carrot yoghurt, whereas yoghurt with pumpkin was the least susceptible to syneresis. The other texture parameters were not affected by the addition of vegetables. Broccoli and red sweet pepper flavours were dominating in the fermented milks fortified with these vegetables, whereas carrot and pumpkin flavours were less distinctive. Yoghurt supplemented with red sweet pepper got the highest sensoric acceptability. The number of starter bacteria was not influenced by the vegetable additives, except for pumpkin yoghurt, which contained lower population of lactobacilli. Among all tested vegetables, carrot additive had the greatest potential to improve yoghurt structure, whereas red sweet pepper imparted the most acceptable flavour.

Utility of texture analysis for quantifying hepatic fibrosis on proton density MRI.

PubMed

Yu, HeiShun; Buch, Karen; Li, Baojun; O'Brien, Michael; Soto, Jorge; Jara, Hernan; Anderson, Stephan W

2015-11-01

To evaluate the potential utility of texture analysis of proton density maps for quantifying hepatic fibrosis in a murine model of hepatic fibrosis. Following Institutional Animal Care and Use Committee (IACUC) approval, a dietary model of hepatic fibrosis was used and 15 ex vivo murine liver tissues were examined. All images were acquired using a 30 mm bore 11.7T magnetic resonance imaging (MRI) scanner with a multiecho spin-echo sequence. A texture analysis was employed extracting multiple texture features including histogram-based, gray-level co-occurrence matrix-based (GLCM), gray-level run-length-based features (GLRL), gray level gradient matrix (GLGM), and Laws' features. Texture features were correlated with histopathologic and digital image analysis of hepatic fibrosis. Histogram features demonstrated very weak to moderate correlations (r = -0.29 to 0.51) with hepatic fibrosis. GLCM features correlation and contrast demonstrated moderate-to-strong correlations (r = -0.71 and 0.59, respectively) with hepatic fibrosis. Moderate correlations were seen between hepatic fibrosis and the GLRL feature short run low gray-level emphasis (SRLGE) (r = -0. 51). GLGM features demonstrate very weak to weak correlations with hepatic fibrosis (r = -0.27 to 0.09). Moderate correlations were seen between hepatic fibrosis and Laws' features L6 and L7 (r = 0.58). This study demonstrates the utility of texture analysis applied to proton density MRI in a murine liver fibrosis model and validates the potential utility of texture-based features for the noninvasive, quantitative assessment of hepatic fibrosis. © 2015 Wiley Periodicals, Inc.

Evolution of Deformation and Recrystallization Textures in High-Purity Ni and the Ni-5 at. pct W Alloy

NASA Astrophysics Data System (ADS)

Bhattacharjee, Pinaki P.; Ray, Ranjit K.; Tsuji, Nobuhiro

2010-11-01

An attempt has been made to study the evolution of texture in high-purity Ni and Ni-5 at. pct W alloy prepared by the powder metallurgy route followed by heavy cold rolling ( 95 pct deformation) and recrystallization. The deformation textures of the two materials are of typical pure metal or Cu-type texture. Cube-oriented ( left\\{ {00 1} right\\}left< { 100} rightrangle ) regions are present in the deformed state as long thin bands, elongated in the rolling direction (RD). These bands are characterized by a high orientation gradient inside, which is a result of the rotation of the cube-oriented cells around the RD toward the RD-rotated cube ( left\\{ {0 1 3} right\\}left< { 100} rightrangle ). Low-temperature annealing produces a weak cube texture along with the left\\{ {0 1 3} right\\}left< { 100} rightrangle component, with the latter being much stronger in high-purity Ni than in the Ni-W alloy. At higher temperatures, the cube texture is strengthened considerably in the Ni-W alloy; however, the cube volume fraction in high-purity Ni is significantly lower because of the retention of the left\\{ {0 1 3} right\\}left< { 100} rightrangle component. The difference in the relative strengths of the cube, and the left\\{ {0 1 3} right\\}left< { 100} rightrangle components in the two materials is evident from the beginning of recrystallization in which more left\\{ {0 1 3} right\\}left< { 100} rightrangle -oriented grains than near cube grains form in high-purity Ni. The preferential nucleation of the near cube and the left\\{ {0 1 3} right\\}left< { 100} rightrangle grains in these materials seems to be a result of the high orientation gradients associated with the cube bands that offer a favorable environment for early nucleation.

Land use classification using texture information in ERTS-A MSS imagery

NASA Technical Reports Server (NTRS)

Haralick, R. M. (Principal Investigator); Shanmugam, K. S.; Bosley, R.

1973-01-01

The author has identified the following significant results. Preliminary digital analysis of ERTS-1 MSS imagery reveals that the textural features of the imagery are very useful for land use classification. A procedure for extracting the textural features of ERTS-1 imagery is presented and the results of a land use classification scheme based on the textural features are also presented. The land use classification algorithm using textural features was tested on a 5100 square mile area covered by part of an ERTS-1 MSS band 5 image over the California coastline. The image covering this area was blocked into 648 subimages of size 8.9 square miles each. Based on a color composite of the image set, a total of 7 land use categories were identified. These land use categories are: coastal forest, woodlands, annual grasslands, urban areas, large irrigated fields, small irrigated fields, and water. The automatic classifier was trained to identify the land use categories using only the textural characteristics of the subimages; 75 percent of the subimages were assigned correct identifications. Since texture and spectral features provide completely different kinds of information, a significant increase in identification accuracy will take place when both features are used together.

Computerized Liquid Crystal Phase Identification by Neural Networks Analysis of Polarizing Microscopy Textures

NASA Astrophysics Data System (ADS)

Karaszi, Zoltan; Konya, Andrew; Dragan, Feodor; Jakli, Antal; CPIP/LCI; CS Dept. of Kent State University Collaboration

Polarizing optical microscopy (POM) is traditionally the best-established method of studying liquid crystals, and using POM started already with Otto Lehman in 1890. An expert, who is familiar with the science of optics of anisotropic materials and typical textures of liquid crystals, can identify phases with relatively large confidence. However, for unambiguous identification usually other expensive and time-consuming experiments are needed. Replacement of the subjective and qualitative human eye-based liquid crystal texture analysis with quantitative computerized image analysis technique started only recently and were used to enhance the detection of smooth phase transitions, determine order parameter and birefringence of specific liquid crystal phases. We investigate if the computer can recognize and name the phase where the texture was taken. To judge the potential of reliable image recognition based on this procedure, we used 871 images of liquid crystal textures belonging to five main categories: Nematic, Smectic A, Smectic C, Cholesteric and Crystal, and used a Neural Network Clustering Technique included in the data mining software package in Java ``WEKA''. A neural network trained on a set of 827 LC textures classified the remaining 44 textures with 80% accuracy.

Adjoint-based optimization of mechanical performance in polycrystalline materials and structures through texture control

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gu, Grace; Brown, Judith Alice; Bishop, Joseph E.

The texture of a polycrystalline material refers to the preferred orientation of the grains within the material. In metallic materials, texture can significantly affect the mechanical properties such as elastic moduli, yield stress, strain hardening, and fracture toughness. Recent advances in additive manufacturing of metallic materials offer the possibility in the not too distant future of controlling the spatial variation of texture. In this work, we investigate the advantages, in terms of mechanical performance, of allowing the texture to vary spatially. We use an adjoint-based gradient optimization algorithm within a finite element solver (COMSOL) to optimize several engineering quantities ofmore » interest in a simple structure (hole in a plate) and loading (uniaxial tension) condition. As a first step to general texture optimization, we consider the idealized case of a pure fiber texture in which the homogenized properties are transversely isotropic. In this special case, the only spatially varying design variables are the three Euler angles that prescribe the orientation of the homogenized material at each point within the structure. This work paves a new way to design metallic materials for tunable mechanical properties at the microstructure level.« less

Auditory Sensory Substitution is Intuitive and Automatic with Texture Stimuli

PubMed Central

Stiles, Noelle R. B.; Shimojo, Shinsuke

2015-01-01

Millions of people are blind worldwide. Sensory substitution (SS) devices (e.g., vOICe) can assist the blind by encoding a video stream into a sound pattern, recruiting visual brain areas for auditory analysis via crossmodal interactions and plasticity. SS devices often require extensive training to attain limited functionality. In contrast to conventional attention-intensive SS training that starts with visual primitives (e.g., geometrical shapes), we argue that sensory substitution can be engaged efficiently by using stimuli (such as textures) associated with intrinsic crossmodal mappings. Crossmodal mappings link images with sounds and tactile patterns. We show that intuitive SS sounds can be matched to the correct images by naive sighted participants just as well as by intensively-trained participants. This result indicates that existing crossmodal interactions and amodal sensory cortical processing may be as important in the interpretation of patterns by SS as crossmodal plasticity (e.g., the strengthening of existing connections or the formation of new ones), especially at the earlier stages of SS usage. An SS training procedure based on crossmodal mappings could both considerably improve participant performance and shorten training times, thereby enabling SS devices to significantly expand blind capabilities. PMID:26490260

Influence of watermelon seed protein concentrates on dough handling, textural and sensory properties of cookies.

PubMed

Wani, Ali Abas; Sogi, D S; Singh, Preeti; Khatkar, B S

2015-04-01

Fruit processing wastes contain numerous by products of potential use in food & allied industry. Watermelon seeds represent a major by-product of the processing waste and contain high amount of nutritional proteins. Protein rich cereal based products are in demand due to their health promoting benefits. With this aim, wheat flour was fortified with watermelon seed protein concentrates (2.5 %, 5 %, 7.5 % and 10 % levels) to prepare cookies with desirable physical, nutritional, and textural and sensory properties. Substitution levels of 5 % and 10 % significantly (p ≤ 0.05) increased the dough stability and mixing tolerance index, however pasting properties and dough extensibility decreased considerably above 5 % substitution levels. Cookie fracture force (kg) increased significantly (p ≤ 0.05) above 5 % fortification levels. Cookie spread factor (W/T) increased from 2.5 % to 7.5 % fortification levels, further increase showed negative impact. Sensory scores of the cookies showed that protein concentrate may be added up to 7.5 % fortification levels. This study revealed that watermelon protein concentrates can be fortified with protein concentrates upto 5-7.5 % levels in cookies to improve their protein quality.

SU-F-R-20: Image Texture Features Correlate with Time to Local Failure in Lung SBRT Patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andrews, M; Abazeed, M; Woody, N

Purpose: To explore possible correlation between CT image-based texture and histogram features and time-to-local-failure in early stage non-small cell lung cancer (NSCLC) patients treated with stereotactic body radiotherapy (SBRT).Methods and Materials: From an IRB-approved lung SBRT registry for patients treated between 2009–2013 we selected 48 (20 male, 28 female) patients with local failure. Median patient age was 72.3±10.3 years. Mean time to local failure was 15 ± 7.1 months. Physician-contoured gross tumor volumes (GTV) on the planning CT images were processed and 3D gray-level co-occurrence matrix (GLCM) based texture and histogram features were calculated in Matlab. Data were exported tomore » R and a multiple linear regression model was used to examine the relationship between texture features and time-to-local-failure. Results: Multiple linear regression revealed that entropy (p=0.0233, multiple R2=0.60) from GLCM-based texture analysis and the standard deviation (p=0.0194, multiple R2=0.60) from the histogram-based features were statistically significantly correlated with the time-to-local-failure. Conclusion: Image-based texture analysis can be used to predict certain aspects of treatment outcomes of NSCLC patients treated with SBRT. We found entropy and standard deviation calculated for the GTV on the CT images displayed a statistically significant correlation with and time-to-local-failure in lung SBRT patients.« less

Independent Component Analysis of Textures

NASA Technical Reports Server (NTRS)

Manduchi, Roberto; Portilla, Javier

2000-01-01

A common method for texture representation is to use the marginal probability densities over the outputs of a set of multi-orientation, multi-scale filters as a description of the texture. We propose a technique, based on Independent Components Analysis, for choosing the set of filters that yield the most informative marginals, meaning that the product over the marginals most closely approximates the joint probability density function of the filter outputs. The algorithm is implemented using a steerable filter space. Experiments involving both texture classification and synthesis show that compared to Principal Components Analysis, ICA provides superior performance for modeling of natural and synthetic textures.

Texture feature extraction based on a uniformity estimation method for local brightness and structure in chest CT images.

PubMed

Peng, Shao-Hu; Kim, Deok-Hwan; Lee, Seok-Lyong; Lim, Myung-Kwan

2010-01-01

Texture feature is one of most important feature analysis methods in the computer-aided diagnosis (CAD) systems for disease diagnosis. In this paper, we propose a Uniformity Estimation Method (UEM) for local brightness and structure to detect the pathological change in the chest CT images. Based on the characteristics of the chest CT images, we extract texture features by proposing an extension of rotation invariant LBP (ELBP(riu4)) and the gradient orientation difference so as to represent a uniform pattern of the brightness and structure in the image. The utilization of the ELBP(riu4) and the gradient orientation difference allows us to extract rotation invariant texture features in multiple directions. Beyond this, we propose to employ the integral image technique to speed up the texture feature computation of the spatial gray level dependent method (SGLDM). Copyright © 2010 Elsevier Ltd. All rights reserved.

A numerical investigation of grain shape and crystallographic texture effects on the plastic strain localization in friction stir weld zones

NASA Astrophysics Data System (ADS)

Romanova, V.; Balokhonov, R.; Batukhtina, E.; Shakhidjanov, V.

2015-10-01

Crystal plasticity approaches were adopted to build models accounting for the microstructure and texture observed in different friction stir weld zones. To this end, a numerical investigation of crystallographic texture and grain shape effects on the plastic strain localization in a friction stir weld of an aluminum-base alloy was performed. The presence of texture was found to give rise to pronounced mesoscale plastic strain localization.

Texture- and deformability-based surface recognition by tactile image analysis.

PubMed

Khasnobish, Anwesha; Pal, Monalisa; Tibarewala, D N; Konar, Amit; Pal, Kunal

2016-08-01

Deformability and texture are two unique object characteristics which are essential for appropriate surface recognition by tactile exploration. Tactile sensation is required to be incorporated in artificial arms for rehabilitative and other human-computer interface applications to achieve efficient and human-like manoeuvring. To accomplish the same, surface recognition by tactile data analysis is one of the prerequisites. The aim of this work is to develop effective technique for identification of various surfaces based on deformability and texture by analysing tactile images which are obtained during dynamic exploration of the item by artificial arms whose gripper is fitted with tactile sensors. Tactile data have been acquired, while human beings as well as a robot hand fitted with tactile sensors explored the objects. The tactile images are pre-processed, and relevant features are extracted from the tactile images. These features are provided as input to the variants of support vector machine (SVM), linear discriminant analysis and k-nearest neighbour (kNN) for classification. Based on deformability, six household surfaces are recognized from their corresponding tactile images. Moreover, based on texture five surfaces of daily use are classified. The method adopted in the former two cases has also been applied for deformability- and texture-based recognition of four biomembranes, i.e. membranes prepared from biomaterials which can be used for various applications such as drug delivery and implants. Linear SVM performed best for recognizing surface deformability with an accuracy of 83 % in 82.60 ms, whereas kNN classifier recognizes surfaces of daily use having different textures with an accuracy of 89 % in 54.25 ms and SVM with radial basis function kernel recognizes biomembranes with an accuracy of 78 % in 53.35 ms. The classifiers are observed to generalize well on the unseen test datasets with very high performance to achieve efficient material recognition based on its deformability and texture.

Optimal frequency domain textural edge detection filter

NASA Technical Reports Server (NTRS)

Townsend, J. K.; Shanmugan, K. S.; Frost, V. S.

1985-01-01

An optimal frequency domain textural edge detection filter is developed and its performance evaluated. For the given model and filter bandwidth, the filter maximizes the amount of output image energy placed within a specified resolution interval centered on the textural edge. Filter derivation is based on relating textural edge detection to tonal edge detection via the complex low-pass equivalent representation of narrowband bandpass signals and systems. The filter is specified in terms of the prolate spheroidal wave functions translated in frequency. Performance is evaluated using the asymptotic approximation version of the filter. This evaluation demonstrates satisfactory filter performance for ideal and nonideal textures. In addition, the filter can be adjusted to detect textural edges in noisy images at the expense of edge resolution.

Method of forming biaxially textured alloy substrates and devices thereon

DOEpatents

Goyal, Amit; Specht, Eliot D.; Kroeger, Donald M.; Paranthaman, Mariappan

1999-01-01

Specific alloys, in particular Ni-based alloys, that can be biaxially textured, with a well-developed, single component texture are disclosed. These alloys have a significantly reduced Curie point, which is very desirable from the point of view of superconductivity applications. The biaxially textured alloy substrates also possess greatly enhanced mechanical properties (yield strength, ultimate tensile strength) which are essential for most applications, in particular, superconductors. A method is disclosed for producing complex multicomponent alloys which have the ideal physical properties for specific applications, such as lattice parameter, degree of magnetism and mechanical strength, and which cannot be fabricated in textured form. In addition, a method for making ultra thin biaxially textured substrates with complex compositions is disclosed.

Unsupervised consensus cluster analysis of [18F]-fluoroethyl-L-tyrosine positron emission tomography identified textural features for the diagnosis of pseudoprogression in high-grade glioma

PubMed Central

Kebir, Sied; Khurshid, Zain; Gaertner, Florian C.; Essler, Markus; Hattingen, Elke; Fimmers, Rolf; Scheffler, Björn; Herrlinger, Ulrich; Bundschuh, Ralph A.; Glas, Martin

2017-01-01

Rationale Timely detection of pseudoprogression (PSP) is crucial for the management of patients with high-grade glioma (HGG) but remains difficult. Textural features of O-(2-[18F]fluoroethyl)-L-tyrosine positron emission tomography (FET-PET) mirror tumor uptake heterogeneity; some of them may be associated with tumor progression. Methods Fourteen patients with HGG and suspected of PSP underwent FET-PET imaging. A set of 19 conventional and textural FET-PET features were evaluated and subjected to unsupervised consensus clustering. The final diagnosis of true progression vs. PSP was based on follow-up MRI using RANO criteria. Results Three robust clusters have been identified based on 10 predominantly textural FET-PET features. None of the patients with PSP fell into cluster 2, which was associated with high values for textural FET-PET markers of uptake heterogeneity. Three out of 4 patients with PSP were assigned to cluster 3 that was largely associated with low values of textural FET-PET features. By comparison, tumor-to-normal brain ratio (TNRmax) at the optimal cutoff 2.1 was less predictive of PSP (negative predictive value 57% for detecting true progression, p=0.07 vs. 75% with cluster 3, p=0.04). Principal Conclusions Clustering based on textural O-(2-[18F]fluoroethyl)-L-tyrosine PET features may provide valuable information in assessing the elusive phenomenon of pseudoprogression. PMID:28030820

Classification of cloud fields based on textural characteristics

NASA Technical Reports Server (NTRS)

Welch, R. M.; Sengupta, S. K.; Chen, D. W.

1987-01-01

The present study reexamines the applicability of texture-based features for automatic cloud classification using very high spatial resolution (57 m) Landsat multispectral scanner digital data. It is concluded that cloud classification can be accomplished using only a single visible channel.

Computer-aided mass detection in mammography: False positive reduction via gray-scale invariant ranklet texture features

DOE Office of Scientific and Technical Information (OSTI.GOV)

Masotti, Matteo; Lanconelli, Nico; Campanini, Renato

In this work, gray-scale invariant ranklet texture features are proposed for false positive reduction (FPR) in computer-aided detection (CAD) of breast masses. Two main considerations are at the basis of this proposal. First, false positive (FP) marks surviving our previous CAD system seem to be characterized by specific texture properties that can be used to discriminate them from masses. Second, our previous CAD system achieves invariance to linear/nonlinear monotonic gray-scale transformations by encoding regions of interest into ranklet images through the ranklet transform, an image transformation similar to the wavelet transform, yet dealing with pixels' ranks rather than with theirmore » gray-scale values. Therefore, the new FPR approach proposed herein defines a set of texture features which are calculated directly from the ranklet images corresponding to the regions of interest surviving our previous CAD system, hence, ranklet texture features; then, a support vector machine (SVM) classifier is used for discrimination. As a result of this approach, texture-based information is used to discriminate FP marks surviving our previous CAD system; at the same time, invariance to linear/nonlinear monotonic gray-scale transformations of the new CAD system is guaranteed, as ranklet texture features are calculated from ranklet images that have this property themselves by construction. To emphasize the gray-scale invariance of both the previous and new CAD systems, training and testing are carried out without any in-between parameters' adjustment on mammograms having different gray-scale dynamics; in particular, training is carried out on analog digitized mammograms taken from a publicly available digital database, whereas testing is performed on full-field digital mammograms taken from an in-house database. Free-response receiver operating characteristic (FROC) curve analysis of the two CAD systems demonstrates that the new approach achieves a higher reduction of FP marks when compared to the previous one. Specifically, at 60%, 65%, and 70% per-mammogram sensitivity, the new CAD system achieves 0.50, 0.68, and 0.92 FP marks per mammogram, whereas at 70%, 75%, and 80% per-case sensitivity it achieves 0.37, 0.48, and 0.71 FP marks per mammogram, respectively. Conversely, at the same sensitivities, the previous CAD system reached 0.71, 0.87, and 1.15 FP marks per mammogram, and 0.57, 0.73, and 0.92 FPs per mammogram. Also, statistical significance of the difference between the two per-mammogram and per-case FROC curves is demonstrated by the p-value<0.001 returned by jackknife FROC analysis performed on the two CAD systems.« less

A signature dissimilarity measure for trabecular bone texture in knee radiographs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Woloszynski, T.; Podsiadlo, P.; Stachowiak, G. W.

Purpose: The purpose of this study is to develop a dissimilarity measure for the classification of trabecular bone (TB) texture in knee radiographs. Problems associated with the traditional extraction and selection of texture features and with the invariance to imaging conditions such as image size, anisotropy, noise, blur, exposure, magnification, and projection angle were addressed. Methods: In the method developed, called a signature dissimilarity measure (SDM), a sum of earth mover's distances calculated for roughness and orientation signatures is used to quantify dissimilarities between textures. Scale-space theory was used to ensure scale and rotation invariance. The effects of image size,more » anisotropy, noise, and blur on the SDM developed were studied using computer generated fractal texture images. The invariance of the measure to image exposure, magnification, and projection angle was studied using x-ray images of human tibia head. For the studies, Mann-Whitney tests with significance level of 0.01 were used. A comparison study between the performances of a SDM based classification system and other two systems in the classification of Brodatz textures and the detection of knee osteoarthritis (OA) were conducted. The other systems are based on weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND-CHARM) and local binary patterns (LBP). Results: Results obtained indicate that the SDM developed is invariant to image exposure (2.5-30 mA s), magnification (x1.00-x1.35), noise associated with film graininess and quantum mottle (<25%), blur generated by a sharp film screen, and image size (>64x64 pixels). However, the measure is sensitive to changes in projection angle (>5 deg.), image anisotropy (>30 deg.), and blur generated by a regular film screen. For the classification of Brodatz textures, the SDM based system produced comparable results to the LBP system. For the detection of knee OA, the SDM based system achieved 78.8% classification accuracy and outperformed the WND-CHARM system (64.2%). Conclusions: The SDM is well suited for the classification of TB texture images in knee OA detection and may be useful for the texture classification of medical images in general.« less

Quaternion-Based Texture Analysis of Multiband Satellite Images: Application to the Estimation of Aboveground Biomass in the East Region of Cameroon.

PubMed

Djiongo Kenfack, Cedrigue Boris; Monga, Olivier; Mpong, Serge Moto; Ndoundam, René

2018-03-01

Within the last decade, several approaches using quaternion numbers to handle and model multiband images in a holistic manner were introduced. The quaternion Fourier transform can be efficiently used to model texture in multidimensional data such as color images. For practical application, multispectral satellite data appear as a primary source for measuring past trends and monitoring changes in forest carbon stocks. In this work, we propose a texture-color descriptor based on the quaternion Fourier transform to extract relevant information from multiband satellite images. We propose a new multiband image texture model extraction, called FOTO++, in order to address biomass estimation issues. The first stage consists in removing noise from the multispectral data while preserving the edges of canopies. Afterward, color texture descriptors are extracted thanks to a discrete form of the quaternion Fourier transform, and finally the support vector regression method is used to deduce biomass estimation from texture indices. Our texture features are modeled using a vector composed with the radial spectrum coming from the amplitude of the quaternion Fourier transform. We conduct several experiments in order to study the sensitivity of our model to acquisition parameters. We also assess its performance both on synthetic images and on real multispectral images of Cameroonian forest. The results show that our model is more robust to acquisition parameters than the classical Fourier Texture Ordination model (FOTO). Our scheme is also more accurate for aboveground biomass estimation. We stress that a similar methodology could be implemented using quaternion wavelets. These results highlight the potential of the quaternion-based approach to study multispectral satellite images.

Binary patterns encoded convolutional neural networks for texture recognition and remote sensing scene classification

NASA Astrophysics Data System (ADS)

Anwer, Rao Muhammad; Khan, Fahad Shahbaz; van de Weijer, Joost; Molinier, Matthieu; Laaksonen, Jorma

2018-04-01

Designing discriminative powerful texture features robust to realistic imaging conditions is a challenging computer vision problem with many applications, including material recognition and analysis of satellite or aerial imagery. In the past, most texture description approaches were based on dense orderless statistical distribution of local features. However, most recent approaches to texture recognition and remote sensing scene classification are based on Convolutional Neural Networks (CNNs). The de facto practice when learning these CNN models is to use RGB patches as input with training performed on large amounts of labeled data (ImageNet). In this paper, we show that Local Binary Patterns (LBP) encoded CNN models, codenamed TEX-Nets, trained using mapped coded images with explicit LBP based texture information provide complementary information to the standard RGB deep models. Additionally, two deep architectures, namely early and late fusion, are investigated to combine the texture and color information. To the best of our knowledge, we are the first to investigate Binary Patterns encoded CNNs and different deep network fusion architectures for texture recognition and remote sensing scene classification. We perform comprehensive experiments on four texture recognition datasets and four remote sensing scene classification benchmarks: UC-Merced with 21 scene categories, WHU-RS19 with 19 scene classes, RSSCN7 with 7 categories and the recently introduced large scale aerial image dataset (AID) with 30 aerial scene types. We demonstrate that TEX-Nets provide complementary information to standard RGB deep model of the same network architecture. Our late fusion TEX-Net architecture always improves the overall performance compared to the standard RGB network on both recognition problems. Furthermore, our final combination leads to consistent improvement over the state-of-the-art for remote sensing scene classification.

Enhancement of multimodality texture-based prediction models via optimization of PET and MR image acquisition protocols: a proof of concept

NASA Astrophysics Data System (ADS)

Vallières, Martin; Laberge, Sébastien; Diamant, André; El Naqa, Issam

2017-11-01

Texture-based radiomic models constructed from medical images have the potential to support cancer treatment management via personalized assessment of tumour aggressiveness. While the identification of stable texture features under varying imaging settings is crucial for the translation of radiomics analysis into routine clinical practice, we hypothesize in this work that a complementary optimization of image acquisition parameters prior to texture feature extraction could enhance the predictive performance of texture-based radiomic models. As a proof of concept, we evaluated the possibility of enhancing a model constructed for the early prediction of lung metastases in soft-tissue sarcomas by optimizing PET and MR image acquisition protocols via computerized simulations of image acquisitions with varying parameters. Simulated PET images from 30 STS patients were acquired by varying the extent of axial data combined per slice (‘span’). Simulated T 1-weighted and T 2-weighted MR images were acquired by varying the repetition time and echo time in a spin-echo pulse sequence, respectively. We analyzed the impact of the variations of PET and MR image acquisition parameters on individual textures, and we investigated how these variations could enhance the global response and the predictive properties of a texture-based model. Our results suggest that it is feasible to identify an optimal set of image acquisition parameters to improve prediction performance. The model constructed with textures extracted from simulated images acquired with a standard clinical set of acquisition parameters reached an average AUC of 0.84 +/- 0.01 in bootstrap testing experiments. In comparison, the model performance significantly increased using an optimal set of image acquisition parameters (p = 0.04 ), with an average AUC of 0.89 +/- 0.01 . Ultimately, specific acquisition protocols optimized to generate superior radiomics measurements for a given clinical problem could be developed and standardized via dedicated computer simulations and thereafter validated using clinical scanners.

Evaluation of the Williams-type model for barley yields in North Dakota and Minnesota

NASA Technical Reports Server (NTRS)

Barnett, T. L. (Principal Investigator)

1981-01-01

The Williams-type yield model is based on multiple regression analysis of historial time series data at CRD level pooled to regional level (groups of similar CRDs). Basic variables considered in the analysis include USDA yield, monthly mean temperature, monthly precipitation, soil texture and topographic information, and variables derived from these. Technologic trend is represented by piecewise linear and/or quadratic functions of year. Indicators of yield reliability obtained from a ten-year bootstrap test (1970-1979) demonstrate that biases are small and performance based on root mean square appears to be acceptable for the intended AgRISTARS large area applications. The model is objective, adequate, timely, simple, and not costly. It consideres scientific knowledge on a broad scale but not in detail, and does not provide a good current measure of modeled yield reliability.

Spatial patterns in oxygen and redox sensitive biogeochemistry in tropical forest soils

Treesearch

Daniel Liptzin; Whendee L. Silver

2015-01-01

Humid tropical forest soils are characterized by warm temperatures, abundant rainfall, and high rates of biological activity that vary considerably in both space and time. These conditions, together with finely textured soils typical of humid tropical forests lead to periodic low redox conditions, even in well-drained upland environments. The relationship between redox...

Relationship between trabecular texture features of CT images and an amount of bone cement volume injection in percutaneous vertebroplasty

NASA Astrophysics Data System (ADS)

Tack, Gye Rae; Choi, Hyung Guen; Shin, Kyu-Chul; Lee, Sung J.

2001-06-01

Percutaneous vertebroplasty is a surgical procedure that was introduced for the treatment of compression fracture of the vertebrae. This procedure includes puncturing vertebrae and filling with polymethylmethacrylate (PMMA). Recent studies have shown that the procedure could provide structural reinforcement for the osteoporotic vertebrae while being minimally invasive and safe with immediate pain relief. However, treatment failures due to disproportionate PMMA volume injection have been reported as one of complications in vertebroplasty. It is believed that control of PMMA volume is one of the most critical factors that can reduce the incidence of complications. In this study, appropriate amount of PMMA volume was assessed based on the imaging data of a given patient under the following hypotheses: (1) a relationship can be drawn between the volume of PMMA injection and textural features of the trabecular bone in preoperative CT images and (2) the volume of PMMA injection can be estimated based on 3D reconstruction of postoperative CT images. Gray-level run length analysis was used to determine the textural features of the trabecular bone. The width of trabecular (T-texture) and the width of intertrabecular spaces (I-texture) were calculated. The correlation between PMMA volume and textural features of patient's CT images was also examined to evaluate the appropriate PMMA amount. Results indicated that there was a strong correlation between the actual PMMA injection volume and the area of the intertrabecular space and that of trabecular bone calculated from the CT image (correlation coefficient, requals0.96 and requals-0.95, respectively). T- texture (requals-0.93) did correlate better with the actual PMMA volume more than the I-texture (requals0.57). Therefore, it was demonstrated that appropriate PMMA injection volume could be predicted based on the textural analysis for better clinical management of the osteoporotic spine.

Development of low friction snake-inspired deterministic textured surfaces

NASA Astrophysics Data System (ADS)

Cuervo, P.; López, D. A.; Cano, J. P.; Sánchez, J. C.; Rudas, S.; Estupiñán, H.; Toro, A.; Abdel-Aal, H. A.

2016-06-01

The use of surface texturization to reduce friction in sliding interfaces has proved successful in some tribological applications. However, it is still difficult to achieve robust surface texturing with controlled designer-functionalities. This is because the current existing gap between enabling texturization technologies and surface design paradigms. Surface engineering, however, is advanced in natural surface constructs especially within legless reptiles. Many intriguing features facilitate the tribology of such animals so that it is feasible to discover the essence of their surface construction. In this work, we report on the tribological behavior of a novel class of surfaces of which the spatial dimensions of the textural patterns originate from micro-scale features present within the ventral scales of pre-selected snake species. Mask lithography was used to produce implement elliptical texturizing patterns on the surface of titanium alloy (Ti6Al4V) pins. To study the tribological behavior of the texturized pins, pin-on-disc tests were carried out with the pins sliding against ultra-high molecular weight polyethylene discs with no lubrication. For comparison, two non-texturized samples were also tested under the same conditions. The results show the feasibility of the texturization technique based on the coefficient of friction of the textured surfaces to be consistently lower than that of the non-texturized samples.

Texturization of as-cut p-type monocrystalline silicon wafer using different wet chemical solutions

NASA Astrophysics Data System (ADS)

Hashmi, Galib; Hasanuzzaman, Muhammad; Basher, Mohammad Khairul; Hoq, Mahbubul; Rahman, Md. Habibur

2018-06-01

Implementing texturization process on the monocrystalline silicon substrate reduces reflection and enhances light absorption of the substrate. Thus texturization is one of the key elements to increase the efficiency of solar cell. Considering as-cut monocrystalline silicon wafer as base substrate, in this work different concentrations of Na2CO3 and NaHCO3 solution, KOH-IPA (isopropyl alcohol) solution and tetramethylammonium hydroxide solution with different time intervals have been investigated for texturization process. Furthermore, saw damage removal process was conducted with 10% NaOH solution, 20 wt% KOH-13.33 wt% IPA solution and HF/nitric/acetic acid solution. The surface morphology of saw damage, saw damage removed surface and textured wafer were observed using optical microscope and field emission scanning electron microscopy. Texturization causes pyramidal micro structures on the surface of (100) oriented monocrystalline silicon wafer. The height of the pyramid on the silicon surface varies from 1.5 to 3.2 µm and the inclined planes of the pyramids are acute angle. Contact angle value indicates that the textured wafer's surface fall in between near-hydrophobic to hydrophobic range. With respect to base material absolute reflectance 1.049-0.75% within 250-800 nm wavelength region, 0.1-0.026% has been achieved within the same wavelength region when textured with 0.76 wt% KOH-4 wt% IPA solution for 20 min. Furthermore, an alternative route of using 1 wt% Na2CO3-0.2 wt% NaHCO3 solution for 50 min has been exploited in the texturization process.

RADIATION PASTEURIZATION OF FRESH FRUITS AND VEGETABLES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Truelsen, T.A.

1963-03-01

Use of pasteurizing doses of Co/sup 60/ gamma radiation to increase the stability of fresh strawberries, raspberries, cauliflower, tomatoes, and asparagus was tested. Only with strawberries was it possible to obtain a considerable increase in stability. For all products there appeared to be a close connection between grading for taste and texture. Strawberry samples irradiated with 100, 200, 300, or 400 krad showed, a few days after treatment, no significant differences in scores between treated and untreated berries. However, after storage for 8 days all of the irradiated samples were judged better, and after 14 days, only the samples givenmore » high doses of radiation still appeared to be in better condition. At this time, however, berries from all types of treatment were judged unacceptable. Raspberries exposed to 250 to 500 krad showed deterioration of taste and texture, but 4 days after the berries were exposed to 100 krad they were given better marks than controls. Cauliflower examples exposed to 300 krad were considerably darker in 24 hours, and after 27 days discoloration was very pronounced. Irradiation of tomatoes appeared to impnir the formation of lycopene. Doses of 1000 krad in asparagus caused deterioration of both taste and texture, with best results at a radiation dose of 250 krad. Only in raspberries was it possible for the low doses later in the storage period to raise the taste marks above the level of those given untreated samples. However, the improvement was not sufficient for the increase in stability to be of practical importance. (TCO)« less

Characterisation of group behaviour surface texturing with multi-layers fitting method

NASA Astrophysics Data System (ADS)

Kang, Zhengyang; Fu, Yonghong; Ji, Jinghu; Wang, Hao

2016-07-01

Surface texturing was widely applied in improving the tribological properties of mechanical components, but study of measurement of this technology was still insufficient. This study proposed the multi-layers fitting (MLF) method to characterise the dimples array texture surface. Based on the synergistic effect among the dimples, the 3D morphology of texture surface was rebuilt by 2D stylus profiler in the MLF method. The feasible regions of texture patterns and sensitive parameters were confirmed by non-linear programming, and the processing software of MLF method was developed based on the Matlab®. The characterisation parameters system of dimples was defined mathematically, and the accuracy of MLF method was investigated by comparison experiment. The surface texture specimens were made by laser surface texturing technology, in which high consistency of dimples' size and distribution was achieved. Then, 2D profiles of different dimples were captured by employing Hommel-T1000 stylus profiler, and the data were further processed by MLF software to rebuild 3D morphology of single dimple. The experiment results indicated that the MLF characterisation results were similar to those of Wyko T1100, the white light interference microscope. It was also found that the stability of MLF characterisation results highly depended on the number of captured cross-sections.

Optimizing the sensory characteristics and acceptance of canned cat food: use of a human taste panel.

PubMed

Pickering, G J

2009-02-01

A methodology based on descriptive analysis techniques used in the evaluation of human food has been successfully refined to allow for a human taste panel to profile the flavour and texture of a range of cat food products (CFP) and their component parts. Included in this method is the development of evaluation protocols for homogeneous products and for binary samples containing both meat chunk (MC) and gravy/gel (GG) constituents. Using these techniques, 18 flavour attributes (sweet, sour/acid, tuna, herbal, spicy, soy, salty, cereal, caramel, chicken, methionine, vegetable, offaly, meaty, burnt flavour, prawn, rancid and bitter) and four texture dimensions (hardness, chewiness, grittiness and viscosity) were generated to describe the sensations elicited by 13 commercial pet food samples. These samples differed in intensity for 16 of the 18 flavour attributes, which allows for individual CFP flavour profiles to be developed. Principal components analysis (PCA) could successfully discriminate between samples within the PCA space and also reveal some groupings amongst them. While many flavour attributes were weakly correlated, a large number (describing both taste and retro-nasal aroma qualities) were required to adequately differentiate between samples, suggesting considerable complexity in the products assessed. For both MC and GG, differences between samples for each of the texture dimensions were also found. For MC, grittiness appears to be the most discriminating textural attribute, while for GG viscosity discriminates well between samples. Meat chunks and gravy/gels differed significantly from each other in both flavour and texture. Cat food products differed in their liking ratings, although no differences were found between homogeneous, MC and GG samples, and eight flavour attributes were correlated with overall liking scores. It is now necessary to determine the usefulness and limits of sensory data gathered from human panels in describing and predicting food acceptance and preference behaviours in cats. For instance, while the sense of taste in cats appears generally similar to that of other mammals, they lack a sweet taste receptor (Li et al., 2006), which may limit the applicability of sweetness ratings obtained from humans. Modification of existing techniques used with human food research, such as external preference mapping (Naes and Risvik, 1996) may be useful. Ultimately, this may facilitate more economical and efficient methods for optimizing cat food flavour and texture and predicting the effects of composition and processing changes on cat feeding behaviour. This will require collaboration between pet food manufacturers and nutritionists, animal behaviourists and human sensory scientists. The results of this preliminary study should assist in this process.

Piezoelectric textured ceramics: Effective properties and application to ultrasonic transducers.

PubMed

Levassort, Franck; Pham Thi, Mai; Hemery, Henry; Marechal, Pierre; Tran-Huu-Hue, Louis-Pascal; Lethiecq, Marc

2006-12-22

Piezoelectric textured ceramics obtained by homo-template grain growth (HTGG) were recently demonstrated. A simple model with several assumptions has been used to calculate effective parameters of these new materials. Different connectivities have been simulated to show that spatial arrangements between the considered phases have little influence on the effective parameters, even through the 3-0 connectivity delivers the highest electromechanical thickness factor. A transducer based on a textured ceramic sample has been fabricated and characterised to show the efficiency of these piezoelectric materials. Finally, in a single element transducer configuration, simulation shows an improvement of 2 dB sensitivity for a transducer made with textured ceramic in comparison with a similar transducer design based on standard soft PZT (at equivalent bandwidths).

Mapping lava flow textures using three-dimensional measures of surface roughness

NASA Astrophysics Data System (ADS)

Mallonee, H. C.; Kobs-Nawotniak, S. E.; McGregor, M.; Hughes, S. S.; Neish, C.; Downs, M.; Delparte, D.; Lim, D. S. S.; Heldmann, J. L.

2016-12-01

Lava flow emplacement conditions are reflected in the surface textures of a lava flow; unravelling these conditions is crucial to understanding the eruptive history and characteristics of basaltic volcanoes. Mapping lava flow textures using visual imagery alone is an inherently subjective process, as these images generally lack the resolution needed to make these determinations. Our team has begun mapping lava flow textures using visual spectrum imagery, which is an inherently subjective process involving the challenge of identifying transitional textures such as rubbly and slabby pāhoehoe, as these textures are similar in appearance and defined qualitatively. This is particularly problematic for interpreting planetary lava flow textures, where we have more limited data. We present a tool to objectively classify lava flow textures based on quantitative measures of roughness, including the 2D Hurst exponent, RMS height, and 2D:3D surface area ratio. We collected aerial images at Craters of the Moon National Monument (COTM) using Unmanned Aerial Vehicles (UAVs) in 2015 and 2016 as part of the FINESSE (Field Investigations to Enable Solar System Science and Exploration) and BASALT (Biologic Analog Science Associated with Lava Terrains) research projects. The aerial images were stitched together to create Digital Terrain Models (DTMs) with resolutions on the order of centimeters. The DTMs were evaluated by the classification tool described above, with output compared against field assessment of the texture. Further, the DTMs were downsampled and reevaluated to assess the efficacy of the classification tool at data resolutions similar to current datasets from other planetary bodies. This tool allows objective classification of lava flow texture, which enables more accurate interpretations of flow characteristics. This work also gives context for interpretations of flows with comparatively low data resolutions, such as those on the Moon and Mars. Textural maps based on quantitative measures of roughness are a valuable asset for studies of lava flows on Earth and other planetary bodies.

A parametric texture model based on deep convolutional features closely matches texture appearance for humans.

PubMed

Wallis, Thomas S A; Funke, Christina M; Ecker, Alexander S; Gatys, Leon A; Wichmann, Felix A; Bethge, Matthias

2017-10-01

Our visual environment is full of texture-"stuff" like cloth, bark, or gravel as distinct from "things" like dresses, trees, or paths-and humans are adept at perceiving subtle variations in material properties. To investigate image features important for texture perception, we psychophysically compare a recent parametric model of texture appearance (convolutional neural network [CNN] model) that uses the features encoded by a deep CNN (VGG-19) with two other models: the venerable Portilla and Simoncelli model and an extension of the CNN model in which the power spectrum is additionally matched. Observers discriminated model-generated textures from original natural textures in a spatial three-alternative oddity paradigm under two viewing conditions: when test patches were briefly presented to the near-periphery ("parafoveal") and when observers were able to make eye movements to all three patches ("inspection"). Under parafoveal viewing, observers were unable to discriminate 10 of 12 original images from CNN model images, and remarkably, the simpler Portilla and Simoncelli model performed slightly better than the CNN model (11 textures). Under foveal inspection, matching CNN features captured appearance substantially better than the Portilla and Simoncelli model (nine compared to four textures), and including the power spectrum improved appearance matching for two of the three remaining textures. None of the models we test here could produce indiscriminable images for one of the 12 textures under the inspection condition. While deep CNN (VGG-19) features can often be used to synthesize textures that humans cannot discriminate from natural textures, there is currently no uniformly best model for all textures and viewing conditions.

Acquiring 3-D information about thick objects from differential interference contrast images using texture extraction

NASA Astrophysics Data System (ADS)

Sierra, Heidy; Brooks, Dana; Dimarzio, Charles

2010-07-01

The extraction of 3-D morphological information about thick objects is explored in this work. We extract this information from 3-D differential interference contrast (DIC) images by applying a texture detection method. Texture extraction methods have been successfully used in different applications to study biological samples. A 3-D texture image is obtained by applying a local entropy-based texture extraction method. The use of this method to detect regions of blastocyst mouse embryos that are used in assisted reproduction techniques such as in vitro fertilization is presented as an example. Results demonstrate the potential of using texture detection methods to improve morphological analysis of thick samples, which is relevant to many biomedical and biological studies. Fluorescence and optical quadrature microscope phase images are used for validation.

Informedia at TRECVID 2003: Analyzing and Searching Broadcast News Video

DTIC Science & Technology

2004-11-03

browsing interface to browse the top-ranked shots according to the different classifiers. Color and texture based image search engines were also...different classifiers. Color and texture based image search engines were also optimized better performance. This “new” interface was evaluated as

Usefulness of Mehlich-3 test in the monitoring of phosphorus dispersion from Polish arable soils.

PubMed

Szara, Ewa; Sosulski, Tomasz; Szymańska, Magdalena; Szyszkowska, Katarzyna

2018-04-19

A considerable area of soils with low abundance of plant-available phosphorus and relatively low consumption of phosphorus fertilisers recorded in Poland over the last 20-25 years suggests that the dispersion of phosphates from arable soils in Poland can be low. The literature, however, provides reports on a considerable share of Polish agriculture in phosphorus pollution of Baltic Sea waters. The literature provides no data concerning phosphorus sorption parameters of arable soils in Poland. Due to this, the study involved the analysis of sorption properties: 1-point phosphorus sorption index (PSI) and degree of phosphorus saturation, based on molar ratio P, Al, and Fe determined by the Mehlich-3 method (DPS-1 M3  = P / (Al + Fe) and DPS-2 M3  = P / Al), 59 soils representing the main types of texture of soils in Poland, characterised by variable content of plant-available phosphorus by Egner-Riehm DL, organic carbon, and soil pH. The obtained results suggest that the soil texture has a lower effect on sorption properties (PSI) than the degree of acidification. Sorption parameters of soils increased with soil acidification as a result of an increase in the content of Al and Fe extracted by the Mehlich-3 extract in strongly acidified soils. An important finding of our study was evidencing that within the same class of abundance in plant-available phosphorus, the soils varied in the degree of phosphorus saturation and content of active phosphorus. This suggests the possibility of losses of phosphorus even from soils with low abundance of the component provided they are characterised by a high value of parameters DPS-1 M3 and DPS-2 M3 .

Detecting fractal power-law long-range dependence in pre-sliced cooked pork ham surface intensity patterns using Detrended Fluctuation Analysis.

PubMed

Valous, Nektarios A; Drakakis, Konstantinos; Sun, Da-Wen

2010-10-01

The visual texture of pork ham slices reveals information about the different qualities and perceived image heterogeneity, which is encapsulated as spatial variations in geometry and spectral characteristics. Detrended Fluctuation Analysis (DFA) detects long-range correlations in nonstationary spatial sequences, by a self-similarity scaling exponent alpha. In the current work, the aim is to investigate the usefulness of alpha, using different colour channels (R, G, B, L*, a*, b*, H, S, V, and Grey), as a quantitative descriptor of visual texture in sliced ham surface patterns for the detection of long-range correlations in unidimensional spatial series of greyscale intensity pixel values at 0 degrees , 30 degrees , 45 degrees , 60 degrees , and 90 degrees rotations. Images were acquired from three qualities of pre-sliced pork ham, typically consumed in Ireland (200 slices per quality). Results indicated that the DFA approach can be used to characterize and quantify the textural appearance of the three ham qualities, for different image orientations, with a global scaling exponent. The spatial series extracted from the ham images display long-range dependence, indicating an average behaviour around 1/f-noise. Results indicate that alpha has a universal character in quantifying the visual texture of ham surface intensity patterns, with no considerable crossovers that alter the behaviour of the fluctuations. Fractal correlation properties can thus be a useful metric for capturing information embedded in the visual texture of hams. Copyright (c) 2010 The American Meat Science Association. Published by Elsevier Ltd. All rights reserved.

BCC skin cancer diagnosis based on texture analysis techniques

NASA Astrophysics Data System (ADS)

Chuang, Shao-Hui; Sun, Xiaoyan; Chang, Wen-Yu; Chen, Gwo-Shing; Huang, Adam; Li, Jiang; McKenzie, Frederic D.

2011-03-01

In this paper, we present a texture analysis based method for diagnosing the Basal Cell Carcinoma (BCC) skin cancer using optical images taken from the suspicious skin regions. We first extracted the Run Length Matrix and Haralick texture features from the images and used a feature selection algorithm to identify the most effective feature set for the diagnosis. We then utilized a Multi-Layer Perceptron (MLP) classifier to classify the images to BCC or normal cases. Experiments showed that detecting BCC cancer based on optical images is feasible. The best sensitivity and specificity we achieved on our data set were 94% and 95%, respectively.

Bayesian Fusion of Color and Texture Segmentations

NASA Technical Reports Server (NTRS)

Manduchi, Roberto

2000-01-01

In many applications one would like to use information from both color and texture features in order to segment an image. We propose a novel technique to combine "soft" segmentations computed for two or more features independently. Our algorithm merges models according to a mean entropy criterion, and allows to choose the appropriate number of classes for the final grouping. This technique also allows to improve the quality of supervised classification based on one feature (e.g. color) by merging information from unsupervised segmentation based on another feature (e.g., texture.)

Hepatic CT image query using Gabor features

NASA Astrophysics Data System (ADS)

Zhao, Chenguang; Cheng, Hongyan; Zhuang, Tiange

2004-07-01

A retrieval scheme for liver computerize tomography (CT) images based on Gabor texture is presented. For each hepatic CT image, we manually delineate abnormal regions within liver area. Then, a continuous Gabor transform is utilized to analyze the texture of the pathology bearing region and extract the corresponding feature vectors. For a given sample image, we compare its feature vector with those of other images. Similar images with the highest rank are retrieved. In experiments, 45 liver CT images are collected, and the effectiveness of Gabor texture for content based retrieval is verified.

Noninvasive Classification of Hepatic Fibrosis Based on Texture Parameters From Double Contrast-Enhanced Magnetic Resonance Images

PubMed Central

Bahl, Gautam; Cruite, Irene; Wolfson, Tanya; Gamst, Anthony C.; Collins, Julie M.; Chavez, Alyssa D.; Barakat, Fatma; Hassanein, Tarek; Sirlin, Claude B.

2016-01-01

Purpose To demonstrate a proof of concept that quantitative texture feature analysis of double contrast-enhanced magnetic resonance imaging (MRI) can classify fibrosis noninvasively, using histology as a reference standard. Materials and Methods A Health Insurance Portability and Accountability Act (HIPAA)-compliant Institutional Review Board (IRB)-approved retrospective study of 68 patients with diffuse liver disease was performed at a tertiary liver center. All patients underwent double contrast-enhanced MRI, with histopathology-based staging of fibrosis obtained within 12 months of imaging. The MaZda software program was used to compute 279 texture parameters for each image. A statistical regularization technique, generalized linear model (GLM)-path, was used to develop a model based on texture features for dichotomous classification of fibrosis category (F ≤2 vs. F ≥3) of the 68 patients, with histology as the reference standard. The model's performance was assessed and cross-validated. There was no additional validation performed on an independent cohort. Results Cross-validated sensitivity, specificity, and total accuracy of the texture feature model in classifying fibrosis were 91.9%, 83.9%, and 88.2%, respectively. Conclusion This study shows proof of concept that accurate, noninvasive classification of liver fibrosis is possible by applying quantitative texture analysis to double contrast-enhanced MRI. Further studies are needed in independent cohorts of subjects. PMID:22851409

Significance of MPEG-7 textural features for improved mass detection in mammography.

PubMed

Eltonsy, Nevine H; Tourassi, Georgia D; Fadeev, Aleksey; Elmaghraby, Adel S

2006-01-01

The purpose of the study is to investigate the significance of MPEG-7 textural features for improving the detection of masses in screening mammograms. The detection scheme was originally based on morphological directional neighborhood features extracted from mammographic regions of interest (ROIs). Receiver Operating Characteristics (ROC) was performed to evaluate the performance of each set of features independently and merged into a back-propagation artificial neural network (BPANN) using the leave-one-out sampling scheme (LOOSS). The study was based on a database of 668 mammographic ROIs (340 depicting cancer regions and 328 depicting normal parenchyma). Overall, the ROC area index of the BPANN using the directional morphological features was Az=0.85+/-0.01. The MPEG-7 edge histogram descriptor-based BPNN showed an ROC area index of Az=0.71+/-0.01 while homogeneous textural descriptors using 30 and 120 channels helped the BPNN achieve similar ROC area indexes of Az=0.882+/-0.02 and Az=0.877+/-0.01 respectively. After merging the MPEG-7 homogeneous textural features with the directional neighborhood features the performance of the BPANN increased providing an ROC area index of Az=0.91+/-0.01. MPEG-7 homogeneous textural descriptor significantly improved the morphology-based detection scheme.

Prediction models for solitary pulmonary nodules based on curvelet textural features and clinical parameters.

PubMed

Wang, Jing-Jing; Wu, Hai-Feng; Sun, Tao; Li, Xia; Wang, Wei; Tao, Li-Xin; Huo, Da; Lv, Ping-Xin; He, Wen; Guo, Xiu-Hua

2013-01-01

Lung cancer, one of the leading causes of cancer-related deaths, usually appears as solitary pulmonary nodules (SPNs) which are hard to diagnose using the naked eye. In this paper, curvelet-based textural features and clinical parameters are used with three prediction models [a multilevel model, a least absolute shrinkage and selection operator (LASSO) regression method, and a support vector machine (SVM)] to improve the diagnosis of benign and malignant SPNs. Dimensionality reduction of the original curvelet-based textural features was achieved using principal component analysis. In addition, non-conditional logistical regression was used to find clinical predictors among demographic parameters and morphological features. The results showed that, combined with 11 clinical predictors, the accuracy rates using 12 principal components were higher than those using the original curvelet-based textural features. To evaluate the models, 10-fold cross validation and back substitution were applied. The results obtained, respectively, were 0.8549 and 0.9221 for the LASSO method, 0.9443 and 0.9831 for SVM, and 0.8722 and 0.9722 for the multilevel model. All in all, it was found that using curvelet-based textural features after dimensionality reduction and using clinical predictors, the highest accuracy rate was achieved with SVM. The method may be used as an auxiliary tool to differentiate between benign and malignant SPNs in CT images.

A microstructure-based yield stress and work-hardening model for textured 6xxx aluminium alloys

NASA Astrophysics Data System (ADS)

Khadyko, M.; Myhr, O. R.; Dumoulin, S.; Hopperstad, O. S.

2016-04-01

The plastic properties of an aluminium alloy are defined by its microstructure. The most important factors are the presence of alloying elements in the form of solid solution and precipitates of various sizes, and the crystallographic texture. A nanoscale model that predicts the work-hardening curves of 6xxx aluminium alloys was proposed by Myhr et al. The model predicts the solid solution concentration and the particle size distributions of different types of metastable precipitates from the chemical composition and thermal history of the alloy. The yield stress and the work hardening of the alloy are then determined from dislocation mechanics. The model was largely used for non-textured materials in previous studies. In this work, a crystal plasticity-based approach is proposed for the work hardening part of the nanoscale model, which allows including the influence of the crystallographic texture. The model is evaluated by comparison with experimental data from uniaxial tensile tests on two textured 6xxx alloys in five temper conditions.

Surface texture can bias tactile form perception.

PubMed

Nakatani, Masashi; Howe, Robert D; Tachi, Susumu

2011-01-01

The sense of touch is believed to provide a reliable perception of the object's properties; however, our tactile perceptions could be illusory at times. A recently reported tactile illusion shows that a raised form can be perceived as indented when it is surrounded by textured areas. This phenomenon suggests that the form perception can be influenced by the surface textures in its adjacent areas. As perception of texture and that of form have been studied independently of each other, the present study examined whether textures, in addition to the geometric edges, contribute to the tactile form perception. We examined the perception of the flat and raised contact surface (3.0 mm width) with various heights (0.1, 0.2, 0.3 mm), which had either textured or non-textured adjacent areas, under the static, passive and active touch conditions. Our results showed that texture decreased the raised perception of the surface with a small height (0.1 mm) and decreased the flat perception of the physically flat surface under the passive and active touch conditions. We discuss a possible mechanism underlying the effect of the textures on the form perception based on previous neurophysiological findings.

Robustness of topological Hall effect of nontrivial spin textures

NASA Astrophysics Data System (ADS)

Jalil, Mansoor B. A.; Tan, Seng Ghee

2014-05-01

We analyze the topological Hall conductivity (THC) of topologically nontrivial spin textures like magnetic vortices and skyrmions and investigate its possible application in the readback for magnetic memory based on those spin textures. Under adiabatic conditions, such spin textures would theoretically yield quantized THC values, which are related to topological invariants such as the winding number and polarity, and as such are insensitive to fluctuations and smooth deformations. However, in a practical setting, the finite size of spin texture elements and the influence of edges may cause them to deviate from their ideal configurations. We calculate the degree of robustness of the THC output in practical magnetic memories in the presence of edge and finite size effects.

Characterization of microstructure and texture across dissimilar super duplex/austenitic stainless steel weldment joint by super duplex filler metal

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eghlimi, Abbas, E-mail: a.eghlimi@ma.iut.ac.ir; Shamanian, Morteza; Eskandarian, Masoomeh

In the present paper, microstructural changes across an as-welded dissimilar austenitic/duplex stainless steel couple welded by a super duplex stainless steel filler metal using gas tungsten arc welding process is characterized with optical microscopy and electron back-scattered diffraction techniques. Accordingly, variations of microstructure, texture, and grain boundary character distribution of base metals, heat affected zones, and weld metal were investigated. The results showed that the weld metal, which was composed of Widmanstätten austenite side-plates and allotriomorphic grain boundary austenite morphologies, had the weakest texture and was dominated by low angle boundaries. The welding process increased the ferrite content but decreasedmore » the texture intensity at the heat affected zone of the super duplex stainless steel base metal. In addition, through partial ferritization, it changed the morphology of elongated grains of the rolled microstructure to twinned partially transformed austenite plateaus scattered between ferrite textured colonies. However, the texture of the austenitic stainless steel heat affected zone was strengthened via encouraging recrystallization and formation of annealing twins. At both interfaces, an increase in the special character coincident site lattice boundaries of the primary phase as well as a strong texture with <100> orientation, mainly of Goss component, was observed. - Graphical abstract: Display Omitted - Highlights: • Weld metal showed local orientation at microscale but random texture at macroscale. • Intensification of <100> orientated grains was observed adjacent to the fusion lines. • The austenite texture was weaker than that of the ferrite in all duplex regions. • Welding caused twinned partially transformed austenites to form at SDSS HAZ. • At both interfaces, the ratio of special CSL boundaries of the primary phase increased.« less

Texture and anisotropy in the bismuth sodium titanate system

NASA Astrophysics Data System (ADS)

Fancher, Christoher M.

Bi0.5Na0.5TiO3 has received interest as a potential replacement for lead containing ferroelectrics. However, the piezoelectric response of pure Bi0.5Na0.5TiO 3 does not compare to the strong piezoelectric response of lead based piezoelectrics. To increase the piezoelectric response, Bi0.5Na 0.5TiO3 has been alloyed with BaTiO3 and K 0.5Na0.5NbO3. Another route to enhance the response is to take advantage of the anisotropic properties by inducing a preferred crystallographic orientation. Both routes were used to investigate the effect a crystallographic texture has on the strain response of Bi0.5Na 0.5TiO3-based ceramics. A crystallographic texture was induced by templated grain growth of pure phase Bi0.5Na0.5TiO3 templates using the tape casting method to orient template particles relative to the tape cast normal. Sintered Bi0.5Na0.5TiO3-based materials developed a strong (00l)pc fiber texture relative to the tape cast normal, with no preferential alignment relative to the tape cast plane. Textured Bi0.5Na0.5TiO3-(5)BaTiO3 showed a piezoelectric response of 245 pC/N, a better than 50% enhancement from the 150 pC/N response of randomly oriented samples. The Bi0.5Na0.5TiO3-(5)BaTiO3-(2)K 0.5Na0.5NbO3 (x,y) system has been shown to undergo electric-field-induced phase transformation from a pseudocubic to polar phase. For (7,2) a strong 8.7 multiples of a random distribution (MRD) crystallographic texture increased the macroscopic strain response by 50%. Applying the electric field perpendicular to the fiber texture axis reduces the macroscopic strain response of textured (7,2) by 17%. The affect field direction has on the electric-field-induced phase transformations of textured (7,2) was investigated using in situ electric field dependent diffraction. In situ diffraction data showed the high strain response of textured (7,2) can be attributed to a reversible pseudocubic to tetragonal transformation. The field-induced tetragonal phase nucleates preferentially with a strong c-axis alignment in the electric field direction, ferroelastic domain texture. In situ diffraction data suggests the origin of the reduction in strain associated with a field applied perpendicular to the fiber texture axis is the result of a shorter induced lattice spacing and lower domain texture.

Computer-aided diagnosis of melanoma using border and wavelet-based texture analysis.

PubMed

Garnavi, Rahil; Aldeen, Mohammad; Bailey, James

2012-11-01

This paper presents a novel computer-aided diagnosis system for melanoma. The novelty lies in the optimised selection and integration of features derived from textural, borderbased and geometrical properties of the melanoma lesion. The texture features are derived from using wavelet-decomposition, the border features are derived from constructing a boundaryseries model of the lesion border and analysing it in spatial and frequency domains, and the geometry features are derived from shape indexes. The optimised selection of features is achieved by using the Gain-Ratio method, which is shown to be computationally efficient for melanoma diagnosis application. Classification is done through the use of four classifiers; namely, Support Vector Machine, Random Forest, Logistic Model Tree and Hidden Naive Bayes. The proposed diagnostic system is applied on a set of 289 dermoscopy images (114 malignant, 175 benign) partitioned into train, validation and test image sets. The system achieves and accuracy of 91.26% and AUC value of 0.937, when 23 features are used. Other important findings include (i) the clear advantage gained in complementing texture with border and geometry features, compared to using texture information only, and (ii) higher contribution of texture features than border-based features in the optimised feature set.

Model-Based Learning of Local Image Features for Unsupervised Texture Segmentation

NASA Astrophysics Data System (ADS)

Kiechle, Martin; Storath, Martin; Weinmann, Andreas; Kleinsteuber, Martin

2018-04-01

Features that capture well the textural patterns of a certain class of images are crucial for the performance of texture segmentation methods. The manual selection of features or designing new ones can be a tedious task. Therefore, it is desirable to automatically adapt the features to a certain image or class of images. Typically, this requires a large set of training images with similar textures and ground truth segmentation. In this work, we propose a framework to learn features for texture segmentation when no such training data is available. The cost function for our learning process is constructed to match a commonly used segmentation model, the piecewise constant Mumford-Shah model. This means that the features are learned such that they provide an approximately piecewise constant feature image with a small jump set. Based on this idea, we develop a two-stage algorithm which first learns suitable convolutional features and then performs a segmentation. We note that the features can be learned from a small set of images, from a single image, or even from image patches. The proposed method achieves a competitive rank in the Prague texture segmentation benchmark, and it is effective for segmenting histological images.

Effect of House Cricket (Acheta domesticus) Flour Addition on Physicochemical and Textural Properties of Meat Emulsion Under Various Formulations.

PubMed

Kim, Hyun-Wook; Setyabrata, Derico; Lee, YongJae; Jones, Owen G; Kim, Yuan H Brad

2017-12-01

The objective of this study was to determine the effect of house cricket (Acheta domesticus) flour addition on physicochemical and textural properties of meat emulsion under various formulations. As an initial marker of functionality, protein solubility, water absorption, emulsifying capacity, and gel formation ability of house cricket flour were determined at pH (2 to 10) and NaCl concentrations (0 to 2.10 M). Control emulsion was formulated with 60% lean pork, 20% back fat, and 20% ice. Six treatment emulsions were prepared with replacement of lean pork and/or back fat portions with spray-dried house cricket flour at 5% and 10% levels, based on a total sample weight. The protein solubility of house cricket flour (67 g protein/100 g) was significantly altered depending upon pH (P < 0.0001) and NaCl concentration (P = 0.0421). Similar water absorption capacity, emulsifying capacity, and gel formation ability of house cricket flour were found between 0 and 2.10 M NaCl concentration (P > 0.05). The replacement of lean meat/fat portion with house cricket flour within 10% level could fortify protein and some micronutrients (phosphorus, potassium, and magnesium) in meat emulsion, without negative impacts on cooking yield and textural properties. Our results suggest that house cricket flour can be used as an effective nonmeat functional ingredient to manufacture emulsified meat products. To better utilize house cricket flour as a food ingredient in wide application, understanding its technological properties in various pH, and ionic strength conditions is a pivotal step. Protein solubility of house cricket flour would be considerably affected by the varying pH and NaCl concentrations of applied conventional foods. In the case of meat emulsion, within 10% lean meat and/or fat portions could be successfully substituted with house cricket flour without detectable adverse impacts on technological properties associated with cooking yield and instrumental analysis of texture. Thus, our findings suggest that house cricket flour possess the necessary physical properties to be used as an alternative nonmeat ingredient for incorporation within emulsified meat products, which could be further explored in subsequent sensory-based studies. © 2017 Institute of Food Technologists®.

A Fourier-based textural feature extraction procedure

NASA Technical Reports Server (NTRS)

Stromberg, W. D.; Farr, T. G.

1986-01-01

A procedure is presented to discriminate and characterize regions of uniform image texture. The procedure utilizes textural features consisting of pixel-by-pixel estimates of the relative emphases of annular regions of the Fourier transform. The utility and derivation of the features are described through presentation of a theoretical justification of the concept followed by a heuristic extension to a real environment. Two examples are provided that validate the technique on synthetic images and demonstrate its applicability to the discrimination of geologic texture in a radar image of a tropical vegetated area.

An RBF-based reparameterization method for constrained texture mapping.

PubMed

Yu, Hongchuan; Lee, Tong-Yee; Yeh, I-Cheng; Yang, Xiaosong; Li, Wenxi; Zhang, Jian J

2012-07-01

Texture mapping has long been used in computer graphics to enhance the realism of virtual scenes. However, to match the 3D model feature points with the corresponding pixels in a texture image, surface parameterization must satisfy specific positional constraints. However, despite numerous research efforts, the construction of a mathematically robust, foldover-free parameterization that is subject to positional constraints continues to be a challenge. In the present paper, this foldover problem is addressed by developing radial basis function (RBF)-based reparameterization. Given initial 2D embedding of a 3D surface, the proposed method can reparameterize 2D embedding into a foldover-free 2D mesh, satisfying a set of user-specified constraint points. In addition, this approach is mesh free. Therefore, generating smooth texture mapping results is possible without extra smoothing optimization.

Twinning-mediated work hardening and texture evolution in CrCoFeMnNi high entropy alloys at cryogenic temperature

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, T. K.; Wu, Z.; Stoica, A. D.

The cryogenic plastic deformation of CrCoFeMnNi high entropy alloy is characterized by three distinct stages based on the change of the work hardening rate. Microstructure and bulk texture at different strain levels were studied by electron backscatter diffraction (EBSD) and neutron diffraction. Our findings indicate that the deformation twins led to the constant work hardening rate at Stage II and resulted in the appearance of <115 >//TA texture component, while the dislocation slip was involved all though the entire plastic deformation. As a result, the twinning-mediated tensile plastic deformation at cryogenic temperature finally induced the strong {111}- < 112 >more » texture component and minor {001} < 110 > texture component accompanied with twinning-induced {115}< 552 > texture component.« less

Twinning-mediated work hardening and texture evolution in CrCoFeMnNi high entropy alloys at cryogenic temperature

DOE PAGES

Liu, T. K.; Wu, Z.; Stoica, A. D.; ...

2017-06-17

The cryogenic plastic deformation of CrCoFeMnNi high entropy alloy is characterized by three distinct stages based on the change of the work hardening rate. Microstructure and bulk texture at different strain levels were studied by electron backscatter diffraction (EBSD) and neutron diffraction. Our findings indicate that the deformation twins led to the constant work hardening rate at Stage II and resulted in the appearance of <115 >//TA texture component, while the dislocation slip was involved all though the entire plastic deformation. As a result, the twinning-mediated tensile plastic deformation at cryogenic temperature finally induced the strong {111}- < 112 >more » texture component and minor {001} < 110 > texture component accompanied with twinning-induced {115}< 552 > texture component.« less

Textural features and SUV-based variables assessed by dual time point 18F-FDG PET/CT in locally advanced breast cancer.

PubMed

Garcia-Vicente, Ana María; Molina, David; Pérez-Beteta, Julián; Amo-Salas, Mariano; Martínez-González, Alicia; Bueno, Gloria; Tello-Galán, María Jesús; Soriano-Castrejón, Ángel

2017-12-01

To study the influence of dual time point 18F-FDG PET/CT in textural features and SUV-based variables and their relation among them. Fifty-six patients with locally advanced breast cancer (LABC) were prospectively included. All of them underwent a standard 18F-FDG PET/CT (PET-1) and a delayed acquisition (PET-2). After segmentation, SUV variables (SUVmax, SUVmean, and SUVpeak), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were obtained. Eighteen three-dimensional (3D) textural measures were computed including: run-length matrices (RLM) features, co-occurrence matrices (CM) features, and energies. Differences between all PET-derived variables obtained in PET-1 and PET-2 were studied. Significant differences were found between the SUV-based parameters and MTV obtained in the dual time point PET/CT, with higher values of SUV-based variables and lower MTV in the PET-2 with respect to the PET-1. In relation with the textural parameters obtained in dual time point acquisition, significant differences were found for the short run emphasis, low gray-level run emphasis, short run high gray-level emphasis, run percentage, long run emphasis, gray-level non-uniformity, homogeneity, and dissimilarity. Textural variables showed relations with MTV and TLG. Significant differences of textural features were found in dual time point 18F-FDG PET/CT. Thus, a dynamic behavior of metabolic characteristics should be expected, with higher heterogeneity in delayed PET acquisition compared with the standard PET. A greater heterogeneity was found in bigger tumors.

Classifying brain metastases by their primary site of origin using a radiomics approach based on texture analysis: a feasibility study.

PubMed

Ortiz-Ramón, Rafael; Larroza, Andrés; Ruiz-España, Silvia; Arana, Estanislao; Moratal, David

2018-05-14

To examine the capability of MRI texture analysis to differentiate the primary site of origin of brain metastases following a radiomics approach. Sixty-seven untreated brain metastases (BM) were found in 3D T1-weighted MRI of 38 patients with cancer: 27 from lung cancer, 23 from melanoma and 17 from breast cancer. These lesions were segmented in 2D and 3D to compare the discriminative power of 2D and 3D texture features. The images were quantized using different number of gray-levels to test the influence of quantization. Forty-three rotation-invariant texture features were examined. Feature selection and random forest classification were implemented within a nested cross-validation structure. Classification was evaluated with the area under receiver operating characteristic curve (AUC) considering two strategies: multiclass and one-versus-one. In the multiclass approach, 3D texture features were more discriminative than 2D features. The best results were achieved for images quantized with 32 gray-levels (AUC = 0.873 ± 0.064) using the top four features provided by the feature selection method based on the p-value. In the one-versus-one approach, high accuracy was obtained when differentiating lung cancer BM from breast cancer BM (four features, AUC = 0.963 ± 0.054) and melanoma BM (eight features, AUC = 0.936 ± 0.070) using the optimal dataset (3D features, 32 gray-levels). Classification of breast cancer and melanoma BM was unsatisfactory (AUC = 0.607 ± 0.180). Volumetric MRI texture features can be useful to differentiate brain metastases from different primary cancers after quantizing the images with the proper number of gray-levels. • Texture analysis is a promising source of biomarkers for classifying brain neoplasms. • MRI texture features of brain metastases could help identifying the primary cancer. • Volumetric texture features are more discriminative than traditional 2D texture features.

Textural features of dynamic contrast-enhanced MRI derived model-free and model-based parameter maps in glioma grading.

PubMed

Xie, Tian; Chen, Xiao; Fang, Jingqin; Kang, Houyi; Xue, Wei; Tong, Haipeng; Cao, Peng; Wang, Sumei; Yang, Yizeng; Zhang, Weiguo

2018-04-01

Presurgical glioma grading by dynamic contrast-enhanced MRI (DCE-MRI) has unresolved issues. The aim of this study was to investigate the ability of textural features derived from pharmacokinetic model-based or model-free parameter maps of DCE-MRI in discriminating between different grades of gliomas, and their correlation with pathological index. Retrospective. Forty-two adults with brain gliomas. 3.0T, including conventional anatomic sequences and DCE-MRI sequences (variable flip angle T1-weighted imaging and three-dimensional gradient echo volumetric imaging). Regions of interest on the cross-sectional images with maximal tumor lesion. Five commonly used textural features, including Energy, Entropy, Inertia, Correlation, and Inverse Difference Moment (IDM), were generated. All textural features of model-free parameters (initial area under curve [IAUC], maximal signal intensity [Max SI], maximal up-slope [Max Slope]) could effectively differentiate between grade II (n = 15), grade III (n = 13), and grade IV (n = 14) gliomas (P < 0.05). Two textural features, Entropy and IDM, of four DCE-MRI parameters, including Max SI, Max Slope (model-free parameters), vp (Extended Tofts), and vp (Patlak) could differentiate grade III and IV gliomas (P < 0.01) in four measurements. Both Entropy and IDM of Patlak-based K trans and vp could differentiate grade II (n = 15) from III (n = 13) gliomas (P < 0.01) in four measurements. No textural features of any DCE-MRI parameter maps could discriminate between subtypes of grade II and III gliomas (P < 0.05). Both Entropy and IDM of Extended Tofts- and Patlak-based vp showed highest area under curve in discriminating between grade III and IV gliomas. However, intraclass correlation coefficient (ICC) of these features revealed relatively lower inter-observer agreement. No significant correlation was found between microvascular density and textural features, compared with a moderate correlation found between cellular proliferation index and those features. Textural features of DCE-MRI parameter maps displayed a good ability in glioma grading. 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1099-1111. © 2017 International Society for Magnetic Resonance in Medicine.

Atomistic modeling of dropwise condensation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sikarwar, B. S., E-mail: bssikarwar@amity.edu; Singh, P. L.; Muralidhar, K.

The basic aim of the atomistic modeling of condensation of water is to determine the size of the stable cluster and connect phenomena occurring at atomic scale to the macroscale. In this paper, a population balance model is described in terms of the rate equations to obtain the number density distribution of the resulting clusters. The residence time is taken to be large enough so that sufficient time is available for all the adatoms existing in vapor-phase to loose their latent heat and get condensed. The simulation assumes clusters of a given size to be formed from clusters of smallermore » sizes, but not by the disintegration of the larger clusters. The largest stable cluster size in the number density distribution is taken to be representative of the minimum drop radius formed in a dropwise condensation process. A numerical confirmation of this result against predictions based on a thermodynamic model has been obtained. Results show that the number density distribution is sensitive to the surface diffusion coefficient and the rate of vapor flux impinging on the substrate. The minimum drop radius increases with the diffusion coefficient and the impinging vapor flux; however, the dependence is weak. The minimum drop radius predicted from thermodynamic considerations matches the prediction of the cluster model, though the former does not take into account the effect of the surface properties on the nucleation phenomena. For a chemically passive surface, the diffusion coefficient and the residence time are dependent on the surface texture via the coefficient of friction. Thus, physical texturing provides a means of changing, within limits, the minimum drop radius. The study reveals that surface texturing at the scale of the minimum drop radius does not provide controllability of the macro-scale dropwise condensation at large timescales when a dynamic steady-state is reached.« less

Texture analysis of clinical radiographs using radon transform on a local scale for differentiation between post-menopausal women with and without hip fracture

NASA Astrophysics Data System (ADS)

Boehm, Holger F.; Körner, Markus; Baumert, Bernhard; Linsenmaier, Ulrich; Reiser, Maximilian

2011-03-01

Osteoporosis is a chronic condition characterized by demineralization and destruction of bone tissue. Fractures associated with the disease are becoming an increasingly relevant issue for public health institutions. Prediction of fracture risk is a major focus research and, over the years, has been approched by various methods. Still, bone mineral density (BMD) obtained by dual-energy X-ray absorptiometry (DXA) remains the clinical gold-standard for diagnosis and follow-up of osteoporosis. However, DXA is restricted to specialized diagnostic centers and there exists considerable overlap in BMD results between populations of individuals with and without fractures. Clinically far more available than DXA is conventional x-ray imaging depicting trabecular bone structure in great detail. In this paper, we demonstrate that bone structure depicted by clinical radiographs can be analysed quantitatively by parameters obtained from the Radon Transform (RT). RT is a global analysis-tool for detection of predefined, parameterized patterns, e.g. straight lines or struts, representing suitable approximations of trabecular bone texture. The proposed algorithm differentiates between patients with and without fractures of the hip by application of various texture-metrics based on the Radon-Transform to standard x-ray images of the proximal femur. We consider three different regions-of-interest in the proximal femur (femoral head, neck, and inter-trochanteric area), and conduct an analysis with respect to correct classification of the fracture status. Performance of the novel approach is compared to DXA. We draw the conclusion that performance of RT is comparable to DXA and may become a useful supplement to densitometry for the prediction of fracture risk.

Retrieval and Mapping of Soil Texture Based on Land Surface Diurnal Temperature Range Data from MODIS

PubMed Central

Wang, De-Cai; Zhang, Gan-Lin; Zhao, Ming-Song; Pan, Xian-Zhang; Zhao, Yu-Guo; Li, De-Cheng; Macmillan, Bob

2015-01-01

Numerous studies have investigated the direct retrieval of soil properties, including soil texture, using remotely sensed images. However, few have considered how soil properties influence dynamic changes in remote images or how soil processes affect the characteristics of the spectrum. This study investigated a new method for mapping regional soil texture based on the hypothesis that the rate of change of land surface temperature is related to soil texture, given the assumption of similar starting soil moisture conditions. The study area was a typical flat area in the Yangtze-Huai River Plain, East China. We used the widely available land surface temperature product of MODIS as the main data source. We analyzed the relationships between the content of different particle soil size fractions at the soil surface and land surface day temperature, night temperature and diurnal temperature range (DTR) during three selected time periods. These periods occurred after rainfalls and between the previous harvest and the subsequent autumn sowing in 2004, 2007 and 2008. Then, linear regression models were developed between the land surface DTR and sand (> 0.05 mm), clay (< 0.001 mm) and physical clay (< 0.01 mm) contents. The models for each day were used to estimate soil texture. The spatial distribution of soil texture from the studied area was mapped based on the model with the minimum RMSE. A validation dataset produced error estimates for the predicted maps of sand, clay and physical clay, expressed as RMSE of 10.69%, 4.57%, and 12.99%, respectively. The absolute error of the predictions is largely influenced by variations in land cover. Additionally, the maps produced by the models illustrate the natural spatial continuity of soil texture. This study demonstrates the potential for digitally mapping regional soil texture variations in flat areas using readily available MODIS data. PMID:26090852

Relevance of 2D radiographic texture analysis for the assessment of 3D bone micro-architecture

DOE Office of Scientific and Technical Information (OSTI.GOV)

Apostol, Lian; Boudousq, Vincent; Basset, Oliver

Although the diagnosis of osteoporosis is mainly based on dual x-ray absorptiometry, it has been shown that trabecular bone micro-architecture is also an important factor in regard to fracture risk. In vivo, techniques based on high-resolution x-ray radiography associated to texture analysis have been proposed to investigate bone micro-architecture, but their relevance for giving pertinent 3D information is unclear. Thirty-three calcaneus and femoral neck bone samples including the cortical shells (diameter: 14 mm, height: 30-40 mm) were imaged using 3D-synchrotron x-ray micro-CT at the ESRF. The 3D reconstructed images with a cubic voxel size of 15 {mu}m were further usedmore » for two purposes: (1) quantification of three-dimensional trabecular bone micro-architecture (2) simulation of realistic x-ray radiographs under different acquisition conditions. The simulated x-ray radiographs were then analyzed using a large variety of texture analysis methods (co-occurrence, spectral density, fractal, morphology, etc.). The range of micro-architecture parameters was in agreement with previous studies and rather large, suggesting that the population was representative. More than 350 texture parameters were tested. A small number of them were selected based on their correlation to micro-architectural morphometric parameters. Using this subset of texture parameters, multiple regression allowed one to predict up to 93% of the variance of micro-architecture parameters using three texture features. 2D texture features predicting 3D micro-architecture parameters other than BV/TV were identified. The methodology proposed for evaluating the relationships between 3D micro-architecture and 2D texture parameters may also be used for optimizing the conditions for radiographic imaging. Further work will include the application of the method to physical radiographs. In the future, this approach could be used in combination with DXA to refine osteoporosis diagnosis.« less

Retrieval and Mapping of Soil Texture Based on Land Surface Diurnal Temperature Range Data from MODIS.

PubMed

Wang, De-Cai; Zhang, Gan-Lin; Zhao, Ming-Song; Pan, Xian-Zhang; Zhao, Yu-Guo; Li, De-Cheng; Macmillan, Bob

2015-01-01

Numerous studies have investigated the direct retrieval of soil properties, including soil texture, using remotely sensed images. However, few have considered how soil properties influence dynamic changes in remote images or how soil processes affect the characteristics of the spectrum. This study investigated a new method for mapping regional soil texture based on the hypothesis that the rate of change of land surface temperature is related to soil texture, given the assumption of similar starting soil moisture conditions. The study area was a typical flat area in the Yangtze-Huai River Plain, East China. We used the widely available land surface temperature product of MODIS as the main data source. We analyzed the relationships between the content of different particle soil size fractions at the soil surface and land surface day temperature, night temperature and diurnal temperature range (DTR) during three selected time periods. These periods occurred after rainfalls and between the previous harvest and the subsequent autumn sowing in 2004, 2007 and 2008. Then, linear regression models were developed between the land surface DTR and sand (> 0.05 mm), clay (< 0.001 mm) and physical clay (< 0.01 mm) contents. The models for each day were used to estimate soil texture. The spatial distribution of soil texture from the studied area was mapped based on the model with the minimum RMSE. A validation dataset produced error estimates for the predicted maps of sand, clay and physical clay, expressed as RMSE of 10.69%, 4.57%, and 12.99%, respectively. The absolute error of the predictions is largely influenced by variations in land cover. Additionally, the maps produced by the models illustrate the natural spatial continuity of soil texture. This study demonstrates the potential for digitally mapping regional soil texture variations in flat areas using readily available MODIS data.

TU-D-207B-03: Early Assessment of Response to Chemoradiotherapy Based On Textural Analysis of Pre and Mid-Treatment FDG-PET Image in Locally Advanced Head and Neck Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cui, Y; Pollom, E; Loo, B

Purpose: To evaluate whether tumor textural features extracted from both pre- and mid-treatment FDG-PET images predict early response to chemoradiotherapy in locally advanced head and neck cancer, and investigate whether they provide complementary value to conventional volume-based measurements. Methods: Ninety-four patients with locally advanced head and neck cancers were retrospectively studied. All patients received definitive chemoradiotherapy and underwent FDG-PET planning scans both before and during treatment. Within the primary tumor we extracted 6 textural features based on gray-level co-occurrence matrices (GLCM): entropy, dissimilarity, contrast, correlation, energy, and homogeneity. These image features were evaluated for their predictive power of treatment responsemore » to chemoradiotherapy in terms of local recurrence free survival (LRFS) and progression free survival (PFS). Logrank test were used to assess the statistical significance of the stratification between low- and high-risk groups. P-values were adjusted for multiple comparisons by the false discovery rate (FDR) method. Results: All six textural features extracted from pre-treatment PET images significantly differentiated low- and high-risk patient groups for LRFS (P=0.011–0.038) and PFS (P=0.029–0.034). On the other hand, none of the textural features on mid-treatment PET images was statistically significant in stratifying LRFS (P=0.212–0.445) or PFS (P=0.168–0.299). An imaging signature that combines textural feature (GLCM homogeneity) and metabolic tumor volume showed an improved performance for predicting LRFS (hazard ratio: 22.8, P<0.0001) and PFS (hazard ratio: 13.9, P=0.0005) in leave-one-out cross validation. Intra-tumor heterogeneity measured by textural features was significantly lower in mid-treatment PET images than in pre-treatment PET images (T-test: P<1.4e-6). Conclusion: Tumor textural features on pretreatment FDG-PET images are predictive for response to chemoradiotherapy in locally advanced head and neck cancer. The complementary information offered by textural features improves patient stratification and may potentially aid in personalized risk-adaptive therapy.« less

Accuracy and variability of texture-based radiomics features of lung lesions across CT imaging conditions

NASA Astrophysics Data System (ADS)

Zheng, Yuese; Solomon, Justin; Choudhury, Kingshuk; Marin, Daniele; Samei, Ehsan

2017-03-01

Texture analysis for lung lesions is sensitive to changing imaging conditions but these effects are not well understood, in part, due to a lack of ground-truth phantoms with realistic textures. The purpose of this study was to explore the accuracy and variability of texture features across imaging conditions by comparing imaged texture features to voxel-based 3D printed textured lesions for which the true values are known. The seven features of interest were based on the Grey Level Co-Occurrence Matrix (GLCM). The lesion phantoms were designed with three shapes (spherical, lobulated, and spiculated), two textures (homogenous and heterogeneous), and two sizes (diameter < 1.5 cm and 1.5 cm < diameter < 3 cm), resulting in 24 lesions (with a second replica of each). The lesions were inserted into an anthropomorphic thorax phantom (Multipurpose Chest Phantom N1, Kyoto Kagaku) and imaged using a commercial CT system (GE Revolution) at three CTDI levels (0.67, 1.42, and 5.80 mGy), three reconstruction algorithms (FBP, IR-2, IR-4), four reconstruction kernel types (standard, soft, edge), and two slice thicknesses (0.6 mm and 5 mm). Another repeat scan was performed. Texture features from these images were extracted and compared to the ground truth feature values by percent relative error. The variability across imaging conditions was calculated by standard deviation across a certain imaging condition for all heterogeneous lesions. The results indicated that the acquisition method has a significant influence on the accuracy and variability of extracted features and as such, feature quantities are highly susceptible to imaging parameter choices. The most influential parameters were slice thickness and reconstruction kernels. Thin slice thickness and edge reconstruction kernel overall produced more accurate and more repeatable results. Some features (e.g., Contrast) were more accurately quantified under conditions that render higher spatial frequencies (e.g., thinner slice thickness and sharp kernels), while others (e.g., Homogeneity) showed more accurate quantification under conditions that render smoother images (e.g., higher dose and smoother kernels). Care should be exercised is relating texture features between cases of varied acquisition protocols, with need to cross calibration dependent on the feature of interest.

Statistical-techniques-based computer-aided diagnosis (CAD) using texture feature analysis: application in computed tomography (CT) imaging to fatty liver disease

NASA Astrophysics Data System (ADS)

Chung, Woon-Kwan; Park, Hyong-Hu; Im, In-Chul; Lee, Jae-Seung; Goo, Eun-Hoe; Dong, Kyung-Rae

2012-09-01

This paper proposes a computer-aided diagnosis (CAD) system based on texture feature analysis and statistical wavelet transformation technology to diagnose fatty liver disease with computed tomography (CT) imaging. In the target image, a wavelet transformation was performed for each lesion area to set the region of analysis (ROA, window size: 50 × 50 pixels) and define the texture feature of a pixel. Based on the extracted texture feature values, six parameters (average gray level, average contrast, relative smoothness, skewness, uniformity, and entropy) were determined to calculate the recognition rate for a fatty liver. In addition, a multivariate analysis of the variance (MANOVA) method was used to perform a discriminant analysis to verify the significance of the extracted texture feature values and the recognition rate for a fatty liver. According to the results, each texture feature value was significant for a comparison of the recognition rate for a fatty liver ( p < 0.05). Furthermore, the F-value, which was used as a scale for the difference in recognition rates, was highest in the average gray level, relatively high in the skewness and the entropy, and relatively low in the uniformity, the relative smoothness and the average contrast. The recognition rate for a fatty liver had the same scale as that for the F-value, showing 100% (average gray level) at the maximum and 80% (average contrast) at the minimum. Therefore, the recognition rate is believed to be a useful clinical value for the automatic detection and computer-aided diagnosis (CAD) using the texture feature value. Nevertheless, further study on various diseases and singular diseases will be needed in the future.

Invasion Potential of Two Tropical Physalis Species in Arid and Semi-Arid Climates: Effect of Water-Salinity Stress and Soil Types on Growth and Fecundity.

PubMed

Ozaslan, Cumali; Farooq, Shahid; Onen, Huseyin; Bukun, Bekir; Ozcan, Selcuk; Gunal, Hikmet

2016-01-01

Invasive plants are recognized for their impressive abilities to withstand adverse environmental conditions however, all invaders do not express the similar abilities. Therefore, survival, growth, nutrient uptake and fecundity of two co-occurring, invasive Physalis species were tested under water and salinity stresses, and different soil textures in the current study. Five different water stress levels (100, 75, 50, 25, and 12.5% pot water contents), four different soil salinity levels (0, 3, 6, and 12 dSm-1) and four different soil textures (67% clay, 50% clay, silt clay loam and sandy loam) were included in three different pot experiments. Both weeds survived under all levels of water stress except 12.5% water contents and on all soil types however, behaved differently under increasing salinity. The weeds responded similarly to salinity up till 3 dSm-1 whereas, P. philadelphica survived for longer time than P. angulata under remaining salinity regimes. Water and salinity stress hampered the growth and fecundity of both weeds while, soil textures had slight effect. Both weeds preferred clay textured soils for better growth and nutrient uptake however, interactive effect of weeds and soil textures was non-significant. P. angulata accumulated higher K and Na while P. philadelphica accrued more Ca and Mg as well as maintained better K/Na ratio. P. angulata accumulated more Na and P under salinity stress while, P. philadelphica accrued higher K and Mg, and maintained higher K/Na ratio. Collectively, highest nutrient accumulation was observed under stress free conditions and on clay textured soils. P. philadelphica exhibited higher reproductive output under all experimental conditions than P. angulata. It is predicted that P. philadelphica will be more problematic under optimal water supply and high salinity while P. angulata can better adapt water limited environments. The results indicate that both weeds have considerable potential to further expand their ranges in semi-arid regions of Turkey.

Invasion Potential of Two Tropical Physalis Species in Arid and Semi-Arid Climates: Effect of Water-Salinity Stress and Soil Types on Growth and Fecundity

PubMed Central

Ozaslan, Cumali; Bukun, Bekir; Ozcan, Selcuk

2016-01-01

Invasive plants are recognized for their impressive abilities to withstand adverse environmental conditions however, all invaders do not express the similar abilities. Therefore, survival, growth, nutrient uptake and fecundity of two co-occurring, invasive Physalis species were tested under water and salinity stresses, and different soil textures in the current study. Five different water stress levels (100, 75, 50, 25, and 12.5% pot water contents), four different soil salinity levels (0, 3, 6, and 12 dSm-1) and four different soil textures (67% clay, 50% clay, silt clay loam and sandy loam) were included in three different pot experiments. Both weeds survived under all levels of water stress except 12.5% water contents and on all soil types however, behaved differently under increasing salinity. The weeds responded similarly to salinity up till 3 dSm-1 whereas, P. philadelphica survived for longer time than P. angulata under remaining salinity regimes. Water and salinity stress hampered the growth and fecundity of both weeds while, soil textures had slight effect. Both weeds preferred clay textured soils for better growth and nutrient uptake however, interactive effect of weeds and soil textures was non-significant. P. angulata accumulated higher K and Na while P. philadelphica accrued more Ca and Mg as well as maintained better K/Na ratio. P. angulata accumulated more Na and P under salinity stress while, P. philadelphica accrued higher K and Mg, and maintained higher K/Na ratio. Collectively, highest nutrient accumulation was observed under stress free conditions and on clay textured soils. P. philadelphica exhibited higher reproductive output under all experimental conditions than P. angulata. It is predicted that P. philadelphica will be more problematic under optimal water supply and high salinity while P. angulata can better adapt water limited environments. The results indicate that both weeds have considerable potential to further expand their ranges in semi-arid regions of Turkey. PMID:27741269

Estimating of Soil Texture Using Landsat Imagery: a Case Study in Thatta Tehsil, Sindh

NASA Astrophysics Data System (ADS)

Khalil, Zahid

2016-07-01

Soil texture is considered as an important environment factor for agricultural growth. It is the most essential part for soil classification in large scale. Today the precise soil information in large scale is of great demand from various stakeholders including soil scientists, environmental managers, land use planners and traditional agricultural users. With the increasing demand of soil properties in fine scale spatial resolution made the traditional laboratory methods inadequate. In addition the costs of soil analysis with precision agriculture systems are more expensive than traditional methods. In this regard, the application of geo-spatial techniques can be used as an alternative for examining soil analysis. This study aims to examine the ability of Geo-spatial techniques in identifying the spatial patterns of soil attributes in fine scale. Around 28 samples of soil were collected from the different areas of Thatta Tehsil, Sindh, Pakistan for analyzing soil texture. An Ordinary Least Square (OLS) regression analysis was used to relate the reflectance values of Landsat8 OLI imagery with the soil variables. The analysis showed there was a significant relationship (p<0.05) of band 2 and 5 with silt% (R2 = 0.52), and band 4 and 6 with clay% (R2 =0.40). The equation derived from OLS analysis was then used for the whole study area for deriving soil attributes. The USDA textural classification triangle was implementing for the derivation of soil texture map in GIS environment. The outcome revealed that the 'sandy loam' was in great quantity followed by loam, sandy clay loam and clay loam. The outcome shows that the Geo-spatial techniques could be used efficiently for mapping soil texture of a larger area in fine scale. This technology helped in decreasing cost, time and increase detailed information by reducing field work to a considerable level.

Enhanced Line Integral Convolution with Flow Feature Detection

NASA Technical Reports Server (NTRS)

Lane, David; Okada, Arthur

1996-01-01

The Line Integral Convolution (LIC) method, which blurs white noise textures along a vector field, is an effective way to visualize overall flow patterns in a 2D domain. The method produces a flow texture image based on the input velocity field defined in the domain. Because of the nature of the algorithm, the texture image tends to be blurry. This sometimes makes it difficult to identify boundaries where flow separation and reattachments occur. We present techniques to enhance LIC texture images and use colored texture images to highlight flow separation and reattachment boundaries. Our techniques have been applied to several flow fields defined in 3D curvilinear multi-block grids and scientists have found the results to be very useful.

Texture and structure contribution to low-temperature plasticity enhancement of Mg-Al-Zn-Mn Alloy MA2-1hp after ECAP and annealing

NASA Astrophysics Data System (ADS)

Serebryany, V. N.; D'yakonov, G. S.; Kopylov, V. I.; Salishchev, G. A.; Dobatkin, S. V.

2013-05-01

Equal channel angular pressing (ECAP) in magnesium alloys due to severe plastic shear deformations provides both grain refinement and the slope of the initial basal texture at 40°-50° to the pressing direction. These changes in microstructure and texture contribute to the improvement of low-temperature plasticity of the alloys. Quantitative texture X-ray diffraction analysis and diffraction of backscattered electrons are used to study the main textural and structural factors responsible for enhanced low-temperature plasticity based on the example of magnesium alloy MA2-1hp of the Mg-Al-Zn-Mn system. The possible mechanisms of deformation that lead to this positive effect are discussed.

Coupled crystal orientation-size effects on the strength of nano crystals

PubMed Central

Yuan, Rui; Beyerlein, Irene J.; Zhou, Caizhi

2016-01-01

We study the combined effects of grain size and texture on the strength of nanocrystalline copper (Cu) and nickel (Ni) using a crystal-plasticity based mechanics model. Within the model, slip occurs in discrete slip events exclusively by individual dislocations emitted statistically from the grain boundaries. We show that a Hall-Petch relationship emerges in both initially texture and non-textured materials and our values are in agreement with experimental measurements from numerous studies. We find that the Hall-Petch slope increases with texture strength, indicating that preferred orientations intensify the enhancements in strength that accompany grain size reductions. These findings reveal that texture is too influential to be neglected when analyzing and engineering grain size effects for increasing nanomaterial strength. PMID:27185364

Objective and quantitative definitions of modified food textures based on sensory and rheological methodology.

PubMed

Wendin, Karin; Ekman, Susanne; Bülow, Margareta; Ekberg, Olle; Johansson, Daniel; Rothenberg, Elisabet; Stading, Mats

2010-06-28

Patients who suffer from chewing and swallowing disorders, i.e. dysphagia, may have difficulties ingesting normal food and liquids. In these patients a texture modified diet may enable that the patient maintain adequate nutrition. However, there is no generally accepted definition of 'texture' that includes measurements describing different food textures. Objectively define and quantify categories of texture-modified food by conducting rheological measurements and sensory analyses. A further objective was to facilitate the communication and recommendations of appropriate food textures for patients with dysphagia. About 15 food samples varying in texture qualities were characterized by descriptive sensory and rheological measurements. Soups were perceived as homogenous; thickened soups were perceived as being easier to swallow, more melting and creamy compared with soups without thickener. Viscosity differed between the two types of soups. Texture descriptors for pâtés were characterized by high chewing resistance, firmness, and having larger particles compared with timbales and jellied products. Jellied products were perceived as wobbly, creamy, and easier to swallow. Concerning the rheological measurements, all solid products were more elastic than viscous (G'>G''), belonging to different G' intervals: jellied products (low G') and timbales together with pâtés (higher G'). By combining sensory and rheological measurements, a system of objective, quantitative, and well-defined food textures was developed that characterizes the different texture categories.

Structure of Profiled Crystals Based on Solid Solutions of Bi2Te3 and Their X-Ray Diagnostics

NASA Astrophysics Data System (ADS)

Voronin, A. I.; Bublik, V. T.; Tabachkova, N. Yu.; Belov, Yu. M.

2011-05-01

In this work, we used x-ray structural diagnostic data to reveal the formation of structural regularities in profiled polycrystalline ingots based on Bi and Sb chalcogenide solid solutions. In Bi2Te3 lattice crystals, the solid phase grows such that the cleavage surfaces are perpendicular to the crystallization front. The crystallization singularity determines the nature of the growth texture. Because texture is an important factor determining the anisotropy of properties, which in turn determines the suitability of an ingot for production of modules and the possibility of figure of merit improvement, its diagnostics is an important issue for technology testing. Examples of texture analysis using the method of straight pole figure (SPF) construction for profiled crystals are provided. The structure of the surface layers in the profiled ingots was studied after electroerosion cutting. In addition, the method of estimation of the disturbed layer depth based on the nature of texture changes was used.

Giant energy density in [001]-textured Pb(Mg1/3Nb2/3)O3-PbZrO3-PbTiO3 piezoelectric ceramics

NASA Astrophysics Data System (ADS)

Yan, Yongke; Cho, Kyung-Hoon; Maurya, Deepam; Kumar, Amit; Kalinin, Sergei; Khachaturyan, Armen; Priya, Shashank

2013-01-01

Pb(Zr,Ti)O3 (PZT) based compositions have been challenging to texture or grow in a single crystal form due to the incongruent melting point of ZrO2. Here we demonstrate the method for achieving 90% textured PZT-based ceramics and further show that it can provide highest known energy density in piezoelectric materials through enhancement of piezoelectric charge and voltage coefficients (d and g). Our method provides more than ˜5× increase in the ratio d(textured)/d(random). A giant magnitude of d.g coefficient with value of 59 000 × 10-15 m2 N-1 (comparable to that of the single crystal counterpart and 359% higher than that of the best commercial compositions) was obtained.

Time-frequency feature representation using multi-resolution texture analysis and acoustic activity detector for real-life speech emotion recognition.

PubMed

Wang, Kun-Ching

2015-01-14

The classification of emotional speech is mostly considered in speech-related research on human-computer interaction (HCI). In this paper, the purpose is to present a novel feature extraction based on multi-resolutions texture image information (MRTII). The MRTII feature set is derived from multi-resolution texture analysis for characterization and classification of different emotions in a speech signal. The motivation is that we have to consider emotions have different intensity values in different frequency bands. In terms of human visual perceptual, the texture property on multi-resolution of emotional speech spectrogram should be a good feature set for emotion classification in speech. Furthermore, the multi-resolution analysis on texture can give a clearer discrimination between each emotion than uniform-resolution analysis on texture. In order to provide high accuracy of emotional discrimination especially in real-life, an acoustic activity detection (AAD) algorithm must be applied into the MRTII-based feature extraction. Considering the presence of many blended emotions in real life, in this paper make use of two corpora of naturally-occurring dialogs recorded in real-life call centers. Compared with the traditional Mel-scale Frequency Cepstral Coefficients (MFCC) and the state-of-the-art features, the MRTII features also can improve the correct classification rates of proposed systems among different language databases. Experimental results show that the proposed MRTII-based feature information inspired by human visual perception of the spectrogram image can provide significant classification for real-life emotional recognition in speech.

Modern methods of experimental construction of texture complete direct pole figures by using X-ray data

NASA Astrophysics Data System (ADS)

Isaenkova, M.; Perlovich, Yu; Fesenko, V.

2016-04-01

Currently used methods for constructing texture complete direct pole figure (CDPF) based on the results of X-ray diffractometric measurements were considered with respect to the products of Zr-based alloys and, in particular, used in a nuclear reactor cladding tubes, for which the accuracy of determination of integral texture parameters is of the especial importance. The main attention was devoted to technical issues which are solved by means of computer processing of large arrays of obtained experimental data. Among considered questions there are amendments of the defocusing, techniques for constructing of complete direct pole figures and determination of integral textural parameters. The methods of reconstruction of complete direct pole figures by partial direct pole figures recorded up to tilt angles of sample ψ=70-80°: the method of extrapolation of data to an uninvestigated region of the stereographic projection, and the method of "sewing" of partial pole figures measured for three mutually perpendicular plane sections of the product. The limits of applicability of these methods, depending on the shape of the test product and the degree of inhomogeneity of the layer-by-layer texture, were revealed. On the basis of a large number of experimental data, the accuracy of the integral parameters used for calculation of the physical and mechanical properties of metals with a hexagonal crystal structure was found to be equal to 0.02, when taking into account the texture heterogeneity of regular products from Zr-based alloys.

Texture-based segmentation of temperate-zone woodland in panchromatic IKONOS imagery

NASA Astrophysics Data System (ADS)

Gagnon, Langis; Bugnet, Pierre; Cavayas, Francois

2003-08-01

We have performed a study to identify optimal texture parameters for woodland segmentation in a highly non-homogeneous urban area from a temperate-zone panchromatic IKONOS image. Texture images are produced with the sum- and difference-histograms depend on two parameters: window size f and displacement step p. The four texture features yielding the best discrimination between classes are the mean, contrast, correlation and standard deviation. The f-p combinations 17-1, 17-2, 35-1 and 35-2 are those which give the best performance, with an average classification rate of 90%.

Effect of Duck Feet Gelatin Concentration on Physicochemical, Textural, and Sensory Properties of Duck Meat Jellies

PubMed Central

2014-01-01

This study was conducted to determine the effect of duck feet gelatin concentration on the physicochemical, textural and sensory properties of duck meat jellies. Duck feet gelatin was prepared with acidic swelling and hot water extraction. In this study, four duck meat jellies were formulated with 3, 4, 5, and 6% duck feet gelatin, respectively. In the preliminary experiment, the increase in duck feet gelatin ranged from 5 to 20%, resulting in a significant (p<0.001) increase in the color score, but a decline in the hardness and dispersibility satisfaction scores. An increase in the added amount of duck feet gelatin contributed to decreased lightness and increased protein content in duck meat jellies. Regarding the textural properties, increase in the added amount of duck feet gelatin highly correlated with the hardness in the center (p<0.01, R2=0.91), and edge (p<0.01, R2=0.89), of duck meat jellies. Meanwhile, the increase in duck feet gelatin decreased the score for textural satisfaction; duck meat jellies containing 6% duck feet gelatin had a significantly lower textural satisfaction score, than those containing 3% duck feet gelatin (p<0.05). Furthermore, a significant difference in the overall acceptance of duck meat jellies formulated with 5% duck feet gelatin was observed, as compared to those prepared with 3% duck feet gelatin. Therefore, this study suggested that duck feet gelatin is a useful ingredient for manufacturing cold-cut meat products. In consideration of the sensory acceptance, the optimal level of duck feet gelatin in duck meat jellies was determined to be 5%. PMID:26761181

Quantifying Urban Texture in Nairobi, Kenya and its Implications for Understanding Natural Hazard Impact

NASA Astrophysics Data System (ADS)

Taylor, Faith E.; Malamud, Bruce D.; Millington, James D. A.

2016-04-01

The configuration of infrastructure networks such as roads, drainage and power lines can both affect and be affected by natural hazards such as earthquakes, intense rain, wildfires and extreme temperatures. In this paper, we present and compare two methods to quantify urban topology on approximate scales of 0.0005 km2 to 10 km2 and create classifications of different 'urban textures' that relate to risk of natural hazard impact in an area. The methods we use focus on applicability in urban developing country settings, where access to high resolution and high quality data may be difficult. We use the city of Nairobi, Kenya to trial these methods. Nairobi has a population >3 million, and is a mix of informal settlements, residential and commercial development. The city and its immediate surroundings are subject to a variety of natural hazards such as floods, landslides, fires, drought, hail, heavy wind and extreme temperatures; all of these hazards can occur singly, but also have the potential for one to trigger another, thus providing a 'cascade' of hazards, or for two of the hazards to occur spatially and temporally near each other and interact. We use two measures of urban texture: (i) Street block textures, (ii) Google Earth land cover textures. Street block textures builds on the methodology of Louf and Barthelemy (2014) and uses Open Street Map data to analyse the shape, size, complexity and pattern of individual blocks of land created by fully enclosed loops of the major and minor road network of Nairobi. We find >4000 of these blocks ranging in size from approximately 0.0005 km2 to 10 km2, with approximately 5 classifications of urban texture. Google Earth land cover texture is a visual classification of homogeneous parcels of land performed in Google Earth using high-resolution airborne imagery and a qualitative criteria for each land cover type. Using the Google Earth land cover texture method, we identify >40 'urban textures' based on visual characteristics such as colour, texture, shadow and setting and have created a clear criteria for classifying an area based on its visual characteristics. These two methods for classifying urban texture in Nairobi are compared in a GIS and in the field to investigate whether there is a link between the visual appearance of an area and its network topology. From these urban textures, we may start to identify areas where (a) urban texture types may indicate a relative propensity to certain hazards and their interactions and (b) urban texture types that may increase or decrease the impact of a hazard that occurs in that area.

Content-based image retrieval for interstitial lung diseases using classification confidence

NASA Astrophysics Data System (ADS)

Dash, Jatindra Kumar; Mukhopadhyay, Sudipta; Prabhakar, Nidhi; Garg, Mandeep; Khandelwal, Niranjan

2013-02-01

Content Based Image Retrieval (CBIR) system could exploit the wealth of High-Resolution Computed Tomography (HRCT) data stored in the archive by finding similar images to assist radiologists for self learning and differential diagnosis of Interstitial Lung Diseases (ILDs). HRCT findings of ILDs are classified into several categories (e.g. consolidation, emphysema, ground glass, nodular etc.) based on their texture like appearances. Therefore, analysis of ILDs is considered as a texture analysis problem. Many approaches have been proposed for CBIR of lung images using texture as primitive visual content. This paper presents a new approach to CBIR for ILDs. The proposed approach makes use of a trained neural network (NN) to find the output class label of query image. The degree of confidence of the NN classifier is analyzed using Naive Bayes classifier that dynamically takes a decision on the size of the search space to be used for retrieval. The proposed approach is compared with three simple distance based and one classifier based texture retrieval approaches. Experimental results show that the proposed technique achieved highest average percentage precision of 92.60% with lowest standard deviation of 20.82%.

Texture Mixing via Universal Simulation

DTIC Science & Technology

2005-08-01

classes and universal simulation. Based on the well-known Lempel and Ziv (LZ) universal compression scheme, the universal type class of a one...length that produce the same tree (dictionary) under the Lempel - Ziv (LZ) incre- mental parsing defined in the well-known LZ78 universal compression ...the well known Lempel - Ziv parsing algorithm . The goal is not just to synthesize mixed textures, but to understand what texture is. We are currently

Investigations on femtosecond laser modified micro-textured surface with anti-friction property on bearing steel GCr15

NASA Astrophysics Data System (ADS)

Yang, Lijun; Ding, Ye; Cheng, Bai; He, Jiangtao; Wang, Genwang; Wang, Yang

2018-03-01

This work puts forward femtosecond laser modification of micro-textured surface on bearing steel GCr15 in order to reduce frictional wear and enhance load capacity during its application. Multi pulses femtosecond laser ablation experiments are established for the confirmation of laser spot radius as well as single pulse threshold fluence and pulse incubation coefficient of bulk material. Analytical models are set up in combination with hydrodynamics lubrication theory. Corresponding simulations are carried out on to explore influences of surface and cross sectional morphology of textures on hydrodynamics lubrication effect based on Navier-Stokes (N-S) equation. Technological experiments focus on the impacts of femtosecond laser machining variables, like scanning times, scanning velocity, pulse frequency and scanning gap on morphology of grooves as well as realization of optimized textures proposed by simulations, mechanisms of which are analyzed from multiple perspectives. Results of unidirectional rotating friction tests suggest that spherical texture with depth-to-width ratio of 0.2 can significantly improve tribological properties at low loading and velocity condition comparing with un-textured and other textured surfaces, which also verifies the accuracy of simulations and feasibility of femtosecond laser in modification of micro-textured surface.

Real-time volume rendering of 4D image using 3D texture mapping

NASA Astrophysics Data System (ADS)

Hwang, Jinwoo; Kim, June-Sic; Kim, Jae Seok; Kim, In Young; Kim, Sun Il

2001-05-01

Four dimensional image is 3D volume data that varies with time. It is used to express deforming or moving object in virtual surgery of 4D ultrasound. It is difficult to render 4D image by conventional ray-casting or shear-warp factorization methods because of their time-consuming rendering time or pre-processing stage whenever the volume data are changed. Even 3D texture mapping is used, repeated volume loading is also time-consuming in 4D image rendering. In this study, we propose a method to reduce data loading time using coherence between currently loaded volume and previously loaded volume in order to achieve real time rendering based on 3D texture mapping. Volume data are divided into small bricks and each brick being loaded is tested for similarity to one which was already loaded in memory. If the brick passed the test, it is defined as 3D texture by OpenGL functions. Later, the texture slices of the brick are mapped into polygons and blended by OpenGL blending functions. All bricks undergo this test. Continuously deforming fifty volumes are rendered in interactive time with SGI ONYX. Real-time volume rendering based on 3D texture mapping is currently available on PC.

Texture-Based Automated Lithological Classification Using Aeromagenetic Anomaly Images

USGS Publications Warehouse

Shankar, Vivek

2009-01-01

This report consists of a thesis submitted to the faculty of the Department of Electrical and Computer Engineering, in partial fulfillment of the requirements for the degree of Master of Science, Graduate College, The University of Arizona, 2004 Aeromagnetic anomaly images are geophysical prospecting tools frequently used in the exploration of metalliferous minerals and hydrocarbons. The amplitude and texture content of these images provide a wealth of information to geophysicists who attempt to delineate the nature of the Earth's upper crust. These images prove to be extremely useful in remote areas and locations where the minerals of interest are concealed by basin fill. Typically, geophysicists compile a suite of aeromagnetic anomaly images, derived from amplitude and texture measurement operations, in order to obtain a qualitative interpretation of the lithological (rock) structure. Texture measures have proven to be especially capable of capturing the magnetic anomaly signature of unique lithological units. We performed a quantitative study to explore the possibility of using texture measures as input to a machine vision system in order to achieve automated classification of lithological units. This work demonstrated a significant improvement in classification accuracy over random guessing based on a priori probabilities. Additionally, a quantitative comparison between the performances of five classes of texture measures in their ability to discriminate lithological units was achieved.

Decorating surfaces with bidirectional texture functions.

PubMed

Zhou, Kun; Du, Peng; Wang, Lifeng; Matsushita, Yasuyuki; Shi, Jiaoying; Guo, Baining; Shum, Heung-Yeung

2005-01-01

We present a system for decorating arbitrary surfaces with bidirectional texture functions (BTF). Our system generates BTFs in two steps. First, we automatically synthesize a BTF over the target surface from a given BTF sample. Then, we let the user interactively paint BTF patches onto the surface such that the painted patches seamlessly integrate with the background patterns. Our system is based on a patch-based texture synthesis approach known as quilting. We present a graphcut algorithm for BTF synthesis on surfaces and the algorithm works well for a wide variety of BTF samples, including those which present problems for existing algorithms. We also describe a graphcut texture painting algorithm for creating new surface imperfections (e.g., dirt, cracks, scratches) from existing imperfections found in input BTF samples. Using these algorithms, we can decorate surfaces with real-world textures that have spatially-variant reflectance, fine-scale geometry details, and surfaces imperfections. A particularly attractive feature of BTF painting is that it allows us to capture imperfections of real materials and paint them onto geometry models. We demonstrate the effectiveness of our system with examples.

Global ensemble texture representations are critical to rapid scene perception.

PubMed

Brady, Timothy F; Shafer-Skelton, Anna; Alvarez, George A

2017-06-01

Traditionally, recognizing the objects within a scene has been treated as a prerequisite to recognizing the scene itself. However, research now suggests that the ability to rapidly recognize visual scenes could be supported by global properties of the scene itself rather than the objects within the scene. Here, we argue for a particular instantiation of this view: That scenes are recognized by treating them as a global texture and processing the pattern of orientations and spatial frequencies across different areas of the scene without recognizing any objects. To test this model, we asked whether there is a link between how proficient individuals are at rapid scene perception and how proficiently they represent simple spatial patterns of orientation information (global ensemble texture). We find a significant and selective correlation between these tasks, suggesting a link between scene perception and spatial ensemble tasks but not nonspatial summary statistics In a second and third experiment, we additionally show that global ensemble texture information is not only associated with scene recognition, but that preserving only global ensemble texture information from scenes is sufficient to support rapid scene perception; however, preserving the same information is not sufficient for object recognition. Thus, global ensemble texture alone is sufficient to allow activation of scene representations but not object representations. Together, these results provide evidence for a view of scene recognition based on global ensemble texture rather than a view based purely on objects or on nonspatially localized global properties. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

An improved high order texture features extraction method with application to pathological diagnosis of colon lesions for CT colonography

NASA Astrophysics Data System (ADS)

Song, Bowen; Zhang, Guopeng; Lu, Hongbing; Wang, Huafeng; Han, Fangfang; Zhu, Wei; Liang, Zhengrong

2014-03-01

Differentiation of colon lesions according to underlying pathology, e.g., neoplastic and non-neoplastic, is of fundamental importance for patient management. Image intensity based textural features have been recognized as a useful biomarker for the differentiation task. In this paper, we introduce high order texture features, beyond the intensity, such as gradient and curvature, for that task. Based on the Haralick texture analysis method, we introduce a virtual pathological method to explore the utility of texture features from high order differentiations, i.e., gradient and curvature, of the image intensity distribution. The texture features were validated on database consisting of 148 colon lesions, of which 35 are non-neoplastic lesions, using the random forest classifier and the merit of area under the curve (AUC) of the receiver operating characteristics. The results show that after applying the high order features, the AUC was improved from 0.8069 to 0.8544 in differentiating non-neoplastic lesion from neoplastic ones, e.g., hyperplastic polyps from tubular adenomas, tubulovillous adenomas and adenocarcinomas. The experimental results demonstrated that texture features from the higher order images can significantly improve the classification accuracy in pathological differentiation of colorectal lesions. The gain in differentiation capability shall increase the potential of computed tomography (CT) colonography for colorectal cancer screening by not only detecting polyps but also classifying them from optimal polyp management for the best outcome in personalized medicine.

Deciphering the genetic control of fruit texture in apple by multiple family-based analysis and genome-wide association

PubMed Central

Di Guardo, Mario; Bink, Marco C.A.M.; Guerra, Walter; Letschka, Thomas; Lozano, Lidia; Busatto, Nicola; Poles, Lara; Tadiello, Alice; Bianco, Luca; Visser, Richard G.F.; van de Weg, Eric

2017-01-01

Abstract Fruit texture is a complex feature composed of mechanical and acoustic properties relying on the modifications occurring in the cell wall throughout fruit development and ripening. Apple is characterized by a large variation in fruit texture behavior that directly impacts both the consumer’s appreciation and post-harvest performance. To decipher the genetic control of fruit texture comprehensively, two complementing quantitative trait locus (QTL) mapping approaches were employed. The first was represented by a pedigree-based analysis (PBA) carried out on six full-sib pedigreed families, while the second was a genome-wide association study (GWAS) performed on a collection of 233 apple accessions. Both plant materials were genotyped with a 20K single nucleotide polymorphism (SNP) array and phenotyped with a sophisticated high-resolution texture analyzer. The overall QTL results indicated the fundamental role of chromosome 10 in controlling the mechanical properties, while chromosomes 2 and 14 were more associated with the acoustic response. The latter QTL, moreover, showed a consistent relationship between the QTL-estimated genotypes and the acoustic performance assessed among seedlings. The in silico annotation of these intervals revealed interesting candidate genes potentially involved in fruit texture regulation, as suggested by the gene expression profile. The joint integration of these approaches sheds light on the specific control of fruit texture, enabling important genetic information to assist in the selection of valuable fruit quality apple varieties. PMID:28338805

Deciphering the genetic control of fruit texture in apple by multiple family-based analysis and genome-wide association.

PubMed

Di Guardo, Mario; Bink, Marco C A M; Guerra, Walter; Letschka, Thomas; Lozano, Lidia; Busatto, Nicola; Poles, Lara; Tadiello, Alice; Bianco, Luca; Visser, Richard G F; van de Weg, Eric; Costa, Fabrizio

2017-03-01

Fruit texture is a complex feature composed of mechanical and acoustic properties relying on the modifications occurring in the cell wall throughout fruit development and ripening. Apple is characterized by a large variation in fruit texture behavior that directly impacts both the consumer's appreciation and post-harvest performance. To decipher the genetic control of fruit texture comprehensively, two complementing quantitative trait locus (QTL) mapping approaches were employed. The first was represented by a pedigree-based analysis (PBA) carried out on six full-sib pedigreed families, while the second was a genome-wide association study (GWAS) performed on a collection of 233 apple accessions. Both plant materials were genotyped with a 20K single nucleotide polymorphism (SNP) array and phenotyped with a sophisticated high-resolution texture analyzer. The overall QTL results indicated the fundamental role of chromosome 10 in controlling the mechanical properties, while chromosomes 2 and 14 were more associated with the acoustic response. The latter QTL, moreover, showed a consistent relationship between the QTL-estimated genotypes and the acoustic performance assessed among seedlings. The in silico annotation of these intervals revealed interesting candidate genes potentially involved in fruit texture regulation, as suggested by the gene expression profile. The joint integration of these approaches sheds light on the specific control of fruit texture, enabling important genetic information to assist in the selection of valuable fruit quality apple varieties. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Texture analysis on the fluence map to evaluate the degree of modulation for volumetric modulated arc therapy.

PubMed

Park, So-Yeon; Kim, Il Han; Ye, Sung-Joon; Carlson, Joel; Park, Jong Min

2014-11-01

Texture analysis on fluence maps was performed to evaluate the degree of modulation for volumetric modulated arc therapy (VMAT) plans. A total of six textural features including angular second moment, inverse difference moment, contrast, variance, correlation, and entropy were calculated for fluence maps generated from 20 prostate and 20 head and neck VMAT plans. For each of the textural features, particular displacement distances (d) of 1, 5, and 10 were adopted. To investigate the deliverability of each VMAT plan, gamma passing rates of pretreatment quality assurance, and differences in modulating parameters such as multileaf collimator (MLC) positions, gantry angles, and monitor units at each control point between VMAT plans and dynamic log files registered by the Linac control system during delivery were acquired. Furthermore, differences between the original VMAT plan and the plan reconstructed from the dynamic log files were also investigated. To test the performance of the textural features as indicators for the modulation degree of VMAT plans, Spearman's rank correlation coefficients (rs) with the plan deliverability were calculated. For comparison purposes, conventional modulation indices for VMAT including the modulation complexity score for VMAT, leaf travel modulation complexity score, and modulation index supporting station parameter optimized radiation therapy (MISPORT) were calculated, and their correlations were analyzed in the same way. There was no particular textural feature which always showed superior correlations with every type of plan deliverability. Considering the results comprehensively, contrast (d = 1) and variance (d = 1) generally showed considerable correlations with every type of plan deliverability. These textural features always showed higher correlations to the plan deliverability than did the conventional modulation indices, except in the case of modulating parameter differences. The rs values of contrast to the global gamma passing rates with criteria of 2%/2 mm, 2%/1 mm, and 1%/2 mm were 0.536, 0.473, and 0.718, respectively. The respective values for variance were 0.551, 0.481, and 0.688. In the case of local gamma passing rates, the rs values of contrast were 0.547, 0.578, and 0.620, respectively, and those of variance were 0.519, 0.527, and 0.569. All of the rs values in those cases were statistically significant (p < 0.003). In the cases of global and local gamma passing rates, MISPORT showed the highest correlations among the conventional modulation indices. For global passing rates, rs values of MISPORT were -0.420, -0.330, and -0.632, respectively, and those for local passing rates were -0.455, -0.490 and -0.502. The values of rs of contrast, variance, and MISPORT with the MLC errors were -0.863, -0.828, and 0.795, respectively, all with statistical significances (p < 0.001). The correlations with statistical significances between variance and dose-volumetric differences were observed more frequently than the others. The contrast (d = 1) and variance (d = 1) calculated from fluence maps of VMAT plans showed considerable correlations with the plan deliverability, indicating their potential use as indicators for assessing the degree of modulation of VMAT plans. Both contrast and variance consistently showed better performance than the conventional modulation indices for VMAT.

High Performance of PEDOT:PSS/n-Si Solar Cells Based on Textured Surface with AgNWs Electrodes

NASA Astrophysics Data System (ADS)

Jiang, Xiangyu; Zhang, Pengbo; Zhang, Juan; Wang, Jilei; Li, Gaofei; Fang, Xiaohong; Yang, Liyou; Chen, Xiaoyuan

2018-02-01

Hybrid heterojunction solar cells (HHSCs) have gained extensive research and attention due to simple device structure and low-cost technological processes. Here, HHSCs are presented based on a highly transparent conductive polymer poly(3,4ethylenedioxythiophene):poly(styrenesulfonate)(PEDOT:PSS) directly spin-coated on an n-type crystalline silicon with microscale surface textures, which are prepared by traditional chemical etching. We have studied interface properties between PEDOT:PSS and textured n-Si by varying coating conditions. Final power conversion efficiency (PCE) could arrive at 8.54% by these simple solution-based fabrication processes. The high conversion efficiency is attributed to the fully conformal contact between PEDOT:PSS film and textured silicon. Furthermore, the reflectance of the PEDOT:PSS layer on textured surface is analyzed by changing film thickness. In order to improve the performance of the device, silver nanowires were employed as electrodes because of its better optical transmittance and electrical conductivity. The highest PCE of 11.07% was achieved which displayed a 29.6% enhancement compared with traditional silver electrodes. These findings imply that the combination of PEDOT:PSS film and silver nanowire transparent electrodes pave a promising way for realizing high-efficiency and low-cost solar cells.

High Performance of PEDOT:PSS/n-Si Solar Cells Based on Textured Surface with AgNWs Electrodes.

PubMed

Jiang, Xiangyu; Zhang, Pengbo; Zhang, Juan; Wang, Jilei; Li, Gaofei; Fang, Xiaohong; Yang, Liyou; Chen, Xiaoyuan

2018-02-14

Hybrid heterojunction solar cells (HHSCs) have gained extensive research and attention due to simple device structure and low-cost technological processes. Here, HHSCs are presented based on a highly transparent conductive polymer poly(3,4ethylenedioxythiophene):poly(styrenesulfonate)(PEDOT:PSS) directly spin-coated on an n-type crystalline silicon with microscale surface textures, which are prepared by traditional chemical etching. We have studied interface properties between PEDOT:PSS and textured n-Si by varying coating conditions. Final power conversion efficiency (PCE) could arrive at 8.54% by these simple solution-based fabrication processes. The high conversion efficiency is attributed to the fully conformal contact between PEDOT:PSS film and textured silicon. Furthermore, the reflectance of the PEDOT:PSS layer on textured surface is analyzed by changing film thickness. In order to improve the performance of the device, silver nanowires were employed as electrodes because of its better optical transmittance and electrical conductivity. The highest PCE of 11.07% was achieved which displayed a 29.6% enhancement compared with traditional silver electrodes. These findings imply that the combination of PEDOT:PSS film and silver nanowire transparent electrodes pave a promising way for realizing high-efficiency and low-cost solar cells.

Efficient optical analysis of surface texture combinations for silicon solar cells

NASA Astrophysics Data System (ADS)

Tucher, Nico; Eisenlohr, Johannes; Kiefel, Peter; Gebrewold, Habtamu; Höhn, Oliver; Hauser, Hubert; Müller, Claas; Goldschmidt, Jan Christoph; Bläsi, Benedikt

2016-04-01

Surface textures can significantly improve anti-reflective and light trapping properties of silicon solar cells. Combining standard pyramidal front side textures with scattering or diffractive rear side textures has the potential to further increase the light path length inside the silicon and thereby increase the solar cell efficiency. In this work we introduce the OPTOS (Optical Properties of Textured Optical Sheets) simulation formalism and apply it to the modelling of silicon solar cells with different surface textures at front and rear side. OPTOS is a matrix-based method that allows for the computationally-efficient calculation of non-coherent light propagation within textured solar cells, featuring multiple textures that may operate in different optical regimes. After calculating redistribution matrices for each individual surface texture with the most appropriate technique, optical properties like angle dependent reflectance, transmittance or absorptance can be determined via matrix multiplications. Using OPTOS, we demonstrate for example that the integration of a diffractive grating at the rear side of solar cells with random pyramids at the front results in an absorptance gain that corresponds to a photocurrent density enhancement of 0.73 mA/cm2 for a 250 μm thick cell. The re-usability of matrices enables the investigation of different solar cell thicknesses within minutes. For thicknesses down to 50 μm the simulated gain increases up to 1.22 mA/cm2. The OPTOS formalism is furthermore not restricted with respect to the number of textured interfaces. By combining two or more textured sheets to effective interfaces, it is possible to optically model a complete photovoltaic module including EVA and potentially textured glass layers with one calculation tool.

Utilizing management zones for Rotylenchulus reniformis in Cotton: Effects on nematode levels, crop damage, and Pasteuria sp.

USDA-ARS?s Scientific Manuscript database

The effect of soil texture on nematode levels is the primary basis for site-specific nematode management. Management zones (MZs) are sampled independently and decisions are based on those sample results. MZs based on soil electrical conductivity (EC, a proxy for soil texture) have not been tested ...

Texture based segmentation method to detect atherosclerotic plaque from optical tomography images

NASA Astrophysics Data System (ADS)

Prakash, Ammu; Hewko, Mark; Sowa, Michael; Sherif, Sherif

2013-06-01

Optical coherence tomography (OCT) imaging has been widely employed in assessing cardiovascular disease. Atherosclerosis is one of the major cause cardio vascular diseases. However visual detection of atherosclerotic plaque from OCT images is often limited and further complicated by high frame rates. We developed a texture based segmentation method to automatically detect plaque and non plaque regions from OCT images. To verify our results we compared them to photographs of the vascular tissue with atherosclerotic plaque that we used to generate the OCT images. Our results show a close match with photographs of vascular tissue with atherosclerotic plaque. Our texture based segmentation method for plaque detection could be potentially used in clinical cardiovascular OCT imaging for plaque detection.

Textures and compositions of cobalt pentlandite and cobaltian mackinawite from the Madan-Kudan copper deposit, Khetri Copper Belt, Rajasthan, India

NASA Astrophysics Data System (ADS)

Baidya, Abu Saeed; Sen, Atlanta; Pal, Dipak C.

2018-06-01

The Khetri Copper Belt (KCB), a part of the Proterozoic Delhi-Aravalli fold belt in western India, hosts several Cu deposits, which are known to contain considerable Au, Ag, Co and Ni. Although many Co-bearing phases have been reported from the KCB and adjacent areas, detailed textural and geochemical data are either unavailable or scant except for mackinawite. In this study, we describe the textures and compositions (determined by EPMA) of two very rare Co-rich phases, namely cobaltian mackinawite (containing up to 12.68 wt.% Co, 1.90 wt.% Ni and 2.52 wt.% Cu) and cobalt-pentlandite (containing up to 49.30 wt.% Co and 10.19 wt.% Ni), identified based on composition, from the Madan-Kudan deposit. To the best of our knowledge, neither cobalt-pentlandite nor such highly Co-rich mackinawite have previously been reported from this area. The common sulphide minerals viz. chalcopyrite, pyrrhotite and rare pyrite occur in chalcopyrite-pyrrhotite ± pyrite-magnetite-chlorite-blue amphibole (Cl-rich hastingsite-pargasite-sadanagaite) ± marialitic scapolite ± allanite ± uraninite veins in amphibole-bearing feldspathic quartzite and garnetiferous chlorite schist. Cobaltian mackinawite is invariably associated with chalcopyrite and occurs as exsolution and inclusion within chalcopyrite or outside, but at the contact of chalcopyrite. On the other hand, cobalt-pentlandite is invariably associated with pyrrhotite and shows similar textural relation with pyrrhotite as that of mackinawite with chalcopyrite. Mineralogically diverse undeformed sulphide veins comprising Cl-rich amphibole and locally Cl-rich marialitic scapolite suggests epigenetic hydrothermal mineralization involving Cl-rich saline fluid in the Madan-Kudan deposit. Transport of metals, derived from a mafic source rock with high intrinsic Ni:Co ratio, by Cl-rich fluid can suitably explain the high Co:Ni ratio of the studied ore minerals. Presence of such highly Co-rich phases and other circumstantial evidences, enumerated in this work, are consistent with variants of Fe oxide (-Cu-Au) (IOCG) style mineralization, at least for some stages of mineralization in the Madan-Kudan deposit.

Automatic Texture Mapping of Architectural and Archaeological 3d Models

NASA Astrophysics Data System (ADS)

Kersten, T. P.; Stallmann, D.

2012-07-01

Today, detailed, complete and exact 3D models with photo-realistic textures are increasingly demanded for numerous applications in architecture and archaeology. Manual texture mapping of 3D models by digital photographs with software packages, such as Maxon Cinema 4D, Autodesk 3Ds Max or Maya, still requires a complex and time-consuming workflow. So, procedures for automatic texture mapping of 3D models are in demand. In this paper two automatic procedures are presented. The first procedure generates 3D surface models with textures by web services, while the second procedure textures already existing 3D models with the software tmapper. The program tmapper is based on the Multi Layer 3D image (ML3DImage) algorithm and developed in the programming language C++. The studies showing that the visibility analysis using the ML3DImage algorithm is not sufficient to obtain acceptable results of automatic texture mapping. To overcome the visibility problem the Point Cloud Painter algorithm in combination with the Z-buffer-procedure will be applied in the future.

Associations Between PET Textural Features and GLUT1 Expression, and the Prognostic Significance of Textural Features in Lung Adenocarcinoma.

PubMed

Koh, Young Wha; Park, Seong Yong; Hyun, Seung Hyup; Lee, Su Jin

2018-02-01

We evaluated the association between positron emission tomography (PET) textural features and glucose transporter 1 (GLUT1) expression level and further investigated the prognostic significance of textural features in lung adenocarcinoma. We evaluated 105 adenocarcinoma patients. We extracted texture-based PET parameters of primary tumors. Conventional PET parameters were also measured. The relationships between PET parameters and GLUT1 expression levels were evaluated. The association between PET parameters and overall survival (OS) was assessed using Cox's proportional hazard regression models. In terms of PET textural features, tumors expressing high levels of GLUT1 exhibited significantly lower coarseness, contrast, complexity, and strength, but significantly higher busyness. On univariate analysis, the metabolic tumor volume, total lesion glycolysis, contrast, busyness, complexity, and strength were significant predictors of OS. Multivariate analysis showed that lower complexity (HR=2.017, 95%CI=1.032-3.942, p=0.040) was independently associated with poorer survival. PET textural features may aid risk stratification in lung adenocarcinoma patients. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Soil erosion model predictions using parent material/soil texture-based parameters compared to using site-specific parameters

Treesearch

R. B. Foltz; W. J. Elliot; N. S. Wagenbrenner

2011-01-01

Forested areas disturbed by access roads produce large amounts of sediment. One method to predict erosion and, hence, manage forest roads is the use of physically based soil erosion models. A perceived advantage of a physically based model is that it can be parameterized at one location and applied at another location with similar soil texture or geological parent...

New decision support tool for acute lymphoblastic leukemia classification

NASA Astrophysics Data System (ADS)

Madhukar, Monica; Agaian, Sos; Chronopoulos, Anthony T.

2012-03-01

In this paper, we build up a new decision support tool to improve treatment intensity choice in childhood ALL. The developed system includes different methods to accurately measure furthermore cell properties in microscope blood film images. The blood images are exposed to series of pre-processing steps which include color correlation, and contrast enhancement. By performing K-means clustering on the resultant images, the nuclei of the cells under consideration are obtained. Shape features and texture features are then extracted for classification. The system is further tested on the classification of spectra measured from the cell nuclei in blood samples in order to distinguish normal cells from those affected by Acute Lymphoblastic Leukemia. The results show that the proposed system robustly segments and classifies acute lymphoblastic leukemia based on complete microscopic blood images.

Paleoarchean trace fossils in altered volcanic glass.

PubMed

Staudigel, Hubert; Furnes, Harald; DeWit, Maarten

2015-06-02

Microbial corrosion textures in volcanic glass from Cenozoic seafloor basalts and the corresponding titanite replacement microtextures in metamorphosed Paleoarchean pillow lavas have been interpreted as evidence for a deep biosphere dating back in time through the earliest periods of preserved life on earth. This interpretation has been recently challenged for Paleoarchean titanite replacement textures based on textural and geochronological data from pillow lavas in the Hooggenoeg Complex of the Barberton Greenstone Belt in South Africa. We use this controversy to explore the strengths and weaknesses of arguments made in support or rejection of the biogenicity interpretation of bioalteration trace fossils in Cenozoic basalt glasses and their putative equivalents in Paleoarchean greenstones. Our analysis suggests that biogenicity cannot be taken for granted for all titanite-based textures in metamorphosed basalt glass, but a cautious and critical evaluation of evidence suggests that biogenicity remains the most likely interpretation for previously described titanite microtextures in Paleoarchean pillow lavas.

BRAIN TUMOR SEGMENTATION WITH SYMMETRIC TEXTURE AND SYMMETRIC INTENSITY-BASED DECISION FORESTS.

PubMed

Bianchi, Anthony; Miller, James V; Tan, Ek Tsoon; Montillo, Albert

2013-04-01

Accurate automated segmentation of brain tumors in MR images is challenging due to overlapping tissue intensity distributions and amorphous tumor shape. However, a clinically viable solution providing precise quantification of tumor and edema volume would enable better pre-operative planning, treatment monitoring and drug development. Our contributions are threefold. First, we design efficient gradient and LBPTOP based texture features which improve classification accuracy over standard intensity features. Second, we extend our texture and intensity features to symmetric texture and symmetric intensity which further improve the accuracy for all tissue classes. Third, we demonstrate further accuracy enhancement by extending our long range features from 100mm to a full 200mm. We assess our brain segmentation technique on 20 patients in the BraTS 2012 dataset. Impact from each contribution is measured and the combination of all the features is shown to yield state-of-the-art accuracy and speed.

Paleoarchean trace fossils in altered volcanic glass

PubMed Central

Staudigel, Hubert; Furnes, Harald; DeWit, Maarten

2015-01-01

Microbial corrosion textures in volcanic glass from Cenozoic seafloor basalts and the corresponding titanite replacement microtextures in metamorphosed Paleoarchean pillow lavas have been interpreted as evidence for a deep biosphere dating back in time through the earliest periods of preserved life on earth. This interpretation has been recently challenged for Paleoarchean titanite replacement textures based on textural and geochronological data from pillow lavas in the Hooggenoeg Complex of the Barberton Greenstone Belt in South Africa. We use this controversy to explore the strengths and weaknesses of arguments made in support or rejection of the biogenicity interpretation of bioalteration trace fossils in Cenozoic basalt glasses and their putative equivalents in Paleoarchean greenstones. Our analysis suggests that biogenicity cannot be taken for granted for all titanite-based textures in metamorphosed basalt glass, but a cautious and critical evaluation of evidence suggests that biogenicity remains the most likely interpretation for previously described titanite microtextures in Paleoarchean pillow lavas. PMID:26038543

Evidence for Subsolidus Metasomatism in the Eucrite Parent Body

NASA Technical Reports Server (NTRS)

McCallum, I. Stewart; Schwartz, Jeffrey M.; Mullen, Emily K.

2004-01-01

The eucrite parent body (4Vesta) was continuously and rapidy resurfaced by basaltic lavas that formed the non-cumulate eucrites. Ophitic and variolitic textures have been preserved even though eucrites exhibit varying degrees of equilibration based on the extent of thermal metamorphism. Types range from least metamorphosed (type 1) to most metamorphosed (type 7) based in part on the interpretation of textures and compositional zoning profiles within pigeonitic pyroxenes. To provide constraints on the source and duration of the heating event responsible for metamorphism we have investigated primary and secondary textural and compositional relations in noncumulate eucrites with emphasis on subsolidus textures developed in pyroxenes. We have studied examples of most metamorphic types including Pasamonte (type 2) Stannern (4), Nuevo Laredo (4), Juvinas (5), Lakangaon (5), Millbillillie (6), Palo Blanco Creek (7), Jonzac (7), Haraiya (7), along with the cumulate eucrites Moama and Moore County.

Classification of endoscopic capsule images by using color wavelet features, higher order statistics and radial basis functions.

PubMed

Lima, C S; Barbosa, D; Ramos, J; Tavares, A; Monteiro, L; Carvalho, L

2008-01-01

This paper presents a system to support medical diagnosis and detection of abnormal lesions by processing capsule endoscopic images. Endoscopic images possess rich information expressed by texture. Texture information can be efficiently extracted from medium scales of the wavelet transform. The set of features proposed in this paper to code textural information is named color wavelet covariance (CWC). CWC coefficients are based on the covariances of second order textural measures, an optimum subset of them is proposed. Third and forth order moments are added to cope with distributions that tend to become non-Gaussian, especially in some pathological cases. The proposed approach is supported by a classifier based on radial basis functions procedure for the characterization of the image regions along the video frames. The whole methodology has been applied on real data containing 6 full endoscopic exams and reached 95% specificity and 93% sensitivity.

Identifying prognostic intratumor heterogeneity using pre- and post-radiotherapy 18F-FDG PET images for pancreatic cancer patients.

PubMed

Yue, Yong; Osipov, Arsen; Fraass, Benedick; Sandler, Howard; Zhang, Xiao; Nissen, Nicholas; Hendifar, Andrew; Tuli, Richard

2017-02-01

To stratify risks of pancreatic adenocarcinoma (PA) patients using pre- and post-radiotherapy (RT) PET/CT images, and to assess the prognostic value of texture variations in predicting therapy response of patients. Twenty-six PA patients treated with RT from 2011-2013 with pre- and post-treatment 18F-FDG-PET/CT scans were identified. Tumor locoregional texture was calculated using 3D kernel-based approach, and texture variations were identified by fitting discrepancies of texture maps of pre- and post-treatment images. A total of 48 texture and clinical variables were identified and evaluated for association with overall survival (OS). The prognostic heterogeneity features were selected using lasso/elastic net regression, and further were evaluated by multivariate Cox analysis. Median age was 69 y (range, 46-86 y). The texture map and temporal variations between pre- and post-treatment were well characterized by histograms and statistical fitting. The lasso analysis identified seven predictors (age, node stage, post-RT SUVmax, variations of homogeneity, variance, sum mean, and cluster tendency). The multivariate Cox analysis identified five significant variables: age, node stage, variations of homogeneity, variance, and cluster tendency (with P=0.020, 0.040, 0.065, 0.078, and 0.081, respectively). The patients were stratified into two groups based on the risk score of multivariate analysis with log-rank P=0.001: a low risk group (n=11) with a longer mean OS (29.3 months) and higher texture variation (>30%), and a high risk group (n=15) with a shorter mean OS (17.7 months) and lower texture variation (<15%). Locoregional metabolic texture response provides a feasible approach for evaluating and predicting clinical outcomes following treatment of PA with RT. The proposed method can be used to stratify patient risk and help select appropriate treatment strategies for individual patients toward implementing response-driven adaptive RT.

Investigation into the Effects of Textural Properties on Cuttability Performance of a Chisel Tool

NASA Astrophysics Data System (ADS)

Tumac, Deniz; Copur, Hanifi; Balci, Cemal; Er, Selman; Avunduk, Emre

2018-04-01

The main objective of this study is to investigate the effect of textural properties of stones on cutting performance of a standard chisel tool. Therewithal, the relationships between textural properties and cutting performance parameters and physical and mechanical properties were statistically analyzed. For this purpose, physical and mechanical property tests and mineralogical and petrographic analyses were carried out on eighteen natural stone samples, which can be grouped into three fundamentally different geological origins, i.e., metamorphic, igneous, and sedimentary. Then, texture coefficient analyses were performed on the samples. To determine the cuttability of the stones; the samples were cut with a portable linear cutting machine using a standard chisel tool at different depths of cut in unrelieved (non-interactive) cutting mode. The average and maximum forces (normal and cutting) and specific energy were measured, and the obtained values were correlated with texture coefficient, packing weighting, and grain size. With reference to the relation between depth of cut and cutting performance of the chisel tool for three types of natural stone groups, specific energy decreases with increasing depth of cut, and cutting forces increase in proportion to the depth of cut. The same is observed for the relationship between packing weighting and both of specific energy and cutter forces. On the other hand, specific energy and the forces decrease while grain size increases. Based on the findings of the present study, texture coefficient has strong correlation with specific energy. Generally, the lower depth of cut values in cutting tests shows higher and more reliable correlations with texture coefficient than the increased depth of cut. The results of cutting tests show also that, at a lower depth of cut (less than 1.5 mm), even stronger correlations can be observed between texture coefficient and cutting performance. Experimental studies indicate that cutting performance of chisel tools can be predicted based on texture coefficients of the natural stones.

Material quality assessment of silk nanofibers based on swarm intelligence

NASA Astrophysics Data System (ADS)

Brandoli Machado, Bruno; Nunes Gonçalves, Wesley; Martinez Bruno, Odemir

2013-02-01

In this paper, we propose a novel approach for texture analysis based on artificial crawler model. Our method assumes that each agent can interact with the environment and each other. The evolution process converges to an equilibrium state according to the set of rules. For each textured image, the feature vector is composed by signatures of the live agents curve at each time. Experimental results revealed that combining the minimum and maximum signatures into one increase the classification rate. In addition, we pioneer the use of autonomous agents for characterizing silk fibroin scaffolds. The results strongly suggest that our approach can be successfully employed for texture analysis.

Parametric classification of handvein patterns based on texture features

NASA Astrophysics Data System (ADS)

Al Mahafzah, Harbi; Imran, Mohammad; Supreetha Gowda H., D.

2018-04-01

In this paper, we have developed Biometric recognition system adopting hand based modality Handvein,which has the unique pattern for each individual and it is impossible to counterfeit and fabricate as it is an internal feature. We have opted in choosing feature extraction algorithms such as LBP-visual descriptor, LPQ-blur insensitive texture operator, Log-Gabor-Texture descriptor. We have chosen well known classifiers such as KNN and SVM for classification. We have experimented and tabulated results of single algorithm recognition rate for Handvein under different distance measures and kernel options. The feature level fusion is carried out which increased the performance level.

Graph run-length matrices for histopathological image segmentation.

PubMed

Tosun, Akif Burak; Gunduz-Demir, Cigdem

2011-03-01

The histopathological examination of tissue specimens is essential for cancer diagnosis and grading. However, this examination is subject to a considerable amount of observer variability as it mainly relies on visual interpretation of pathologists. To alleviate this problem, it is very important to develop computational quantitative tools, for which image segmentation constitutes the core step. In this paper, we introduce an effective and robust algorithm for the segmentation of histopathological tissue images. This algorithm incorporates the background knowledge of the tissue organization into segmentation. For this purpose, it quantifies spatial relations of cytological tissue components by constructing a graph and uses this graph to define new texture features for image segmentation. This new texture definition makes use of the idea of gray-level run-length matrices. However, it considers the runs of cytological components on a graph to form a matrix, instead of considering the runs of pixel intensities. Working with colon tissue images, our experiments demonstrate that the texture features extracted from "graph run-length matrices" lead to high segmentation accuracies, also providing a reasonable number of segmented regions. Compared with four other segmentation algorithms, the results show that the proposed algorithm is more effective in histopathological image segmentation.

Environmental perturbations can be detected through microwear texture analysis in two platyrrhine species from Brazilian Amazonia.

PubMed

Estalrrich, Almudena; Young, Mariel B; Teaford, Mark F; Ungar, Peter S

2015-11-01

Recent dental microwear studies have shown that fossil species differ from one another in texture attributes-both in terms of central tendency and dispersion. Most comparative studies used to interpret these results have relied on poorly provenienced museum samples that are not well-suited to consideration of within species variation in diet. Here we present a study of two species of platyrrhine monkeys, Alouatta belzebul (n = 60) and Sapajus apella (n = 28) from Pará State in the Brazilian Amazon in order to assess effects of habitat variation on microwear (each species was sampled from forests that differ in the degree of disturbance from highly disturbed to minimally disturbed). Results indicate that microwear texture values vary between habitats-more for the capuchins than the howler monkeys. This is consistent with the notion that diets of the more folivorous A. belzebul are less affected by habitat disturbance than those of the more frugivorous S. apella. It also suggests that microwear holds the potential to reflect comparatively subtle differences in within-species variation in fossil taxa if sample size and control over paleohabitat allow. © 2015 Wiley Periodicals, Inc.

Magnetization measurements reveal the local shear stiffness of hydrogels probed by ferromagnetic nanorods

NASA Astrophysics Data System (ADS)

Bender, P.; Tschöpe, A.; Birringer, R.

2014-12-01

The local mechanical coupling of ferromagnetic nanorods in hydrogels was characterized by magnetization measurements. Nickel nanorods were synthesized by the AAO-template method and embedded in gelatine hydrogels with mechanically soft or hard matrix properties determined by the gelatine weight fraction. By applying a homogeneous magnetic field during gelation the nanorods were aligned along the field resulting in uniaxially textured ferrogels. The magnetization curves of the soft ferrogel exhibited not only important similarities but also characteristic differences as compared to the hard ferrogel. The hystereses measured in a field parallel to the texture axis were almost identical for both samples indicating effective coupling of the nanorods with the polymer network. By contrast, measurements in a magnetic field perpendicular to the texture axis revealed a much higher initial susceptibility of the soft as compared to the hard ferrogel. This difference was attributed to the additional rotation of the nanorods allowed by the reduced shear modulus in the soft ferrogel matrix. Two methods for data analysis were presented which enabled us to determine the shear modulus of the gelatine matrix which was interpreted as a local rather than macroscopic quantity in consideration of the nanoscale of the probe particles.

Passive pavement-mounted acoustical linguistic drive alert system and method

DOEpatents

Kisner, Roger A.; Anderson, Richard L.; Carnal, Charles L.; Hylton, James O.; Stevens, Samuel S.

2001-01-01

Systems and methods are described for passive pavement-mounted acoustical alert of the occupants of a vehicle. A method of notifying a vehicle occupant includes providing a driving medium upon which a vehicle is to be driven; and texturing a portion of the driving medium such that the textured portion interacts with the vehicle to produce audible signals, the textured portion pattern such that a linguistic message is encoded into the audible signals. The systems and methods provide advantages because information can be conveyed to the occupants of the vehicle based on the location of the vehicle relative to the textured surface.

Texture analysis of pulmonary parenchyma in normal and emphysematous lung

NASA Astrophysics Data System (ADS)

Uppaluri, Renuka; Mitsa, Theophano; Hoffman, Eric A.; McLennan, Geoffrey; Sonka, Milan

1996-04-01

Tissue characterization using texture analysis is gaining increasing importance in medical imaging. We present a completely automated method for discriminating between normal and emphysematous regions from CT images. This method involves extracting seventeen features which are based on statistical, hybrid and fractal texture models. The best subset of features is derived from the training set using the divergence technique. A minimum distance classifier is used to classify the samples into one of the two classes--normal and emphysema. Sensitivity and specificity and accuracy values achieved were 80% or greater in most cases proving that texture analysis holds great promise in identifying emphysema.

Cortical mechanisms for the segregation and representation of acoustic textures.

PubMed

Overath, Tobias; Kumar, Sukhbinder; Stewart, Lauren; von Kriegstein, Katharina; Cusack, Rhodri; Rees, Adrian; Griffiths, Timothy D

2010-02-10

Auditory object analysis requires two fundamental perceptual processes: the definition of the boundaries between objects, and the abstraction and maintenance of an object's characteristic features. Although it is intuitive to assume that the detection of the discontinuities at an object's boundaries precedes the subsequent precise representation of the object, the specific underlying cortical mechanisms for segregating and representing auditory objects within the auditory scene are unknown. We investigated the cortical bases of these two processes for one type of auditory object, an "acoustic texture," composed of multiple frequency-modulated ramps. In these stimuli, we independently manipulated the statistical rules governing (1) the frequency-time space within individual textures (comprising ramps with a given spectrotemporal coherence) and (2) the boundaries between textures (adjacent textures with different spectrotemporal coherences). Using functional magnetic resonance imaging, we show mechanisms defining boundaries between textures with different coherences in primary and association auditory cortices, whereas texture coherence is represented only in association cortex. Furthermore, participants' superior detection of boundaries across which texture coherence increased (as opposed to decreased) was reflected in a greater neural response in auditory association cortex at these boundaries. The results suggest a hierarchical mechanism for processing acoustic textures that is relevant to auditory object analysis: boundaries between objects are first detected as a change in statistical rules over frequency-time space, before a representation that corresponds to the characteristics of the perceived object is formed.

Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization.

PubMed

Molina, David; Pérez-Beteta, Julián; Martínez-González, Alicia; Martino, Juan; Velasquez, Carlos; Arana, Estanislao; Pérez-García, Víctor M

2017-01-01

Textural measures have been widely explored as imaging biomarkers in cancer. However, their robustness under dynamic range and spatial resolution changes in brain 3D magnetic resonance images (MRI) has not been assessed. The aim of this work was to study potential variations of textural measures due to changes in MRI protocols. Twenty patients harboring glioblastoma with pretreatment 3D T1-weighted MRIs were included in the study. Four different spatial resolution combinations and three dynamic ranges were studied for each patient. Sixteen three-dimensional textural heterogeneity measures were computed for each patient and configuration including co-occurrence matrices (CM) features and run-length matrices (RLM) features. The coefficient of variation was used to assess the robustness of the measures in two series of experiments corresponding to (i) changing the dynamic range and (ii) changing the matrix size. No textural measures were robust under dynamic range changes. Entropy was the only textural feature robust under spatial resolution changes (coefficient of variation under 10% in all cases). Textural measures of three-dimensional brain tumor images are not robust neither under dynamic range nor under matrix size changes. Standards should be harmonized to use textural features as imaging biomarkers in radiomic-based studies. The implications of this work go beyond the specific tumor type studied here and pose the need for standardization in textural feature calculation of oncological images.

Objective and quantitative definitions of modified food textures based on sensory and rheological methodology

PubMed Central

Wendin, Karin; Ekman, Susanne; Bülow, Margareta; Ekberg, Olle; Johansson, Daniel; Rothenberg, Elisabet; Stading, Mats

2010-01-01

Introduction Patients who suffer from chewing and swallowing disorders, i.e. dysphagia, may have difficulties ingesting normal food and liquids. In these patients a texture modified diet may enable that the patient maintain adequate nutrition. However, there is no generally accepted definition of ‘texture’ that includes measurements describing different food textures. Objective Objectively define and quantify categories of texture-modified food by conducting rheological measurements and sensory analyses. A further objective was to facilitate the communication and recommendations of appropriate food textures for patients with dysphagia. Design About 15 food samples varying in texture qualities were characterized by descriptive sensory and rheological measurements. Results Soups were perceived as homogenous; thickened soups were perceived as being easier to swallow, more melting and creamy compared with soups without thickener. Viscosity differed between the two types of soups. Texture descriptors for pâtés were characterized by high chewing resistance, firmness, and having larger particles compared with timbales and jellied products. Jellied products were perceived as wobbly, creamy, and easier to swallow. Concerning the rheological measurements, all solid products were more elastic than viscous (G′>G″), belonging to different G′ intervals: jellied products (low G′) and timbales together with pâtés (higher G′). Conclusion By combining sensory and rheological measurements, a system of objective, quantitative, and well-defined food textures was developed that characterizes the different texture categories. PMID:20592965

Enhanced texture evolution and piezoelectric properties in CuO-doped Pb(In1/2Nb1/2)O3-Pb(Mg1/3Nb2/3)O3-PbTiO3 grain-oriented ceramics

NASA Astrophysics Data System (ADS)

Chang, Yunfei; Watson, Beecher; Fanton, Mark; Meyer, Richard J.; Messing, Gary L.

2017-12-01

In this work, both crystallographic texture and doping engineering strategies were integrated to develop relaxor-PbTiO3 (PT) based ternary ferroelectric ceramics with enhanced texture evolution and superior electromechanical properties. CuO-doped Pb(In1/2Nb1/2)O3-Pb(Mg1/3Nb2/3)O3-PbTiO3 (PIN-PMN-PT) piezoelectric ceramics with [001]c texture fraction ≥97% were synthesized by templated grain growth. The addition of CuO significantly promotes densification and oriented grain growth in the templated ceramics, leading to full texture development at dramatically reduced times and temperatures. Moreover, the CuO dopant remarkably enhances the piezoelectric properties of the textured ceramics while maintaining high phase transition temperatures and large coercive fields. Doping 0.125 wt. % CuO yields the electromechanical properties of d33 = 927 pC/N, d33* = 1510 pm/V, g33 = 43.2 × 10-3 Vm/N, Kp = 0.87, Ec=8.8 kV/cm, and tan δ = 1.3%, which are the best values reported so far in PIN-PMN-PT based ceramics. The high piezoelectric coefficient is mainly from the reversible piezoelectric response, with the irreversible contribution being on the order of 13.1%. We believe that this work not only facilitates closing the performance gap between ceramics and single crystals but also can expand relaxor-PT based piezoelectric application fields.

Time-Frequency Feature Representation Using Multi-Resolution Texture Analysis and Acoustic Activity Detector for Real-Life Speech Emotion Recognition

PubMed Central

Wang, Kun-Ching

2015-01-01

The classification of emotional speech is mostly considered in speech-related research on human-computer interaction (HCI). In this paper, the purpose is to present a novel feature extraction based on multi-resolutions texture image information (MRTII). The MRTII feature set is derived from multi-resolution texture analysis for characterization and classification of different emotions in a speech signal. The motivation is that we have to consider emotions have different intensity values in different frequency bands. In terms of human visual perceptual, the texture property on multi-resolution of emotional speech spectrogram should be a good feature set for emotion classification in speech. Furthermore, the multi-resolution analysis on texture can give a clearer discrimination between each emotion than uniform-resolution analysis on texture. In order to provide high accuracy of emotional discrimination especially in real-life, an acoustic activity detection (AAD) algorithm must be applied into the MRTII-based feature extraction. Considering the presence of many blended emotions in real life, in this paper make use of two corpora of naturally-occurring dialogs recorded in real-life call centers. Compared with the traditional Mel-scale Frequency Cepstral Coefficients (MFCC) and the state-of-the-art features, the MRTII features also can improve the correct classification rates of proposed systems among different language databases. Experimental results show that the proposed MRTII-based feature information inspired by human visual perception of the spectrogram image can provide significant classification for real-life emotional recognition in speech. PMID:25594590

Prognostic Value and Reproducibility of Pretreatment CT Texture Features in Stage III Non-Small Cell Lung Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fried, David V.; Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas; Tucker, Susan L.

2014-11-15

Purpose: To determine whether pretreatment CT texture features can improve patient risk stratification beyond conventional prognostic factors (CPFs) in stage III non-small cell lung cancer (NSCLC). Methods and Materials: We retrospectively reviewed 91 cases with stage III NSCLC treated with definitive chemoradiation therapy. All patients underwent pretreatment diagnostic contrast enhanced computed tomography (CE-CT) followed by 4-dimensional CT (4D-CT) for treatment simulation. We used the average-CT and expiratory (T50-CT) images from the 4D-CT along with the CE-CT for texture extraction. Histogram, gradient, co-occurrence, gray tone difference, and filtration-based techniques were used for texture feature extraction. Penalized Cox regression implementing cross-validation wasmore » used for covariate selection and modeling. Models incorporating texture features from the 33 image types and CPFs were compared to those with models incorporating CPFs alone for overall survival (OS), local-regional control (LRC), and freedom from distant metastases (FFDM). Predictive Kaplan-Meier curves were generated using leave-one-out cross-validation. Patients were stratified based on whether their predicted outcome was above or below the median. Reproducibility of texture features was evaluated using test-retest scans from independent patients and quantified using concordance correlation coefficients (CCC). We compared models incorporating the reproducibility seen on test-retest scans to our original models and determined the classification reproducibility. Results: Models incorporating both texture features and CPFs demonstrated a significant improvement in risk stratification compared to models using CPFs alone for OS (P=.046), LRC (P=.01), and FFDM (P=.005). The average CCCs were 0.89, 0.91, and 0.67 for texture features extracted from the average-CT, T50-CT, and CE-CT, respectively. Incorporating reproducibility within our models yielded 80.4% (±3.7% SD), 78.3% (±4.0% SD), and 78.8% (±3.9% SD) classification reproducibility in terms of OS, LRC, and FFDM, respectively. Conclusions: Pretreatment tumor texture may provide prognostic information beyond that obtained from CPFs. Models incorporating feature reproducibility achieved classification rates of ∼80%. External validation would be required to establish texture as a prognostic factor.« less

Method: automatic segmentation of mitochondria utilizing patch classification, contour pair classification, and automatically seeded level sets

PubMed Central

2012-01-01

Background While progress has been made to develop automatic segmentation techniques for mitochondria, there remains a need for more accurate and robust techniques to delineate mitochondria in serial blockface scanning electron microscopic data. Previously developed texture based methods are limited for solving this problem because texture alone is often not sufficient to identify mitochondria. This paper presents a new three-step method, the Cytoseg process, for automated segmentation of mitochondria contained in 3D electron microscopic volumes generated through serial block face scanning electron microscopic imaging. The method consists of three steps. The first is a random forest patch classification step operating directly on 2D image patches. The second step consists of contour-pair classification. At the final step, we introduce a method to automatically seed a level set operation with output from previous steps. Results We report accuracy of the Cytoseg process on three types of tissue and compare it to a previous method based on Radon-Like Features. At step 1, we show that the patch classifier identifies mitochondria texture but creates many false positive pixels. At step 2, our contour processing step produces contours and then filters them with a second classification step, helping to improve overall accuracy. We show that our final level set operation, which is automatically seeded with output from previous steps, helps to smooth the results. Overall, our results show that use of contour pair classification and level set operations improve segmentation accuracy beyond patch classification alone. We show that the Cytoseg process performs well compared to another modern technique based on Radon-Like Features. Conclusions We demonstrated that texture based methods for mitochondria segmentation can be enhanced with multiple steps that form an image processing pipeline. While we used a random-forest based patch classifier to recognize texture, it would be possible to replace this with other texture identifiers, and we plan to explore this in future work. PMID:22321695

LITERATURE ABSTRACTS.

PubMed

1971-12-01

1. General Principles: 'Statistical Aspect of the Correlation Between Objective and Subjective Measurements of Meat Tenderness', by M. C. Gacula, Jr., J. B. Reaume, K. J. Morgan, and R. L. Luckett 1. General Principles: 'Texture of Semi-Solid Foods: Sensory and Physical Correlates', by W. F. Henry, M. H. Katz, F. J. Pilgrim, and A. T. May 2. Instrumentation and Methodology: 'Measurement of Bread Staling', by W. Morandini and L. Wassermann 2. Instrumentation and Methodology: 'Physical Considerations of the Methods of Consistency Measurement of Butter', by E. Knoop 2. Instrumentation and Methodology: 'Electronic Recording Mixers for the Baking Test', by P. W. Voisey, V. M. Bendelow and H. Miller 2. Instrumentation and Methodology: 'Measurement of the Consistency of Reconstituted Instant Potato Flakes', by P. W. Voisey and P. R. Dean 2. Instrumentation and Methodology: 'The Ottawa Electronic Recording Farinograph', by P. W. Voisey, H. Miller and P. L. Byrne 3. Objective Measurements: A. FOODS: 'The Rheological Properties of Corn Horny Endosperm', by J. R. Hamerle*, R. K. White**, and N. N. Mohsenin*** 3. Objective Measurements: 'Evaluation of Mechanical Properties of Comminuted Sausages by Construction and Analysis of Rheological Model', by St. Tyszkiewicz 3. Objective Measurements: 'Studies on Creep Compliance of Butter', by M. Chwiej 3. Objective Measurements: 'Heat-Induced Milk Gels. II. Preparation of Gels and Measurement of Firmness', by M. Kalab, P. W. Voisey and D. B. Emmons 3. Objective Measurements: 'Rheology of Fresh, Aged and Gamma-Irradiated Egg White', by M. A. Tung, J. F. Richards, B. C. Morrison and E. L. Watson 3. Objective Measurements: 'Retardation of Bread Staling - Practical Experiences', by W. Morandini and L. Wassermann 3. Objective Measurements: B. PHARMACEUTICALS: 'Influence of HLB on Certain Physicochemical Parameters of an O/W Emulsion', by M. Schrenzel 3. Objective Measurements: 'The Rheological Evaluation of Semisolids', by L. H. Block and P. P. Lamy 4. Factors Affecting Texture: 'Effects of Physical and Mechanical Treatments on the Tenderness of the Beef Longissimus', by G. C. Smith, T. C. Arango and Z. L. Carpenter 4. Factors Affecting Texture: 'Histological and Physical Changes in Carrots as Affected by Blanching, Cooking, Freezing, Freeze Drying and Compression', by A. R. Rahman, W. L. Henning and D. E. Westcott 4. Factors Affecting Texture: 'Effects of Physiological Maturity of Beef and Marbling of Rib Steaks on Eating Quality', by H. L. Norris, D. L. Harrison, L. L. Anderson, B. Van Welck and H. J. Tuma 4. Factors Affecting Texture: 'Effect of Ultimate pH Upon the Water-Holding Capacity and Tenderness of Mutton', by P. E. Bouton, P. V. Harris and W. R. Shorthose 4. Factors Affecting Texture: 'The Dilution Coefficient of Butter Serum and the Consistency of Butter', by E. Pijanowski, M. Chwiej, H. Hernik and M. Kurtowicz 4. Factors Affecting Texture: 'Moisture and pH Changes as Criteria of Freshness in Abalone and their Relationship to Texture of the Canned Product', by D. G. James and J. Olley 4. Factors Affecting Texture: 'Effect of Sucrose on Crispness of Explosion-Puffed Apple Pieces Exposed to High Humidities', by E. O. Strolle, J. Cording, Jr., P. E. McDowell, and R. K. Eskew 4. Factors Affecting Texture: 'Effect of Heat Treatment on Viscosity of Yolk', by P. K. Chang, W. D. Powrie and O. Fennema 4. Factors Affecting Texture: 'Protein Quality and Quantity: A Rheological Assessment of the Relative Importance in Breadmaking', by T. Webb, P. W. Heaps, and J. B. M. Coppock 4. Factors Affecting Texture: 'Bread Staling. 1. Experimental Study', by E. M. A. Willhoft 4. Factors Affecting Texture: 'Bread Staling. II. Theoretical Study', by E. M. A. Willhoft.

Finite element simulation of texture evolution and Swift effect in NiAl under torsion

NASA Astrophysics Data System (ADS)

Böhlke, Thomas; Glüge, Rainer; Klöden, Burghardt; Skrotzki, Werner; Bertram, Albrecht

2007-09-01

The texture evolution and the Swift effect in NiAl under torsion at 727 °C are studied by finite element simulations for two different initial textures. The material behaviour is modelled by an elastic-viscoplastic Taylor model. In order to overcome the well-known shortcomings of Taylor's approach, the texture evolution is also investigated by a representative volume element (RVE) with periodic boundary conditions and a compatible microstructure at the opposite faces of the RVE. Such a representative volume element takes into account the grain morphology and the grain interaction. The numerical results are compared with experimental data. It is shown that the modelling of a finite element based RVE leads to a better prediction of the final textures. However, the texture evolution path is not accounted for correctly. The simulated Swift effect depends much more on the initial orientation distribution than observed in experiment. Deviations between simulation and experiment may be due to continuous dynamic recrystallization.

Cloud cover analysis with Arctic Advanced Very High Resolution Radiometer data. II - Classification with spectral and textural measures

NASA Technical Reports Server (NTRS)

Key, J.

1990-01-01

The spectral and textural characteristics of polar clouds and surfaces for a 7-day summer series of AVHRR data in two Arctic locations are examined, and the results used in the development of a cloud classification procedure for polar satellite data. Since spatial coherence and texture sensitivity tests indicate that a joint spectral-textural analysis based on the same cell size is inappropriate, cloud detection with AVHRR data and surface identification with passive microwave data are first done on the pixel level as described by Key and Barry (1989). Next, cloud patterns within 250-sq-km regions are described, then the spectral and local textural characteristics of cloud patterns in the image are determined and each cloud pixel is classified by statistical methods. Results indicate that both spectral and textural features can be utilized in the classification of cloudy pixels, although spectral features are most useful for the discrimination between cloud classes.

The simulation of the half-dry stroke based on the force feedback technology

NASA Astrophysics Data System (ADS)

Guo, Chao; Hou, Zeng-xuan; Zheng, Shuan-zhu; Yang, Guang-qing

2017-02-01

A novel stroke simulation method of the Half-dry style of Chinese calligraphy based on the force feedback technology is proposed for the virtual painting. Firstly, according to the deformation of the brush when the force is exerted on it, the brush footprint between the brush and paper is calculated. The complete brush stroke is obtained by superimposing brush footprints along the painting direction, and the dynamic painting of the brush stroke is implemented. Then, we establish the half-dry texture databases and propose the concept of half-dry value by researching the main factors that affect the effects of the half-dry stroke. In the virtual painting, the half-dry texture is mapped into the stroke in real time according to the half-dry value and painting technique. A technique of texture blending based on the KM model is applied to avoid the seams while texture mapping. The proposed method has been successfully applied to the virtual painting system based on the force feedback technology. In this system, users can implement the painting in real time with a Phantom Desktop haptic device, which can effectively enhance reality to users.

A Comparative Study of Landsat TM and SPOT HRG Images for Vegetation Classification in the Brazilian Amazon.

PubMed

Lu, Dengsheng; Batistella, Mateus; de Miranda, Evaristo E; Moran, Emilio

2008-01-01

Complex forest structure and abundant tree species in the moist tropical regions often cause difficulties in classifying vegetation classes with remotely sensed data. This paper explores improvement in vegetation classification accuracies through a comparative study of different image combinations based on the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data, as well as the combination of spectral signatures and textures. A maximum likelihood classifier was used to classify the different image combinations into thematic maps. This research indicated that data fusion based on HRG multispectral and panchromatic data slightly improved vegetation classification accuracies: a 3.1 to 4.6 percent increase in the kappa coefficient compared with the classification results based on original HRG or TM multispectral images. A combination of HRG spectral signatures and two textural images improved the kappa coefficient by 6.3 percent compared with pure HRG multispectral images. The textural images based on entropy or second-moment texture measures with a window size of 9 pixels × 9 pixels played an important role in improving vegetation classification accuracy. Overall, optical remote-sensing data are still insufficient for accurate vegetation classifications in the Amazon basin.

Image ratio features for facial expression recognition application.

PubMed

Song, Mingli; Tao, Dacheng; Liu, Zicheng; Li, Xuelong; Zhou, Mengchu

2010-06-01

Video-based facial expression recognition is a challenging problem in computer vision and human-computer interaction. To target this problem, texture features have been extracted and widely used, because they can capture image intensity changes raised by skin deformation. However, existing texture features encounter problems with albedo and lighting variations. To solve both problems, we propose a new texture feature called image ratio features. Compared with previously proposed texture features, e.g., high gradient component features, image ratio features are more robust to albedo and lighting variations. In addition, to further improve facial expression recognition accuracy based on image ratio features, we combine image ratio features with facial animation parameters (FAPs), which describe the geometric motions of facial feature points. The performance evaluation is based on the Carnegie Mellon University Cohn-Kanade database, our own database, and the Japanese Female Facial Expression database. Experimental results show that the proposed image ratio feature is more robust to albedo and lighting variations, and the combination of image ratio features and FAPs outperforms each feature alone. In addition, we study asymmetric facial expressions based on our own facial expression database and demonstrate the superior performance of our combined expression recognition system.

Study on anisotropy of n-type Mg3Sb2-based thermoelectric materials

NASA Astrophysics Data System (ADS)

Song, Shaowei; Mao, Jun; Shuai, Jing; Zhu, Hangtian; Ren, Zhensong; Saparamadu, Udara; Tang, Zhongjia; Wang, Bo; Ren, Zhifeng

2018-02-01

The recent discovery of a high thermoelectric figure of merit (ZT) in an n-type Mg3Sb2-based Zintl phase triggered an intense research effort to pursue even higher ZT. Based on our previous report on Mg3.1Nb0.1Sb1.5Bi0.49Te0.01, we report here that partial texturing in the (001) plane is achieved by double hot pressing, which is further confirmed by the rocking curves of the (002) plane. The textured samples of Mg3.1Nb0.1Sb1.5Bi0.49Te0.01 show a much better average performance in the (00l) plane. Hall mobility is significantly improved to ˜105 cm2 V-1 s-1 at room temperature in the (00l) plane due to texturing, resulting in higher electrical conductivity, a higher power factor of ˜18 μW cm-1 K-2 at room temperature, and also higher average ZT. This work shows that texturing is good for higher thermoelectric performance, suggesting that single crystals of n-type Mg3Sb2-based Zintl compounds are worth pursuing.

A Comparative Study of Landsat TM and SPOT HRG Images for Vegetation Classification in the Brazilian Amazon

PubMed Central

Lu, Dengsheng; Batistella, Mateus; de Miranda, Evaristo E.; Moran, Emilio

2009-01-01

Complex forest structure and abundant tree species in the moist tropical regions often cause difficulties in classifying vegetation classes with remotely sensed data. This paper explores improvement in vegetation classification accuracies through a comparative study of different image combinations based on the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data, as well as the combination of spectral signatures and textures. A maximum likelihood classifier was used to classify the different image combinations into thematic maps. This research indicated that data fusion based on HRG multispectral and panchromatic data slightly improved vegetation classification accuracies: a 3.1 to 4.6 percent increase in the kappa coefficient compared with the classification results based on original HRG or TM multispectral images. A combination of HRG spectral signatures and two textural images improved the kappa coefficient by 6.3 percent compared with pure HRG multispectral images. The textural images based on entropy or second-moment texture measures with a window size of 9 pixels × 9 pixels played an important role in improving vegetation classification accuracy. Overall, optical remote-sensing data are still insufficient for accurate vegetation classifications in the Amazon basin. PMID:19789716

Accuracy and Precision of Silicon Based Impression Media for Quantitative Areal Texture Analysis

PubMed Central

Goodall, Robert H.; Darras, Laurent P.; Purnell, Mark A.

2015-01-01

Areal surface texture analysis is becoming widespread across a diverse range of applications, from engineering to ecology. In many studies silicon based impression media are used to replicate surfaces, and the fidelity of replication defines the quality of data collected. However, while different investigators have used different impression media, the fidelity of surface replication has not been subjected to quantitative analysis based on areal texture data. Here we present the results of an analysis of the accuracy and precision with which different silicon based impression media of varying composition and viscosity replicate rough and smooth surfaces. Both accuracy and precision vary greatly between different media. High viscosity media tested show very low accuracy and precision, and most other compounds showed either the same pattern, or low accuracy and high precision, or low precision and high accuracy. Of the media tested, mid viscosity President Jet Regular Body and low viscosity President Jet Light Body (Coltène Whaledent) are the only compounds to show high levels of accuracy and precision on both surface types. Our results show that data acquired from different impression media are not comparable, supporting calls for greater standardisation of methods in areal texture analysis. PMID:25991505

Characterization of Breast Implant Surfaces, Shapes, and Biomechanics: A Comparison of High Cohesive Anatomically Shaped Textured Silicone, Breast Implants from Three Different Manufacturers.

PubMed

Atlan, Michael; Bigerelle, Maxence; Larreta-garde, Véronique; Hindié, Mathilde; Hedén, Per

2016-02-01

Several companies offer anatomically shaped breast implants but differences among manufacturers are often misunderstood. The shell texture is a crucial parameter for anatomically shaped implants to prevent rotation and to decrease the risk of capsular contracture, even though concerns have recently been raised concerning the complications associated with textured breast implants. The aim of this study was to characterize differences in terms of texture, cell adhesion, shape, and stiffness between some commonly used anatomically shaped implants from three different manufacturers. Five commercially available anatomically shaped breast implants from 3 different manufacturers (Allergan, Mentor, and Sebbin) were used. Scanning electron microscopy, X-ray microtomography, and scanning mechanical microscopy were used to characterize the shell texture. Human fibroblast adhesion onto the shells was evaluated. 3D models of the implants were obtained using CT-scan acquisitions to analyze their shape. Implant stiffness was evaluated using a tractiometer. Major differences were observed in the topography of the textures of the shells, but this was not conveyed by a statistically significant fibroblast adhesion difference. However, fibroblasts adhered better on anatomically shaped textured implants than on smooth implants (p < 0.01). Our work pointed out differences in the Biocell® texture in comparison with older studies. The 3D analysis showed significant shape differences between the anatomically shaped implants of the 3 companies, despite similar dimensions. Implant stiffness was comparable among the 3 brands. Each texture had its specific topography, and this work is the first description of Sebbin anatomic breast implant texturation. Moreover, major discrepancies were found in the analysis of the Biocell® texture when comparing our results with previous reports. These differences may have clinical implications and are discussed. This study also highlighted major shape differences among breast implants from different manufacturers, which is quite counterintuitive. The clinical impact of these differences however needs further investigation. This journal requires that authors assign a level of evidence to each submission to which Evidence-Based Medicine rankings are applicable. This excludes Review Articles, Book Reviews, and manuscripts that concern Basic Science, Animal Studies, Cadaver Studies, and Experimental Studies. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266.

Multi-scale textural feature extraction and particle swarm optimization based model selection for false positive reduction in mammography.

PubMed

Zyout, Imad; Czajkowska, Joanna; Grzegorzek, Marcin

2015-12-01

The high number of false positives and the resulting number of avoidable breast biopsies are the major problems faced by current mammography Computer Aided Detection (CAD) systems. False positive reduction is not only a requirement for mass but also for calcification CAD systems which are currently deployed for clinical use. This paper tackles two problems related to reducing the number of false positives in the detection of all lesions and masses, respectively. Firstly, textural patterns of breast tissue have been analyzed using several multi-scale textural descriptors based on wavelet and gray level co-occurrence matrix. The second problem addressed in this paper is the parameter selection and performance optimization. For this, we adopt a model selection procedure based on Particle Swarm Optimization (PSO) for selecting the most discriminative textural features and for strengthening the generalization capacity of the supervised learning stage based on a Support Vector Machine (SVM) classifier. For evaluating the proposed methods, two sets of suspicious mammogram regions have been used. The first one, obtained from Digital Database for Screening Mammography (DDSM), contains 1494 regions (1000 normal and 494 abnormal samples). The second set of suspicious regions was obtained from database of Mammographic Image Analysis Society (mini-MIAS) and contains 315 (207 normal and 108 abnormal) samples. Results from both datasets demonstrate the efficiency of using PSO based model selection for optimizing both classifier hyper-parameters and parameters, respectively. Furthermore, the obtained results indicate the promising performance of the proposed textural features and more specifically, those based on co-occurrence matrix of wavelet image representation technique. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multi-scale radiomic analysis of sub-cortical regions in MRI related to autism, gender and age

NASA Astrophysics Data System (ADS)

Chaddad, Ahmad; Desrosiers, Christian; Toews, Matthew

2017-03-01

We propose using multi-scale image textures to investigate links between neuroanatomical regions and clinical variables in MRI. Texture features are derived at multiple scales of resolution based on the Laplacian-of-Gaussian (LoG) filter. Three quantifier functions (Average, Standard Deviation and Entropy) are used to summarize texture statistics within standard, automatically segmented neuroanatomical regions. Significance tests are performed to identify regional texture differences between ASD vs. TDC and male vs. female groups, as well as correlations with age (corrected p < 0.05). The open-access brain imaging data exchange (ABIDE) brain MRI dataset is used to evaluate texture features derived from 31 brain regions from 1112 subjects including 573 typically developing control (TDC, 99 females, 474 males) and 539 Autism spectrum disorder (ASD, 65 female and 474 male) subjects. Statistically significant texture differences between ASD vs. TDC groups are identified asymmetrically in the right hippocampus, left choroid-plexus and corpus callosum (CC), and symmetrically in the cerebellar white matter. Sex-related texture differences in TDC subjects are found in primarily in the left amygdala, left cerebellar white matter, and brain stem. Correlations between age and texture in TDC subjects are found in the thalamus-proper, caudate and pallidum, most exhibiting bilateral symmetry.

High-Speed Rolling of AZ31 Magnesium Alloy Having Different Initial Textures

NASA Astrophysics Data System (ADS)

Onuki, Yusuke; Hara, Kenichiro; Utsunomiya, Hiroshi; Szpunar, Jerzy A.

2015-02-01

It is known that magnesium alloys can be rolled up to a large thickness reduction and develop a unique texture when the rolling speed is high (>1000 m/min). In order to understand the texture formation mechanism during high-strain-rate deformation, high-speed rolling of AZ31 magnesium alloy samples having different initial textures was conducted. The main components of the textures after the rolling were the RD-split basal, which consisted of 10°-20° inclining basal poles from the normal direction toward the rolling direction of the sheet, regardless of the different initial textures. With preheating at 473 K, all the samples were rolled without cracking while all were cracked when preheating was not applied. The optical micrographs and EBSD measurements showed a significant amount of twins and the cracks that developed along the shear bands consisted with laminated twins. Based on the texture simulation using the visco-plastic self-consistent model, it is concluded that the rapid development of the RD-split basal component from the initial basal alignment along the transverse direction was attributable to the tension twinning, The effect of the initial texture on the crack formation can be explained by the activation of the twinning system.

Design, fabrication and performance of small, graphite electrode, multistage depressed collectors with 200-W, CW, 8- to 18-GHz traveling-wave tubes

NASA Technical Reports Server (NTRS)

Ebihara, Ben T.; Ramins, Peter

1987-01-01

Small multistage depressed collectors (MDC's) which used pyrolytic graphite, ion-beam-textured pyrolytic graphite, and isotropic graphite electrodes were designed, fabricated, and evaluated in conjuntion with 200-W, continuous wave (CW), 8- to 18-GHz traveling-wave tubes (TWT's). The design, construction, and performance of the MDC's are described. The bakeout performance of the collectors, in terms of gas evolution, was indistinguishable from that of typical production tubes with copper collectors. However, preliminary results indicate that some additional radiofrequency (RF) and dc beam processing time (and/or longer or higher temperature bakeouts) may be needed beyond that of typical copper electrode collectors. This is particularly true for pyrolytic graphite electrodes and for TWT's without appendage ion pumps. Extended testing indicated good long-term stability of the textured pyrolytic graphite and isotropic graphite electrode surfaces. The isotropic graphite in particular showed considerable promise as an MDC electrode material because of its high purity, low cost, simple construction, potential for very compact overall size, and relatively low secondary electron emission yield characteristics in the as-machined state. However, considerably more testing experience is required before definitive conclusions on its suitability for electronic countermeasure systems and space TWT's can be made.

Implementation of light extraction improvements of GaN-based light-emitting diodes with specific textured sidewalls

NASA Astrophysics Data System (ADS)

Chen, Chun-Yen; Chen, Wei-Cheng; Chang, Ching-Hong; Lee, Yu-Lin; Liu, Wen-Chau

2018-05-01

Textured-sidewall GaN-based light-emitting diodes (LEDs) with various sidewall angles (15-90°) and convex or concave sidewalls prepared using an inductively-coupled-plasma approach are comprehensively fabricated and studied. The device with 45° sidewalls (Device F) and that with convex sidewalls (Device B) show significant improvements in optical properties. Experiments show that, at an injection current of 350 mA, the light output power, external quantum efficiency, wall-plug efficiency, and luminous flux of Device F (Device B) are greatly improved by 18.3% (18.2%), 18.2% (18.2%), 17.3% (19.8%), and 16.6% (18.4%), respectively, compared to those of a conventional LED with flat sidewalls. In addition, negligible degradation in electrical properties is found. The enhanced optical performance is mainly attributed to increased light extraction in the horizontal direction due to a significant reduction in total internal reflection at the textured sidewalls. Therefore, the reported specific textured-sidewall structures (Devices B and F) are promising for high-power GaN-based LED applications.

3D Texture Analysis Reveals Imperceptible MRI Textural Alterations in the Thalamus and Putamen in Progressive Myoclonic Epilepsy Type 1, EPM1

PubMed Central

Suoranta, Sanna; Holli-Helenius, Kirsi; Koskenkorva, Päivi; Niskanen, Eini; Könönen, Mervi; Äikiä, Marja; Eskola, Hannu; Kälviäinen, Reetta; Vanninen, Ritva

2013-01-01

Progressive myoclonic epilepsy type 1 (EPM1) is an autosomal recessively inherited neurodegenerative disorder characterized by young onset age, myoclonus and tonic-clonic epileptic seizures. At the time of diagnosis, the visual assessment of the brain MRI is usually normal, with no major changes found later. Therefore, we utilized texture analysis (TA) to characterize and classify the underlying properties of the affected brain tissue by means of 3D texture features. Sixteen genetically verified patients with EPM1 and 16 healthy controls were included in the study. TA was performed upon 3D volumes of interest that were placed bilaterally in the thalamus, amygdala, hippocampus, caudate nucleus and putamen. Compared to the healthy controls, EPM1 patients had significant textural differences especially in the thalamus and right putamen. The most significantly differing texture features included parameters that measure the complexity and heterogeneity of the tissue, such as the co-occurrence matrix-based entropy and angular second moment, and also the run-length matrix-based parameters of gray-level non-uniformity, short run emphasis and long run emphasis. This study demonstrates the usability of 3D TA for extracting additional information from MR images. Textural alterations which suggest complex, coarse and heterogeneous appearance were found bilaterally in the thalamus, supporting the previous literature on thalamic pathology in EPM1. The observed putamenal involvement is a novel finding. Our results encourage further studies on the clinical applications, feasibility, reproducibility and reliability of 3D TA. PMID:23922849

Textural Maturity Analysis and Sedimentary Environment Discrimination Based on Grain Shape Data

NASA Astrophysics Data System (ADS)

Tunwal, M.; Mulchrone, K. F.; Meere, P. A.

2017-12-01

Morphological analysis of clastic sedimentary grains is an important source of information regarding the processes involved in their formation, transportation and deposition. However, a standardised approach for quantitative grain shape analysis is generally lacking. In this contribution we report on a study where fully automated image analysis techniques were applied to loose sediment samples collected from glacial, aeolian, beach and fluvial environments. A range of shape parameters are evaluated for their usefulness in textural characterisation of populations of grains. The utility of grain shape data in ranking textural maturity of samples within a given sedimentary environment is evaluated. Furthermore, discrimination of sedimentary environment on the basis of grain shape information is explored. The data gathered demonstrates a clear progression in textural maturity in terms of roundness, angularity, irregularity, fractal dimension, convexity, solidity and rectangularity. Textural maturity can be readily categorised using automated grain shape parameter analysis. However, absolute discrimination between different depositional environments on the basis of shape parameters alone is less certain. For example, the aeolian environment is quite distinct whereas fluvial, glacial and beach samples are inherently variable and tend to overlap each other in terms of textural maturity. This is most likely due to a collection of similar processes and sources operating within these environments. This study strongly demonstrates the merit of quantitative population-based shape parameter analysis of texture and indicates that it can play a key role in characterising both loose and consolidated sediments. This project is funded by the Irish Petroleum Infrastructure Programme (www.pip.ie)

Effect of phase composition on crystal texture formation in hot deformed nanocrystalline SmCo5 magnets

NASA Astrophysics Data System (ADS)

Ma, Qiang; Yue, Ming; Xu, Xiaochang; Zhang, Hongguo; Zhang, Dongtao; Zhang, Xuefeng; Zhang, Jiuxing

2018-05-01

In the present study, bulk anisotropic nanocrystalline SmCo5 magnets were prepared by hot press and subsequent hot deformation method. Effect of phase composition on texture and magnetic properties are presented, based on which the mechanism of plastic deformation and texture formation during the hot deformation process is discussed. The SmCo5 magnets were prepared by hot deformation, excessive Sm of 2.5 wt% and 10 wt% was added to compensate the weight loss due to Sm evaporation. Our analyses reveal that the phase composition is one of the most important parameters that determine the texture of SmCo5 magnets. It is therefore suggested that the existence of 2:17 phase and its phase transformation undermined the crystal texture formation as well as the magnetic properties of nanocrystalline SmCo5 magnets.

Textured micrometer scale templates as light managing fabrication platform for organic solar cells

DOEpatents

Chaudhary, Sumit; Ho, Kai-Ming; Park, Joong-Mok; Nalwa, Kanwar Singh; Leung, Wai Y.

2016-07-26

A three-dimensional, microscale-textured, grating-shaped organic solar cell geometry. The solar cells are fabricated on gratings to give them a three-dimensional texture that provides enhanced light absorption. Introduction of microscale texturing has a positive effect on the overall power conversion efficiency of the devices. This grating-based solar cell having a grating of pre-determined pitch and height has shown improved power-conversion efficiency over a conventional flat solar cell. The improvement in efficiency is accomplished by homogeneous coverage of the grating with uniform thickness of the active layer, which is attributed to a sufficiently high pitch and low height of the underlying gratings. Also the microscale texturing leads to suppressed reflection of incident light due to the efficient coupling of the incident light into modes that are guided in the active layer.

Classification and recognition of texture collagen obtaining by multiphoton microscope with neural network analysis

NASA Astrophysics Data System (ADS)

Wu, Shulian; Peng, Yuanyuan; Hu, Liangjun; Zhang, Xiaoman; Li, Hui

2016-01-01

Second harmonic generation microscopy (SHGM) was used to monitor the process of chronological aging skin in vivo. The collagen structures of mice model with different ages were obtained using SHGM. Then, texture feature with contrast, correlation and entropy were extracted and analysed using the grey level co-occurrence matrix. At last, the neural network tool of Matlab was applied to train the texture of collagen in different statues during the aging process. And the simulation of mice collagen texture was carried out. The results indicated that the classification accuracy reach 85%. Results demonstrated that the proposed approach effectively detected the target object in the collagen texture image during the chronological aging process and the analysis tool based on neural network applied the skin of classification and feature extraction method is feasible.

Segmentation and texture analysis of structural biomarkers using neighborhood-clustering-based level set in MRI of the schizophrenic brain.

PubMed

Latha, Manohar; Kavitha, Ganesan

2018-02-03

Schizophrenia (SZ) is a psychiatric disorder that especially affects individuals during their adolescence. There is a need to study the subanatomical regions of SZ brain on magnetic resonance images (MRI) based on morphometry. In this work, an attempt was made to analyze alterations in structure and texture patterns in images of the SZ brain using the level-set method and Laws texture features. T1-weighted MRI of the brain from Center of Biomedical Research Excellence (COBRE) database were considered for analysis. Segmentation was carried out using the level-set method. Geometrical and Laws texture features were extracted from the segmented brain stem, corpus callosum, cerebellum, and ventricle regions to analyze pattern changes in SZ. The level-set method segmented multiple brain regions, with higher similarity and correlation values compared with an optimized method. The geometric features obtained from regions of the corpus callosum and ventricle showed significant variation (p < 0.00001) between normal and SZ brain. Laws texture feature identified a heterogeneous appearance in the brain stem, corpus callosum and ventricular regions, and features from the brain stem were correlated with Positive and Negative Syndrome Scale (PANSS) score (p < 0.005). A framework of geometric and Laws texture features obtained from brain subregions can be used as a supplement for diagnosis of psychiatric disorders.

Novel texture-based descriptors for tool wear condition monitoring

NASA Astrophysics Data System (ADS)

Antić, Aco; Popović, Branislav; Krstanović, Lidija; Obradović, Ratko; Milošević, Mijodrag

2018-01-01

All state-of-the-art tool condition monitoring systems (TCM) in the tool wear recognition task, especially those that use vibration sensors, heavily depend on the choice of descriptors containing information about the tool wear state which are extracted from the particular sensor signals. All other post-processing techniques do not manage to increase the recognition precision if those descriptors are not discriminative enough. In this work, we propose a tool wear monitoring strategy which relies on the novel texture based descriptors. We consider the module of the Short Term Discrete Fourier Transform (STDFT) spectra obtained from the particular vibration sensors signal utterance as the 2D textured image. This is done by identifying the time scale of STDFT as the first dimension, and the frequency scale as the second dimension of the particular textured image. The obtained textured image is then divided into particular 2D texture patches, covering a part of the frequency range of interest. After applying the appropriate filter bank, 2D textons are extracted for each predefined frequency band. By averaging in time, we extract from the textons for each band of interest the information regarding the Probability Density Function (PDF) in the form of lower order moments, thus obtaining robust tool wear state descriptors. We validate the proposed features by the experiments conducted on the real TCM system, obtaining the high recognition accuracy.

Bayesian exploration for intelligent identification of textures.

PubMed

Fishel, Jeremy A; Loeb, Gerald E

2012-01-01

In order to endow robots with human-like abilities to characterize and identify objects, they must be provided with tactile sensors and intelligent algorithms to select, control, and interpret data from useful exploratory movements. Humans make informed decisions on the sequence of exploratory movements that would yield the most information for the task, depending on what the object may be and prior knowledge of what to expect from possible exploratory movements. This study is focused on texture discrimination, a subset of a much larger group of exploratory movements and percepts that humans use to discriminate, characterize, and identify objects. Using a testbed equipped with a biologically inspired tactile sensor (the BioTac), we produced sliding movements similar to those that humans make when exploring textures. Measurement of tactile vibrations and reaction forces when exploring textures were used to extract measures of textural properties inspired from psychophysical literature (traction, roughness, and fineness). Different combinations of normal force and velocity were identified to be useful for each of these three properties. A total of 117 textures were explored with these three movements to create a database of prior experience to use for identifying these same textures in future encounters. When exploring a texture, the discrimination algorithm adaptively selects the optimal movement to make and property to measure based on previous experience to differentiate the texture from a set of plausible candidates, a process we call Bayesian exploration. Performance of 99.6% in correctly discriminating pairs of similar textures was found to exceed human capabilities. Absolute classification from the entire set of 117 textures generally required a small number of well-chosen exploratory movements (median = 5) and yielded a 95.4% success rate. The method of Bayesian exploration developed and tested in this paper may generalize well to other cognitive problems.

Bayesian Exploration for Intelligent Identification of Textures

PubMed Central

Fishel, Jeremy A.; Loeb, Gerald E.

2012-01-01

In order to endow robots with human-like abilities to characterize and identify objects, they must be provided with tactile sensors and intelligent algorithms to select, control, and interpret data from useful exploratory movements. Humans make informed decisions on the sequence of exploratory movements that would yield the most information for the task, depending on what the object may be and prior knowledge of what to expect from possible exploratory movements. This study is focused on texture discrimination, a subset of a much larger group of exploratory movements and percepts that humans use to discriminate, characterize, and identify objects. Using a testbed equipped with a biologically inspired tactile sensor (the BioTac), we produced sliding movements similar to those that humans make when exploring textures. Measurement of tactile vibrations and reaction forces when exploring textures were used to extract measures of textural properties inspired from psychophysical literature (traction, roughness, and fineness). Different combinations of normal force and velocity were identified to be useful for each of these three properties. A total of 117 textures were explored with these three movements to create a database of prior experience to use for identifying these same textures in future encounters. When exploring a texture, the discrimination algorithm adaptively selects the optimal movement to make and property to measure based on previous experience to differentiate the texture from a set of plausible candidates, a process we call Bayesian exploration. Performance of 99.6% in correctly discriminating pairs of similar textures was found to exceed human capabilities. Absolute classification from the entire set of 117 textures generally required a small number of well-chosen exploratory movements (median = 5) and yielded a 95.4% success rate. The method of Bayesian exploration developed and tested in this paper may generalize well to other cognitive problems. PMID:22783186

Extraction of texture features with a multiresolution neural network

NASA Astrophysics Data System (ADS)

Lepage, Richard; Laurendeau, Denis; Gagnon, Roger A.

1992-09-01

Texture is an important surface characteristic. Many industrial materials such as wood, textile, or paper are best characterized by their texture. Detection of defaults occurring on such materials or classification for quality control anD matching can be carried out through careful texture analysis. A system for the classification of pieces of wood used in the furniture industry is proposed. This paper is concerned with a neural network implementation of the features extraction and classification components of the proposed system. Texture appears differently depending at which spatial scale it is observed. A complete description of a texture thus implies an analysis at several spatial scales. We propose a compact pyramidal representation of the input image for multiresolution analysis. The feature extraction system is implemented on a multilayer artificial neural network. Each level of the pyramid, which is a representation of the input image at a given spatial resolution scale, is mapped into a layer of the neural network. A full resolution texture image is input at the base of the pyramid and a representation of the texture image at multiple resolutions is generated by the feedforward pyramid structure of the neural network. The receptive field of each neuron at a given pyramid level is preprogrammed as a discrete Gaussian low-pass filter. Meaningful characteristics of the textured image must be extracted if a good resolving power of the classifier must be achieved. Local dominant orientation is the principal feature which is extracted from the textured image. Local edge orientation is computed with a Sobel mask at four orientation angles (multiple of (pi) /4). The resulting intrinsic image, that is, the local dominant orientation image, is fed to the texture classification neural network. The classification network is a three-layer feedforward back-propagation neural network.

Exemplar-Based Image Inpainting Using a Modified Priority Definition.

PubMed

Deng, Liang-Jian; Huang, Ting-Zhu; Zhao, Xi-Le

2015-01-01

Exemplar-based algorithms are a popular technique for image inpainting. They mainly have two important phases: deciding the filling-in order and selecting good exemplars. Traditional exemplar-based algorithms are to search suitable patches from source regions to fill in the missing parts, but they have to face a problem: improper selection of exemplars. To improve the problem, we introduce an independent strategy through investigating the process of patches propagation in this paper. We first define a new separated priority definition to propagate geometry and then synthesize image textures, aiming to well recover image geometry and textures. In addition, an automatic algorithm is designed to estimate steps for the new separated priority definition. Comparing with some competitive approaches, the new priority definition can recover image geometry and textures well.

Exemplar-Based Image Inpainting Using a Modified Priority Definition

PubMed Central

Deng, Liang-Jian; Huang, Ting-Zhu; Zhao, Xi-Le

2015-01-01

Exemplar-based algorithms are a popular technique for image inpainting. They mainly have two important phases: deciding the filling-in order and selecting good exemplars. Traditional exemplar-based algorithms are to search suitable patches from source regions to fill in the missing parts, but they have to face a problem: improper selection of exemplars. To improve the problem, we introduce an independent strategy through investigating the process of patches propagation in this paper. We first define a new separated priority definition to propagate geometry and then synthesize image textures, aiming to well recover image geometry and textures. In addition, an automatic algorithm is designed to estimate steps for the new separated priority definition. Comparing with some competitive approaches, the new priority definition can recover image geometry and textures well. PMID:26492491

Local multifractal detrended fluctuation analysis for non-stationary image's texture segmentation

NASA Astrophysics Data System (ADS)

Wang, Fang; Li, Zong-shou; Li, Jin-wei

2014-12-01

Feature extraction plays a great important role in image processing and pattern recognition. As a power tool, multifractal theory is recently employed for this job. However, traditional multifractal methods are proposed to analyze the objects with stationary measure and cannot for non-stationary measure. The works of this paper is twofold. First, the definition of stationary image and 2D image feature detection methods are proposed. Second, a novel feature extraction scheme for non-stationary image is proposed by local multifractal detrended fluctuation analysis (Local MF-DFA), which is based on 2D MF-DFA. A set of new multifractal descriptors, called local generalized Hurst exponent (Lhq) is defined to characterize the local scaling properties of textures. To test the proposed method, both the novel texture descriptor and other two multifractal indicators, namely, local Hölder coefficients based on capacity measure and multifractal dimension Dq based on multifractal differential box-counting (MDBC) method, are compared in segmentation experiments. The first experiment indicates that the segmentation results obtained by the proposed Lhq are better than the MDBC-based Dq slightly and superior to the local Hölder coefficients significantly. The results in the second experiment demonstrate that the Lhq can distinguish the texture images more effectively and provide more robust segmentations than the MDBC-based Dq significantly.

Quantification of Shape, Angularity, and Surface texture of Base Course Materials

DOT National Transportation Integrated Search

1998-01-01

A state-of-the-art review was conducted to determine existing test methods for characterizing the shape, angularity, and surface texture of coarse aggregates. The review found direct methods used by geologists to determine these characteristics. Thes...

Texture analysis improves level set segmentation of the anterior abdominal wall

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Zhoubing; Allen, Wade M.; Baucom, Rebeccah B.

2013-12-15

Purpose: The treatment of ventral hernias (VH) has been a challenging problem for medical care. Repair of these hernias is fraught with failure; recurrence rates ranging from 24% to 43% have been reported, even with the use of biocompatible mesh. Currently, computed tomography (CT) is used to guide intervention through expert, but qualitative, clinical judgments, notably, quantitative metrics based on image-processing are not used. The authors propose that image segmentation methods to capture the three-dimensional structure of the abdominal wall and its abnormalities will provide a foundation on which to measure geometric properties of hernias and surrounding tissues and, therefore,more » to optimize intervention.Methods: In this study with 20 clinically acquired CT scans on postoperative patients, the authors demonstrated a novel approach to geometric classification of the abdominal. The authors’ approach uses a texture analysis based on Gabor filters to extract feature vectors and follows a fuzzy c-means clustering method to estimate voxelwise probability memberships for eight clusters. The memberships estimated from the texture analysis are helpful to identify anatomical structures with inhomogeneous intensities. The membership was used to guide the level set evolution, as well as to derive an initial start close to the abdominal wall.Results: Segmentation results on abdominal walls were both quantitatively and qualitatively validated with surface errors based on manually labeled ground truth. Using texture, mean surface errors for the outer surface of the abdominal wall were less than 2 mm, with 91% of the outer surface less than 5 mm away from the manual tracings; errors were significantly greater (2–5 mm) for methods that did not use the texture.Conclusions: The authors’ approach establishes a baseline for characterizing the abdominal wall for improving VH care. Inherent texture patterns in CT scans are helpful to the tissue classification, and texture analysis can improve the level set segmentation around the abdominal region.« less

Quantification of ultrasonic texture intra-heterogeneity via volumetric stochastic modeling for tissue characterization.

PubMed

Al-Kadi, Omar S; Chung, Daniel Y F; Carlisle, Robert C; Coussios, Constantin C; Noble, J Alison

2015-04-01

Intensity variations in image texture can provide powerful quantitative information about physical properties of biological tissue. However, tissue patterns can vary according to the utilized imaging system and are intrinsically correlated to the scale of analysis. In the case of ultrasound, the Nakagami distribution is a general model of the ultrasonic backscattering envelope under various scattering conditions and densities where it can be employed for characterizing image texture, but the subtle intra-heterogeneities within a given mass are difficult to capture via this model as it works at a single spatial scale. This paper proposes a locally adaptive 3D multi-resolution Nakagami-based fractal feature descriptor that extends Nakagami-based texture analysis to accommodate subtle speckle spatial frequency tissue intensity variability in volumetric scans. Local textural fractal descriptors - which are invariant to affine intensity changes - are extracted from volumetric patches at different spatial resolutions from voxel lattice-based generated shape and scale Nakagami parameters. Using ultrasound radio-frequency datasets we found that after applying an adaptive fractal decomposition label transfer approach on top of the generated Nakagami voxels, tissue characterization results were superior to the state of art. Experimental results on real 3D ultrasonic pre-clinical and clinical datasets suggest that describing tumor intra-heterogeneity via this descriptor may facilitate improved prediction of therapy response and disease characterization. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Prostate-specific membrane antigen PET/MRI validation of MR textural analysis for detection of transition zone prostate cancer.

PubMed

Bates, Anthony; Miles, Kenneth

2017-12-01

To validate MR textural analysis (MRTA) for detection of transition zone (TZ) prostate cancer through comparison with co-registered prostate-specific membrane antigen (PSMA) PET-MR. Retrospective analysis was performed for 30 men who underwent simultaneous PSMA PET-MR imaging for staging of prostate cancer. Thirty texture features were derived from each manually contoured T2-weighted, transaxial, prostatic TZ using texture analysis software that applies a spatial band-pass filter and quantifies texture through histogram analysis. Texture features of the TZ were compared to PSMA expression on the corresponding PET images. The Benjamini-Hochberg correction controlled the false discovery rate at <5%. Eighty-eight T2-weighted images in 18 patients demonstrated abnormal PSMA expression within the TZ on PET-MR. 123 images were PSMA negative. Based on the corrected p-value of 0.005, significant differences between PSMA positive and negative slices were found for 16 texture parameters: Standard deviation and mean of positive pixels for all spatial filters (p = <0.0001 for both at all spatial scaling factor (SSF) values) and mean intensity following filtration for SSF 3-6 mm (p = 0.0002-0.0018). Abnormal expression of PSMA within the TZ is associated with altered texture on T2-weighted MR, providing validation of MRTA for the detection of TZ prostate cancer. • Prostate transition zone (TZ) MR texture analysis may assist in prostate cancer detection. • Abnormal transition zone PSMA expression correlates with altered texture on T2-weighted MR. • TZ with abnormal PSMA expression demonstrates significantly reduced MI, SD and MPP.

Pneumothorax detection in chest radiographs using local and global texture signatures

NASA Astrophysics Data System (ADS)

Geva, Ofer; Zimmerman-Moreno, Gali; Lieberman, Sivan; Konen, Eli; Greenspan, Hayit

2015-03-01

A novel framework for automatic detection of pneumothorax abnormality in chest radiographs is presented. The suggested method is based on a texture analysis approach combined with supervised learning techniques. The proposed framework consists of two main steps: at first, a texture analysis process is performed for detection of local abnormalities. Labeled image patches are extracted in the texture analysis procedure following which local analysis values are incorporated into a novel global image representation. The global representation is used for training and detection of the abnormality at the image level. The presented global representation is designed based on the distinctive shape of the lung, taking into account the characteristics of typical pneumothorax abnormalities. A supervised learning process was performed on both the local and global data, leading to trained detection system. The system was tested on a dataset of 108 upright chest radiographs. Several state of the art texture feature sets were experimented with (Local Binary Patterns, Maximum Response filters). The optimal configuration yielded sensitivity of 81% with specificity of 87%. The results of the evaluation are promising, establishing the current framework as a basis for additional improvements and extensions.

Dynamic texture recognition using local binary patterns with an application to facial expressions.

PubMed

Zhao, Guoying; Pietikäinen, Matti

2007-06-01

Dynamic texture (DT) is an extension of texture to the temporal domain. Description and recognition of DTs have attracted growing attention. In this paper, a novel approach for recognizing DTs is proposed and its simplifications and extensions to facial image analysis are also considered. First, the textures are modeled with volume local binary patterns (VLBP), which are an extension of the LBP operator widely used in ordinary texture analysis, combining motion and appearance. To make the approach computationally simple and easy to extend, only the co-occurrences of the local binary patterns on three orthogonal planes (LBP-TOP) are then considered. A block-based method is also proposed to deal with specific dynamic events such as facial expressions in which local information and its spatial locations should also be taken into account. In experiments with two DT databases, DynTex and Massachusetts Institute of Technology (MIT), both the VLBP and LBP-TOP clearly outperformed the earlier approaches. The proposed block-based method was evaluated with the Cohn-Kanade facial expression database with excellent results. The advantages of our approach include local processing, robustness to monotonic gray-scale changes, and simple computation.

Local binary pattern variants-based adaptive texture features analysis for posed and nonposed facial expression recognition

NASA Astrophysics Data System (ADS)

Sultana, Maryam; Bhatti, Naeem; Javed, Sajid; Jung, Soon Ki

2017-09-01

Facial expression recognition (FER) is an important task for various computer vision applications. The task becomes challenging when it requires the detection and encoding of macro- and micropatterns of facial expressions. We present a two-stage texture feature extraction framework based on the local binary pattern (LBP) variants and evaluate its significance in recognizing posed and nonposed facial expressions. We focus on the parametric limitations of the LBP variants and investigate their effects for optimal FER. The size of the local neighborhood is an important parameter of the LBP technique for its extraction in images. To make the LBP adaptive, we exploit the granulometric information of the facial images to find the local neighborhood size for the extraction of center-symmetric LBP (CS-LBP) features. Our two-stage texture representations consist of an LBP variant and the adaptive CS-LBP features. Among the presented two-stage texture feature extractions, the binarized statistical image features and adaptive CS-LBP features were found showing high FER rates. Evaluation of the adaptive texture features shows competitive and higher performance than the nonadaptive features and other state-of-the-art approaches, respectively.

Tunable dielectric properties of mesoporous carbon hollow microspheres via textural properties.

PubMed

Xu, Hailong; Yin, Xiaowei; Li, Zhaochen; Liu, Chenglong; Wang, Zeyu; Li, Minghang; Zhang, Litong; Cheng, Laifei

2018-05-04

In this study, mesoporous carbon hollow microspheres (PCHMs) with tunable textural properties have been prepared through a facile hard template etching method. The PCHMs were characterized by scanning electron microscopy, transmission electron microscopy, x-ray diffraction, Raman spectra, and nitrogen adsorption and desorption systems. Uniform PCHMs with shell thickness ranging from 23 nm to 55 nm are realized. PCHMs with different textural properties can regulate dielectric and electromagnetic (EM) wave absorption effectively. The composite of paraffin wax mixed with 10 wt% PCHMs (the shell thickness of PCHMs is 35 nm) exhibits a minimum coefficient value of -53.8 dB at 8.8 GHz, with a thickness of 3.4 mm. Besides, it is remarkable that the effective absorption bandwidth covers all the X band with as low as a 10 wt% filler ratio, compared with other spherical EM wave absorbers. The excellent EM wave absorption capability of PCHMs can be ascribed to the better impendence matching and strong EM wave attenuation constant based on tunable textural properties. Our results provide a facile strategy to tune dielectric properties of spherical carbon absorbers based on textural properties, and can be extended to other spherical absorbers.

Tunable dielectric properties of mesoporous carbon hollow microspheres via textural properties

NASA Astrophysics Data System (ADS)

Xu, Hailong; Yin, Xiaowei; Li, Zhaochen; Liu, Chenglong; Wang, Zeyu; Li, Minghang; Zhang, Litong; Cheng, Laifei

2018-05-01

In this study, mesoporous carbon hollow microspheres (PCHMs) with tunable textural properties have been prepared through a facile hard template etching method. The PCHMs were characterized by scanning electron microscopy, transmission electron microscopy, x-ray diffraction, Raman spectra, and nitrogen adsorption and desorption systems. Uniform PCHMs with shell thickness ranging from 23 nm to 55 nm are realized. PCHMs with different textural properties can regulate dielectric and electromagnetic (EM) wave absorption effectively. The composite of paraffin wax mixed with 10 wt% PCHMs (the shell thickness of PCHMs is 35 nm) exhibits a minimum coefficient value of -53.8 dB at 8.8 GHz, with a thickness of 3.4 mm. Besides, it is remarkable that the effective absorption bandwidth covers all the X band with as low as a 10 wt% filler ratio, compared with other spherical EM wave absorbers. The excellent EM wave absorption capability of PCHMs can be ascribed to the better impendence matching and strong EM wave attenuation constant based on tunable textural properties. Our results provide a facile strategy to tune dielectric properties of spherical carbon absorbers based on textural properties, and can be extended to other spherical absorbers.

Bone marrow cavity segmentation using graph-cuts with wavelet-based texture feature.

PubMed

Shigeta, Hironori; Mashita, Tomohiro; Kikuta, Junichi; Seno, Shigeto; Takemura, Haruo; Ishii, Masaru; Matsuda, Hideo

2017-10-01

Emerging bioimaging technologies enable us to capture various dynamic cellular activities [Formula: see text]. As large amounts of data are obtained these days and it is becoming unrealistic to manually process massive number of images, automatic analysis methods are required. One of the issues for automatic image segmentation is that image-taking conditions are variable. Thus, commonly, many manual inputs are required according to each image. In this paper, we propose a bone marrow cavity (BMC) segmentation method for bone images as BMC is considered to be related to the mechanism of bone remodeling, osteoporosis, and so on. To reduce manual inputs to segment BMC, we classified the texture pattern using wavelet transformation and support vector machine. We also integrated the result of texture pattern classification into the graph-cuts-based image segmentation method because texture analysis does not consider spatial continuity. Our method is applicable to a particular frame in an image sequence in which the condition of fluorescent material is variable. In the experiment, we evaluated our method with nine types of mother wavelets and several sets of scale parameters. The proposed method with graph-cuts and texture pattern classification performs well without manual inputs by a user.

Melting temperatures of MgO under high pressure determined by micro-texture observation

NASA Astrophysics Data System (ADS)

Kimura, T.; Ohfuji, H.; Nishi, M.; Irifune, T.

2016-12-01

Periclase (MgO) is the second abundant mineral after bridgmanite in the Earth's lower mantle, and its melting temperature (Tm) under pressure is important to constrain the chemical composition of ultra-deep magma formed near the mantle-core boundary. However, the melting behavior is highly controversial among previous studies: a laser-heated diamond anvil cell (LHDAC) study reported a melting curve with a dTm/dP of 30 K/GPa at zero pressure [1], while several theoretical computations gave substantially higher dTm/dP of 90 100 K/GPa [2,3]. We performed a series of LHDAC experiments for measurements of Tm of MgO under high pressure, using single crystal MgO as the starting material. The melting was detected by using micro-texture observations of the quenched samples. We found that the laser-heated area of the sample quenched from the Tm in previous LHDAC experiments [1] showed randomly aggregated granular crystals, which was not caused by melting, but by plastic deformation of the sample. This suggests that the Tms of their study were substantially underestimated. On the other hand, the sample recovered from the temperature higher by 1500-1700 K than the Tms in previous LHDAC experiments showed a characteristic internal texture comparable to the solidification texture typically shown in metal casting. We determined the Tms based on the observation of this texture up to 32 GPa. Fitting our Tms to the Simon equation yields dTm/dP of 82 K/GPa at zero pressure, which is consistent with those of the theoretical predictions (90 100 K/GPa) [2,3]. Extrapolation of the present melting curve of MgO to the pressure of the CMB (135 GPa) gives a melting temperature of 8900 K. The present steep melting slope offers the eutectic composition close to peridotite (in terms of Mg/Si ratio) throughout the lower mantle conditions. According to the model for sink/float relationship between the solid mantle and the magma [4], a considerable amount of iron (Fe/(Mg+Fe) > 0.24) is expected for the peridotitic partial melt so that it is gravitationally stable to form the ULVZs at the bottom of the lower mantle. Reference 1 A. Zerr and R. Boehler, Nature 371, 506 (1994). 2 D. Alfe, Phys. Rev. Lett. 94, 235701 (2005). 3 N. de Koker and L. Stixrude, Geophys. J. Int. 178, 162 (2009). 4 Funamori, and N. Sato, Earth Planet. Sci. Lett. 295, 435 (2010).

Perceptual compression of magnitude-detected synthetic aperture radar imagery

NASA Technical Reports Server (NTRS)

Gorman, John D.; Werness, Susan A.

1994-01-01

A perceptually-based approach for compressing synthetic aperture radar (SAR) imagery is presented. Key components of the approach are a multiresolution wavelet transform, a bit allocation mask based on an empirical human visual system (HVS) model, and hybrid scalar/vector quantization. Specifically, wavelet shrinkage techniques are used to segregate wavelet transform coefficients into three components: local means, edges, and texture. Each of these three components is then quantized separately according to a perceptually-based bit allocation scheme. Wavelet coefficients associated with local means and edges are quantized using high-rate scalar quantization while texture information is quantized using low-rate vector quantization. The impact of the perceptually-based multiresolution compression algorithm on visual image quality, impulse response, and texture properties is assessed for fine-resolution magnitude-detected SAR imagery; excellent image quality is found at bit rates at or above 1 bpp along with graceful performance degradation at rates below 1 bpp.

Clustered-dot halftoning with direct binary search.

PubMed

Goyal, Puneet; Gupta, Madhur; Staelin, Carl; Fischer, Mani; Shacham, Omri; Allebach, Jan P

2013-02-01

In this paper, we present a new algorithm for aperiodic clustered-dot halftoning based on direct binary search (DBS). The DBS optimization framework has been modified for designing clustered-dot texture, by using filters with different sizes in the initialization and update steps of the algorithm. Following an intuitive explanation of how the clustered-dot texture results from this modified framework, we derive a closed-form cost metric which, when minimized, equivalently generates stochastic clustered-dot texture. An analysis of the cost metric and its influence on the texture quality is presented, which is followed by a modification to the cost metric to reduce computational cost and to make it more suitable for screen design.

Texture-adaptive hyperspectral video acquisition system with a spatial light modulator

NASA Astrophysics Data System (ADS)

Fang, Xiaojing; Feng, Jiao; Wang, Yongjin

2014-10-01

We present a new hybrid camera system based on spatial light modulator (SLM) to capture texture-adaptive high-resolution hyperspectral video. The hybrid camera system records a hyperspectral video with low spatial resolution using a gray camera and a high-spatial resolution video using a RGB camera. The hyperspectral video is subsampled by the SLM. The subsampled points can be adaptively selected according to the texture characteristic of the scene by combining with digital imaging analysis and computational processing. In this paper, we propose an adaptive sampling method utilizing texture segmentation and wavelet transform (WT). We also demonstrate the effectiveness of the sampled pattern on the SLM with the proposed method.

Dynamic facial expression recognition based on geometric and texture features

NASA Astrophysics Data System (ADS)

Li, Ming; Wang, Zengfu

2018-04-01

Recently, dynamic facial expression recognition in videos has attracted growing attention. In this paper, we propose a novel dynamic facial expression recognition method by using geometric and texture features. In our system, the facial landmark movements and texture variations upon pairwise images are used to perform the dynamic facial expression recognition tasks. For one facial expression sequence, pairwise images are created between the first frame and each of its subsequent frames. Integration of both geometric and texture features further enhances the representation of the facial expressions. Finally, Support Vector Machine is used for facial expression recognition. Experiments conducted on the extended Cohn-Kanade database show that our proposed method can achieve a competitive performance with other methods.

Increase of Breakthrough Pressure of Cotton Fabric by Fluoropolymer/Fluoroposs Treatment

DTIC Science & Technology

2011-11-29

obtaining superhydrophobic and superolcophobic textured surfaces. Geometrical parameters based on these textures have been developed to model predicted...contact angles with liquids of varying surfaces tensions. One way of determining the robustness of the superhydrophobic state is to study the

EVALUATING DISCONTINUITIES IN COMPLEX SYSTEMS: TOWARD QUANTITATIVE MEASURE OF RESILIENCE

EPA Science Inventory

The textural discontinuity hypothesis (TDH) is based on the observation that animal body mass distributions exhibit discontinuities that may reflect the texture of the landscape available for exploitation. This idea has been extended to other complex systems, hinting that the ide...

Efficient rolling texture predictions and texture-sensitive properties of α-uranium foils

DOE PAGES

Steiner, Matthew A.; Klein, Robert W.; Calhoun, Christopher A.; ...

2017-01-01

Here, finite element (FE) analysis was used to simulate the strain history of an α-uranium foil during cold-rolling, with the sheet modeled as an isotropic elastoplastic continuum. The resulting strain history was then used as input for a viscoplastic self-consistent (VPSC) polycrystal plasticity model to simulate crystallographic texture evolution. Mid-plane textures predicted via the combined FE→VPSC approach show alignment of the (010) poles along the rolling direction (RD), and the (001) poles along the normal direction (ND) with a symmetric splitting along RD. The surface texture is similar to that of the mid-plane, but with a shear-induced asymmetry that favorsmore » one of the RD split features of the (001) pole figure. Both the mid-plane and surface textures predicted by the FE→VPSC approach agree with published experimental results for cold-rolled α-uranium plates, as well as predictions made by a more computationally intensive full-field crystal plasticity based finite element model. α-uranium foils produced by cold-rolling must typically undergo a final recrystallization anneal to restore ductility prior to their final application, resulting in significant texture evolution from the cold-rolled plate deformation texture. Using the texture measured from a foil in the final recrystallized state, coefficients of the thermal expansion and elastic stiffness tensors were calculated using a thermo-elastic self-consistent model, and the anisotropic yield loci and flow curves along the RD, TD, and ND were predicted using the VPSC code.« less

Efficient rolling texture predictions and texture-sensitive properties of α-uranium foils

DOE Office of Scientific and Technical Information (OSTI.GOV)

Steiner, Matthew A.; Klein, Robert W.; Calhoun, Christopher A.

Here, finite element (FE) analysis was used to simulate the strain history of an α-uranium foil during cold-rolling, with the sheet modeled as an isotropic elastoplastic continuum. The resulting strain history was then used as input for a viscoplastic self-consistent (VPSC) polycrystal plasticity model to simulate crystallographic texture evolution. Mid-plane textures predicted via the combined FE→VPSC approach show alignment of the (010) poles along the rolling direction (RD), and the (001) poles along the normal direction (ND) with a symmetric splitting along RD. The surface texture is similar to that of the mid-plane, but with a shear-induced asymmetry that favorsmore » one of the RD split features of the (001) pole figure. Both the mid-plane and surface textures predicted by the FE→VPSC approach agree with published experimental results for cold-rolled α-uranium plates, as well as predictions made by a more computationally intensive full-field crystal plasticity based finite element model. α-uranium foils produced by cold-rolling must typically undergo a final recrystallization anneal to restore ductility prior to their final application, resulting in significant texture evolution from the cold-rolled plate deformation texture. Using the texture measured from a foil in the final recrystallized state, coefficients of the thermal expansion and elastic stiffness tensors were calculated using a thermo-elastic self-consistent model, and the anisotropic yield loci and flow curves along the RD, TD, and ND were predicted using the VPSC code.« less

Bridges between multiple-point geostatistics and texture synthesis: Review and guidelines for future research

NASA Astrophysics Data System (ADS)

Mariethoz, Gregoire; Lefebvre, Sylvain

2014-05-01

Multiple-Point Simulations (MPS) is a family of geostatistical tools that has received a lot of attention in recent years for the characterization of spatial phenomena in geosciences. It relies on the definition of training images to represent a given type of spatial variability, or texture. We show that the algorithmic tools used are similar in many ways to techniques developed in computer graphics, where there is a need to generate large amounts of realistic textures for applications such as video games and animated movies. Similarly to MPS, these texture synthesis methods use training images, or exemplars, to generate realistic-looking graphical textures. Both domains of multiple-point geostatistics and example-based texture synthesis present similarities in their historic development and share similar concepts. These disciplines have however remained separated, and as a result significant algorithmic innovations in each discipline have not been universally adopted. Texture synthesis algorithms present drastically increased computational efficiency, patterns reproduction and user control. At the same time, MPS developed ways to condition models to spatial data and to produce 3D stochastic realizations, which have not been thoroughly investigated in the field of texture synthesis. In this paper we review the possible links between these disciplines and show the potential and limitations of using concepts and approaches from texture synthesis in MPS. We also provide guidelines on how recent developments could benefit both fields of research, and what challenges remain open.

Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization

PubMed Central

Pérez-Beteta, Julián; Martínez-González, Alicia; Martino, Juan; Velasquez, Carlos; Arana, Estanislao; Pérez-García, Víctor M.

2017-01-01

Purpose Textural measures have been widely explored as imaging biomarkers in cancer. However, their robustness under dynamic range and spatial resolution changes in brain 3D magnetic resonance images (MRI) has not been assessed. The aim of this work was to study potential variations of textural measures due to changes in MRI protocols. Materials and methods Twenty patients harboring glioblastoma with pretreatment 3D T1-weighted MRIs were included in the study. Four different spatial resolution combinations and three dynamic ranges were studied for each patient. Sixteen three-dimensional textural heterogeneity measures were computed for each patient and configuration including co-occurrence matrices (CM) features and run-length matrices (RLM) features. The coefficient of variation was used to assess the robustness of the measures in two series of experiments corresponding to (i) changing the dynamic range and (ii) changing the matrix size. Results No textural measures were robust under dynamic range changes. Entropy was the only textural feature robust under spatial resolution changes (coefficient of variation under 10% in all cases). Conclusion Textural measures of three-dimensional brain tumor images are not robust neither under dynamic range nor under matrix size changes. Standards should be harmonized to use textural features as imaging biomarkers in radiomic-based studies. The implications of this work go beyond the specific tumor type studied here and pose the need for standardization in textural feature calculation of oncological images. PMID:28586353

Cooking Methods for a Soft Diet Using Chicken Based on Food Texture Analysis.

PubMed

Watanabe, Emi; Maeno, Masami; Kayashita, Jun; Miyamoto, Ken-Ichi; Kogirima, Miho

2017-01-01

Undernutrition caused by difficulties in masticating is of growing concern among the elderly. Soft diets are often served at nursing homes; however, the styles differ with nursing homes. Improperly modified food texture and consistency may lead to further loss of nutritive value. Therefore, we developed a method to produce a soft diet using chicken. The texture-modified chicken was prepared by boiling a mixture of minced chicken and additive foodstuff that softened the meat. The best food additive was determined through testing cooking process, size after modification and texture. The optimum proportions of each component in the mixture were determined measuring food texture using a creep meter. Teriyaki chicken was cooked using the texture-modified chicken, and provided to a nursing home. The amount of food intake by elderly residents was subsequently surveyed. This study involved 22 residents (1 man and 21 women; mean age 91.4±5.3 y). Consequently, yakifu, which was made from wheat gluten, was the most suitable additive foodstuff. The hardness of the texture-modified chicken, with proportions of minced chicken, yakifu, and water being 50%, 10%, and 40% respectively, was under 40,000 N/m 2 . The intake amount of the texture-modified chicken of subjects whose intake amount of conventional chicken using chicken thigh was not 100% was significantly higher. These findings suggest that properly modified food textures could contribute to improve the quality of meals by preventing undernutrition among the elderly with mastication difficulties.

Efficient rolling texture predictions and texture-sensitive thermomechanical properties of α-uranium foils

NASA Astrophysics Data System (ADS)

Steiner, Matthew A.; Klein, Robert W.; Calhoun, Christopher A.; Knezevic, Marko; Garlea, Elena; Agnew, Sean R.

2017-11-01

Finite element (FE) analysis was used to simulate the strain history of an α-uranium foil during cold straight-rolling, with the sheet modeled as an isotropic elastoplastic continuum. The resulting strain history was then used as input for a viscoplastic self-consistent (VPSC) polycrystal plasticity model to simulate crystallographic texture evolution. Mid-plane textures predicted via the combined FE→VPSC approach show alignment of the (010) poles along the rolling direction (RD), and the (001) poles along the normal direction (ND) with a symmetric splitting along RD. The surface texture is similar to that of the mid-plane, but with a shear-induced asymmetry that favors one of the RD split features of the (001) pole figure. Both the mid-plane and surface textures predicted by the FE→VPSC approach agree with published experimental results for cold straight-rolled α-uranium plates, as well as predictions made by a more computationally intensive full-field crystal plasticity based finite element model. α-uranium foils produced by cold-rolling must typically undergo a recrystallization anneal to restore ductility prior to their final application, resulting in significant texture evolution from the cold-rolled plate deformation texture. Using the texture measured from a foil in the final recrystallized state, coefficients of thermal expansion and the elastic stiffness tensors were calculated using a thermo-elastic self-consistent model, and the anisotropic yield loci and flow curves along the RD, TD, and ND were predicted using the VPSC code.

Chemical, mineralogical and textural systematics of non-mare melt rocks: Implications for lunar impact and volcanic processes

NASA Technical Reports Server (NTRS)

Irving, A. J.

1975-01-01

Based on a synthesis of chemical data for over 200 samples, the nonmare rocks with fine grained melt textures can be classified into 7 major groups: anorthositic basalts, troctolitic basalts, VHA basalts, Apollo 14-type KREEP basalts, Apollo 15-type KREEP basalts, Apollo 17-type KREEP basalts, and aluminous mare basalts. Review of chemical, mineralogical, textural and experimental evidence leads to preferred hypotheses for the origins of these rocks; those hypotheses are discussed in detail.

Considerations in the use of biologic grafts and alloplastic implants in facial plastic and reconstructive surgery.

PubMed

Boyce, R G; Toriumi, D M

1992-01-01

Surgical changes in the contour of soft tissue and bone of the craniomaxillofacial structures may require use of a biologic graft or alloplastic implant. Autologous materials are preferred; however, the harvesting procedure, donor site, and its associated morbidity are the disadvantages of using autografts. There are numerous types of alloplastic implants and they all differ in how they interact with host tissues. Factors such as implant texture, ability to integrate with host tissues, and rate of resorption all influence the overall success of different implants. In this article, we discuss some considerations in the use of biologic grafts and alloplastic implants in facial plastic and reconstructive surgery.

Comparative study of four antacids.

PubMed Central

Jacyna, M. R.; Boyd, E. J.; Wormsley, K. G.

1984-01-01

Four antacid preparations have been studied in a stratified, randomized, double-blind trial to evaluate criteria which determine patients' acceptance of this type of therapy. There was a considerable range of judgements about palatability, but preference was determined not only by factors such as the smell, taste, texture and after-taste of the preparation, but also by the order in which the antacids were tested and by the age and sex of the patient. The preparations also differed considerably in acid-neutralizing capacity and ability to bind bile salts, as well as cost. We conclude that individuals requiring antacid therapy should be allowed to chose from among a range of preparations, in order to maximize compliance. PMID:6091079

Application of neutron diffraction in characterization of texture evolution during high-temperature creep in magnesium alloys

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vogel, Sven C; Sediako, Dimitry; Shook, S

2010-01-01

A good combination of room-temperature and elevated temperature strength and ductility, good salt-spray corrosion resistance and exceUent diecastability are frequently among the main considerations in development of a new alloy. Unfortunately, there has been much lesser effort in development of wrought-stock alloys for high temperature applications. Extrudability and high temperature performance of wrought material becomes an important factor in an effort to develop new wrought alloys and processing technologies. This paper shows some results received in creep testing and studies of in-creep texture evolution for several wrought magnesium alloys developed for use in elevated-temperature applications. These studies were performed usingmore » E3 neutron spectrometer of the Canadian Neutron Beam Centre in Chalk River, ON, and HIPPO time-of-flight (TOF) spectrometer at Los Alamos Neutron Science Center, NM.« less

Automatic brain MR image denoising based on texture feature-based artificial neural networks.

PubMed

Chang, Yu-Ning; Chang, Herng-Hua

2015-01-01

Noise is one of the main sources of quality deterioration not only for visual inspection but also in computerized processing in brain magnetic resonance (MR) image analysis such as tissue classification, segmentation and registration. Accordingly, noise removal in brain MR images is important for a wide variety of subsequent processing applications. However, most existing denoising algorithms require laborious tuning of parameters that are often sensitive to specific image features and textures. Automation of these parameters through artificial intelligence techniques will be highly beneficial. In the present study, an artificial neural network associated with image texture feature analysis is proposed to establish a predictable parameter model and automate the denoising procedure. In the proposed approach, a total of 83 image attributes were extracted based on four categories: 1) Basic image statistics. 2) Gray-level co-occurrence matrix (GLCM). 3) Gray-level run-length matrix (GLRLM) and 4) Tamura texture features. To obtain the ranking of discrimination in these texture features, a paired-samples t-test was applied to each individual image feature computed in every image. Subsequently, the sequential forward selection (SFS) method was used to select the best texture features according to the ranking of discrimination. The selected optimal features were further incorporated into a back propagation neural network to establish a predictable parameter model. A wide variety of MR images with various scenarios were adopted to evaluate the performance of the proposed framework. Experimental results indicated that this new automation system accurately predicted the bilateral filtering parameters and effectively removed the noise in a number of MR images. Comparing to the manually tuned filtering process, our approach not only produced better denoised results but also saved significant processing time.

Validation of Satellite-Based Objective Overshooting Cloud-Top Detection Methods Using CloudSat Cloud Profiling Radar Observations

NASA Technical Reports Server (NTRS)

Bedka, Kristopher M.; Dworak, Richard; Brunner, Jason; Feltz, Wayne

2012-01-01

Two satellite infrared-based overshooting convective cloud-top (OT) detection methods have recently been described in the literature: 1) the 11-mm infrared window channel texture (IRW texture) method, which uses IRW channel brightness temperature (BT) spatial gradients and thresholds, and 2) the water vapor minus IRW BT difference (WV-IRW BTD). While both methods show good performance in published case study examples, it is important to quantitatively validate these methods relative to overshooting top events across the globe. Unfortunately, no overshooting top database currently exists that could be used in such study. This study examines National Aeronautics and Space Administration CloudSat Cloud Profiling Radar data to develop an OT detection validation database that is used to evaluate the IRW-texture and WV-IRW BTD OT detection methods. CloudSat data were manually examined over a 1.5-yr period to identify cases in which the cloud top penetrates above the tropopause height defined by a numerical weather prediction model and the surrounding cirrus anvil cloud top, producing 111 confirmed overshooting top events. When applied to Moderate Resolution Imaging Spectroradiometer (MODIS)-based Geostationary Operational Environmental Satellite-R Series (GOES-R) Advanced Baseline Imager proxy data, the IRW-texture (WV-IRW BTD) method offered a 76% (96%) probability of OT detection (POD) and 16% (81%) false-alarm ratio. Case study examples show that WV-IRW BTD.0 K identifies much of the deep convective cloud top, while the IRW-texture method focuses only on regions with a spatial scale near that of commonly observed OTs. The POD decreases by 20% when IRW-texture is applied to current geostationary imager data, highlighting the importance of imager spatial resolution for observing and detecting OT regions.

Texture in thin film silicides and germanides: A review

DOE Office of Scientific and Technical Information (OSTI.GOV)

De Schutter, B., E-mail: bob.deschutter@ugent.be; De Keyser, K.; Detavernier, C.

Silicides and germanides are compounds consisting of a metal and silicon or germanium. In the microelectronics industry, silicides are the material of choice for contacting silicon based devices (over the years, CoSi{sub 2}, C54-TiSi{sub 2}, and NiSi have been adopted), while germanides are considered as a top candidate for contacting future germanium based electronics. Since also strain engineering through the use of Si{sub 1−x}Ge{sub x} in the source/drain/gate regions of MOSFET devices is an important technique for improving device characteristics in modern Si-based microelectronics industry, a profound understanding of the formation of silicide/germanide contacts to silicon and germanium is ofmore » utmost importance. The crystallographic texture of these films, which is defined as the statistical distribution of the orientation of the grains in the film, has been the subject of scientific studies since the 1970s. Different types of texture like epitaxy, axiotaxy, fiber, or combinations thereof have been observed in such films. In recent years, it has become increasingly clear that film texture can have a profound influence on the formation and stability of silicide/germanide contacts, as it controls the type and orientation of grain boundaries (affecting diffusion and agglomeration) and the interface energy (affecting nucleation during the solid-state reaction). Furthermore, the texture also has an impact on the electrical characteristics of the contact, as the orientation and size of individual grains influences functional properties such as contact resistance and sheet resistance and will induce local variations in strain and Schottky barrier height. This review aims to give a comprehensive overview of the scientific work that has been published in the field of texture studies on thin film silicide/germanide contacts.« less

Improvement of luster consistency between the p-Pad and the n-Pad of GaN-based light-emitting diodes via the under-etching process

NASA Astrophysics Data System (ADS)

Zheng, Chenju; Lv, Jiajiang; Zhou, Shengjun; Liu, Sheng

2017-04-01

For improvement of the light extraction efficiency of GaN-based lateral light-emitting diodes (LEDs), a p-GaN surface was textured through a low-temperature (850 °C) p-GaN growth process. However, the p-GaN texturing process caused luster inconsistency between the n-pad and the p-pad due to the roughness difference between the indium-tin oxide (ITO) and the n-GaN beneath the pads, which decreased the image recognition rate and accuracy during the wire bonding process for LED packaging. Therefore, an under-etching process was proposed to improve the luster consistency between the p-pad and the n-pad of GaN-based LEDs with a naturally textured p-GaN surface. The under-etching process decreased the roughness of the exposed n-GaN surface from 109 nm to 73.1 nm, which was similar to the roughness (74.8 nm) of the ITO surface. Optical microscopy showed that LEDs with a naturally textured p-GaN surface exhibited excellent luster consistency between the n-pad and the p-pad after the proposed under-etching process had been applied. Further analysis indicated that the LEDs with a naturally textured p-GaN surface showed no degradation of optical or the electrical performance after the proposed under-etching process had been applied. At a 20-mA injection current, the light output power of a LED with naturally a textured p-GaN surface was 8.7% higher than that of a LED with a smooth p-GaN surface.

Texture in thin film silicides and germanides: A review

NASA Astrophysics Data System (ADS)

De Schutter, B.; De Keyser, K.; Lavoie, C.; Detavernier, C.

2016-09-01

Silicides and germanides are compounds consisting of a metal and silicon or germanium. In the microelectronics industry, silicides are the material of choice for contacting silicon based devices (over the years, CoSi2, C54-TiSi2, and NiSi have been adopted), while germanides are considered as a top candidate for contacting future germanium based electronics. Since also strain engineering through the use of Si1-xGex in the source/drain/gate regions of MOSFET devices is an important technique for improving device characteristics in modern Si-based microelectronics industry, a profound understanding of the formation of silicide/germanide contacts to silicon and germanium is of utmost importance. The crystallographic texture of these films, which is defined as the statistical distribution of the orientation of the grains in the film, has been the subject of scientific studies since the 1970s. Different types of texture like epitaxy, axiotaxy, fiber, or combinations thereof have been observed in such films. In recent years, it has become increasingly clear that film texture can have a profound influence on the formation and stability of silicide/germanide contacts, as it controls the type and orientation of grain boundaries (affecting diffusion and agglomeration) and the interface energy (affecting nucleation during the solid-state reaction). Furthermore, the texture also has an impact on the electrical characteristics of the contact, as the orientation and size of individual grains influences functional properties such as contact resistance and sheet resistance and will induce local variations in strain and Schottky barrier height. This review aims to give a comprehensive overview of the scientific work that has been published in the field of texture studies on thin film silicide/germanide contacts.

Machine learning-based quantitative texture analysis of CT images of small renal masses: Differentiation of angiomyolipoma without visible fat from renal cell carcinoma.

PubMed

Feng, Zhichao; Rong, Pengfei; Cao, Peng; Zhou, Qingyu; Zhu, Wenwei; Yan, Zhimin; Liu, Qianyun; Wang, Wei

2018-04-01

To evaluate the diagnostic performance of machine-learning based quantitative texture analysis of CT images to differentiate small (≤ 4 cm) angiomyolipoma without visible fat (AMLwvf) from renal cell carcinoma (RCC). This single-institutional retrospective study included 58 patients with pathologically proven small renal mass (17 in AMLwvf and 41 in RCC groups). Texture features were extracted from the largest possible tumorous regions of interest (ROIs) by manual segmentation in preoperative three-phase CT images. Interobserver reliability and the Mann-Whitney U test were applied to select features preliminarily. Then support vector machine with recursive feature elimination (SVM-RFE) and synthetic minority oversampling technique (SMOTE) were adopted to establish discriminative classifiers, and the performance of classifiers was assessed. Of the 42 extracted features, 16 candidate features showed significant intergroup differences (P < 0.05) and had good interobserver agreement. An optimal feature subset including 11 features was further selected by the SVM-RFE method. The SVM-RFE+SMOTE classifier achieved the best performance in discriminating between small AMLwvf and RCC, with the highest accuracy, sensitivity, specificity and AUC of 93.9 %, 87.8 %, 100 % and 0.955, respectively. Machine learning analysis of CT texture features can facilitate the accurate differentiation of small AMLwvf from RCC. • Although conventional CT is useful for diagnosis of SRMs, it has limitations. • Machine-learning based CT texture analysis facilitate differentiation of small AMLwvf from RCC. • The highest accuracy of SVM-RFE+SMOTE classifier reached 93.9 %. • Texture analysis combined with machine-learning methods might spare unnecessary surgery for AMLwvf.

Textural characterization of histopathological images for oral sub-mucous fibrosis detection.

PubMed

Krishnan, M Muthu Rama; Shah, Pratik; Choudhary, Anirudh; Chakraborty, Chandan; Paul, Ranjan Rashmi; Ray, Ajoy K

2011-10-01

In the field of quantitative microscopy, textural information plays a significant role very often in tissue characterization and diagnosis, in addition to morphology and intensity. The aim of this work is to improve the classification accuracy based on textural features for the development of a computer assisted screening of oral sub-mucous fibrosis (OSF). In fact, a systematic approach is introduced in order to grade the histopathological tissue sections into normal, OSF without dysplasia and OSF with dysplasia, which would help the oral onco-pathologists to screen the subjects rapidly. In totality, 71 textural features are extracted from epithelial region of the tissue sections using various wavelet families, Gabor-wavelet, local binary pattern, fractal dimension and Brownian motion curve, followed by preprocessing and segmentation. Wavelet families contribute a common set of 9 features, out of which 8 are significant and other 61 out of 62 obtained from the rest of the extractors are also statistically significant (p<0.05) in discriminating the three stages. Based on mean distance criteria, the best wavelet family (i.e., biorthogonal3.1 (bior3.1)) is selected for classifier design. support vector machine (SVM) is trained by 146 samples based on 69 textural features and its classification accuracy is computed for each of the combinations of wavelet family and rest of the extractors. Finally, it has been investigated that bior3.1 wavelet coefficients leads to higher accuracy (88.38%) in combination with LBP and Gabor wavelet features through three-fold cross validation. Results are shown and discussed in detail. It is shown that combining more than one texture measure instead of using just one might improve the overall accuracy. Copyright © 2011 Elsevier Ltd. All rights reserved.

Critical heat flux maxima during boiling crisis on textured surfaces

PubMed Central

Dhillon, Navdeep Singh; Buongiorno, Jacopo; Varanasi, Kripa K.

2015-01-01

Enhancing the critical heat flux (CHF) of industrial boilers by surface texturing can lead to substantial energy savings and global reduction in greenhouse gas emissions, but fundamentally this phenomenon is not well understood. Prior studies on boiling crisis indicate that CHF monotonically increases with increasing texture density. Here we report on the existence of maxima in CHF enhancement at intermediate texture density using measurements on parametrically designed plain and nano-textured micropillar surfaces. Using high-speed optical and infrared imaging, we study the dynamics of dry spot heating and rewetting phenomena and reveal that the dry spot heating timescale is of the same order as that of the gravity and liquid imbibition-induced dry spot rewetting timescale. Based on these insights, we develop a coupled thermal-hydraulic model that relates CHF enhancement to rewetting of a hot dry spot on the boiling surface, thereby revealing the mechanism governing the hitherto unknown CHF enhancement maxima. PMID:26346098

Measurement of Vibrated Bulk Density of Coke Particle Blends Using Image Texture Analysis

NASA Astrophysics Data System (ADS)

Azari, Kamran; Bogoya-Forero, Wilinthon; Duchesne, Carl; Tessier, Jayson

2017-09-01

A rapid and nondestructive machine vision sensor was developed for predicting the vibrated bulk density (VBD) of petroleum coke particles based on image texture analysis. It could be used for making corrective adjustments to a paste plant operation to reduce green anode variability (e.g., changes in binder demand). Wavelet texture analysis (WTA) and gray level co-occurrence matrix (GLCM) algorithms were used jointly for extracting the surface textural features of coke aggregates from images. These were correlated with the VBD using partial least-squares (PLS) regression. Coke samples of several sizes and from different sources were used to test the sensor. Variations in the coke surface texture introduced by coke size and source allowed for making good predictions of the VBD of individual coke samples and mixtures of them (blends involving two sources and different sizes). Promising results were also obtained for coke blends collected from an industrial-baked carbon anode manufacturer.

X-ray texture analysis of paper coating pigments and the correlation with chemical composition analysis

NASA Astrophysics Data System (ADS)

Roine, J.; Tenho, M.; Murtomaa, M.; Lehto, V.-P.; Kansanaho, R.

2007-10-01

The present research experiments the applicability of x-ray texture analysis in investigating the properties of paper coatings. The preferred orientations of kaolin, talc, ground calcium carbonate, and precipitated calcium carbonate particles used in four different paper coatings were determined qualitatively based on the measured crystal orientation data. The extent of the orientation, namely, the degree of the texture of each pigment, was characterized quantitatively using a single parameter. As a result, the effect of paper calendering is clearly seen as an increase on the degree of texture of the coating pigments. The effect of calendering on the preferred orientation of kaolin was also evident in an independent energy dispersive spectrometer analysis on micrometer scale and an electron spectroscopy for chemical analysis on nanometer scale. Thus, the present work proves x-ray texture analysis to be a potential research tool for characterizing the properties of paper coating layers.

Shear-Coupled Grain Growth and Texture Development in a Nanocrystalline Ni-Fe Alloy during Cold Rolling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Li; Ungár, Tamás; Toth, Laszlo S.

The evolution of texture, grain size, grain shape, dislocation and twin density has been determined by synchrotron X-ray diffraction and line profile analysis in a nanocrystalline Ni- Fe alloy after cold rolling along different directions related to the initial fiber and the long axis of grains. The texture evolution has been simulated by the Taylor-type relaxed constraints viscoplastic polycrystal model. The simulations were based on the activity of partial dislocations in correlation with the experimental results of dislocation density determination. The concept of stress-induced shear-coupling is supported and strengthened by both the texture simulations and the experimentally determined evolution ofmore » the microstructure parameters. Grain-growth and texture evolution are shown to proceed by the shear-coupling mechanism supported by dislocation activity as long as the grain size is not smaller than about 20 nm.« less

Texture analysis of Napoleonic War Era copper bolts

NASA Astrophysics Data System (ADS)

Malamud, Florencia; Northover, Shirley; James, Jon; Northover, Peter; Kelleher, Joe

2016-04-01

Neutron diffraction techniques are suitable for volume texture analyses due to high penetration of thermal neutrons in most materials. We have implemented a new data analysis methodology that employed the spatial resolution achievable by a time-of-flight neutron strain scanner to non-destructively determine the crystallographic texture at selected locations within a macroscopic sample. The method is based on defining the orientation distribution function of the crystallites from several incomplete pole figures, and it has been implemented on ENGIN-X, a neutron strain scanner at the Isis Facility in the UK. Here, we demonstrate the application of this new texture analysis methodology in determining the crystallographic texture at selected locations within museum quality archaeological objects up to 1 m in length. The results were verified using samples of similar, but less valuable, objects by comparing the results of applying this method with those obtained using both electron backscatter diffraction and X-ray diffraction on their cross sections.

Biometric recognition via texture features of eye movement trajectories in a visual searching task.

PubMed

Li, Chunyong; Xue, Jiguo; Quan, Cheng; Yue, Jingwei; Zhang, Chenggang

2018-01-01

Biometric recognition technology based on eye-movement dynamics has been in development for more than ten years. Different visual tasks, feature extraction and feature recognition methods are proposed to improve the performance of eye movement biometric system. However, the correct identification and verification rates, especially in long-term experiments, as well as the effects of visual tasks and eye trackers' temporal and spatial resolution are still the foremost considerations in eye movement biometrics. With a focus on these issues, we proposed a new visual searching task for eye movement data collection and a new class of eye movement features for biometric recognition. In order to demonstrate the improvement of this visual searching task being used in eye movement biometrics, three other eye movement feature extraction methods were also tested on our eye movement datasets. Compared with the original results, all three methods yielded better results as expected. In addition, the biometric performance of these four feature extraction methods was also compared using the equal error rate (EER) and Rank-1 identification rate (Rank-1 IR), and the texture features introduced in this paper were ultimately shown to offer some advantages with regard to long-term stability and robustness over time and spatial precision. Finally, the results of different combinations of these methods with a score-level fusion method indicated that multi-biometric methods perform better in most cases.

Biometric recognition via texture features of eye movement trajectories in a visual searching task

PubMed Central

Li, Chunyong; Xue, Jiguo; Quan, Cheng; Yue, Jingwei

2018-01-01

Biometric recognition technology based on eye-movement dynamics has been in development for more than ten years. Different visual tasks, feature extraction and feature recognition methods are proposed to improve the performance of eye movement biometric system. However, the correct identification and verification rates, especially in long-term experiments, as well as the effects of visual tasks and eye trackers’ temporal and spatial resolution are still the foremost considerations in eye movement biometrics. With a focus on these issues, we proposed a new visual searching task for eye movement data collection and a new class of eye movement features for biometric recognition. In order to demonstrate the improvement of this visual searching task being used in eye movement biometrics, three other eye movement feature extraction methods were also tested on our eye movement datasets. Compared with the original results, all three methods yielded better results as expected. In addition, the biometric performance of these four feature extraction methods was also compared using the equal error rate (EER) and Rank-1 identification rate (Rank-1 IR), and the texture features introduced in this paper were ultimately shown to offer some advantages with regard to long-term stability and robustness over time and spatial precision. Finally, the results of different combinations of these methods with a score-level fusion method indicated that multi-biometric methods perform better in most cases. PMID:29617383

General Approach for Rock Classification Based on Digital Image Analysis of Electrical Borehole Wall Images

NASA Astrophysics Data System (ADS)

Linek, M.; Jungmann, M.; Berlage, T.; Clauser, C.

2005-12-01

Within the Ocean Drilling Program (ODP), image logging tools have been routinely deployed such as the Formation MicroScanner (FMS) or the Resistivity-At-Bit (RAB) tools. Both logging methods are based on resistivity measurements at the borehole wall and therefore are sensitive to conductivity contrasts, which are mapped in color scale images. These images are commonly used to study the structure of the sedimentary rocks and the oceanic crust (petrologic fabric, fractures, veins, etc.). So far, mapping of lithology from electrical images is purely based on visual inspection and subjective interpretation. We apply digital image analysis on electrical borehole wall images in order to develop a method, which augments objective rock identification. We focus on supervised textural pattern recognition which studies the spatial gray level distribution with respect to certain rock types. FMS image intervals of rock classes known from core data are taken in order to train textural characteristics for each class. A so-called gray level co-occurrence matrix is computed by counting the occurrence of a pair of gray levels that are a certain distant apart. Once the matrix for an image interval is computed, we calculate the image contrast, homogeneity, energy, and entropy. We assign characteristic textural features to different rock types by reducing the image information into a small set of descriptive features. Once a discriminating set of texture features for each rock type is found, we are able to discriminate the entire FMS images regarding the trained rock type classification. A rock classification based on texture features enables quantitative lithology mapping and is characterized by a high repeatability, in contrast to a purely visual subjective image interpretation. We show examples for the rock classification between breccias, pillows, massive units, and horizontally bedded tuffs based on ODP image data.

Texture analysis on the fluence map to evaluate the degree of modulation for volumetric modulated arc therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, So-Yeon; Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul 110-744; Biomedical Research Institute, Seoul National University College of Medicine, Seoul 110-744

Purpose: Texture analysis on fluence maps was performed to evaluate the degree of modulation for volumetric modulated arc therapy (VMAT) plans. Methods: A total of six textural features including angular second moment, inverse difference moment, contrast, variance, correlation, and entropy were calculated for fluence maps generated from 20 prostate and 20 head and neck VMAT plans. For each of the textural features, particular displacement distances (d) of 1, 5, and 10 were adopted. To investigate the deliverability of each VMAT plan, gamma passing rates of pretreatment quality assurance, and differences in modulating parameters such as multileaf collimator (MLC) positions, gantrymore » angles, and monitor units at each control point between VMAT plans and dynamic log files registered by the Linac control system during delivery were acquired. Furthermore, differences between the original VMAT plan and the plan reconstructed from the dynamic log files were also investigated. To test the performance of the textural features as indicators for the modulation degree of VMAT plans, Spearman’s rank correlation coefficients (r{sub s}) with the plan deliverability were calculated. For comparison purposes, conventional modulation indices for VMAT including the modulation complexity score for VMAT, leaf travel modulation complexity score, and modulation index supporting station parameter optimized radiation therapy (MI{sub SPORT}) were calculated, and their correlations were analyzed in the same way. Results: There was no particular textural feature which always showed superior correlations with every type of plan deliverability. Considering the results comprehensively, contrast (d = 1) and variance (d = 1) generally showed considerable correlations with every type of plan deliverability. These textural features always showed higher correlations to the plan deliverability than did the conventional modulation indices, except in the case of modulating parameter differences. The r{sub s} values of contrast to the global gamma passing rates with criteria of 2%/2 mm, 2%/1 mm, and 1%/2 mm were 0.536, 0.473, and 0.718, respectively. The respective values for variance were 0.551, 0.481, and 0.688. In the case of local gamma passing rates, the r{sub s} values of contrast were 0.547, 0.578, and 0.620, respectively, and those of variance were 0.519, 0.527, and 0.569. All of the r{sub s} values in those cases were statistically significant (p < 0.003). In the cases of global and local gamma passing rates, MI{sub SPORT} showed the highest correlations among the conventional modulation indices. For global passing rates, r{sub s} values of MI{sub SPORT} were −0.420, −0.330, and −0.632, respectively, and those for local passing rates were −0.455, −0.490 and −0.502. The values of r{sub s} of contrast, variance, and MI{sub SPORT} with the MLC errors were −0.863, −0.828, and 0.795, respectively, all with statistical significances (p < 0.001). The correlations with statistical significances between variance and dose-volumetric differences were observed more frequently than the others. Conclusions: The contrast (d = 1) and variance (d = 1) calculated from fluence maps of VMAT plans showed considerable correlations with the plan deliverability, indicating their potential use as indicators for assessing the degree of modulation of VMAT plans. Both contrast and variance consistently showed better performance than the conventional modulation indices for VMAT.« less

Development of type transfer functions for regional-scale nonpoint source groundwater vulnerability assessments

NASA Astrophysics Data System (ADS)

Stewart, Iris T.; Loague, Keith

2003-12-01

Groundwater vulnerability assessments of nonpoint source agrochemical contamination at regional scales are either qualitative in nature or require prohibitively costly computational efforts. By contrast, the type transfer function (TTF) modeling approach for vadose zone pesticide leaching presented here estimates solute concentrations at a depth of interest, only uses available soil survey, climatic, and irrigation information, and requires minimal computational cost for application. TTFs are soil texture based travel time probability density functions that describe a characteristic leaching behavior for soil profiles with similar soil hydraulic properties. Seven sets of TTFs, representing different levels of upscaling, were developed for six loam soil textural classes with the aid of simulated breakthrough curves from synthetic data sets. For each TTF set, TTFs were determined from a group or subgroup of breakthrough curves for each soil texture by identifying the effective parameters of the function that described the average leaching behavior of the group. The grouping of the breakthrough curves was based on the TTF index, a measure of the magnitude of the peak concentration, the peak arrival time, and the concentration spread. Comparison to process-based simulations show that the TTFs perform well with respect to mass balance, concentration magnitude, and the timing of concentration peaks. Sets of TTFs based on individual soil textures perform better for all the evaluation criteria than sets that span all textures. As prediction accuracy and computational cost increase with the number of TTFs in a set, the selection of a TTF set is determined by a given application.

Technology and production of plant-based meat analogs with authentic texture

USDA-ARS?s Scientific Manuscript database

Extrusion cooking has been widely used in modern food industry due to its versatility, high productivity, energy efficiency and low cost. Well-known applications include breakfast cereals, pasta, snacks, confectionery products, and textured vegetable proteins. Most applications take place at low ...

The relative contribution of ferroelastic and ferroelectric texture to the character of a hard PZT ceramic

NASA Astrophysics Data System (ADS)

Key, Thomas Stallings

The development of ferroelastic (90°) texture in addition to ferroelectric (180°) texture is essential to maximizing the piezoelectric properties of many hard tetragonal PZTs, including Piezoetechnologies K270. Ferroelastic texture results from motion of domain walls that is dependent on an individual crystals orientation. Increases in ferroelastic texture raises the maximum net polarization that can be achieved by changes in ferroelectric texture. By studying a hard PZT poled under various temperature conditions, insight was gained into factors affecting the development of ferroelastic texture and how ferroelastic texture contributes to piezoelectric properties. Depinning proved to be the major barrier to preventing ferroelastic domain wall motion where strain based domain interactions and polar defect complexes on the domain level appear to be the dominant factors. Insight into the affect of increased domain texture on the relationship between the increasing magnitude of the remnant polarization (|Pr|) and the magnitude of the coercive field (|EC|) was gained by plotting |EC| vs. |Pr| as a function of poling time for a variety of poling temperatures. At low |Pr| values, |EC| increased rapidly as a function of increases in |Pr| regardless of the poling temperature. This relationship was characteristic of samples poled at 25 °C where increases in ferroelastic texture were largely suppressed. Because increases in polarization were still observable changes in ferroelectric texture most responsible for the polarization increase and like play a strong role in the initial |EC| vs. |Pr| relationship. As |Pr| increased beyond 5 to 8 iC/cm2, the slope of |EC| vs. |Pr| decreased where the reduction in slope increased with poling temperature. This only occurred in samples poled at elevated temperatures where ferroelastic texture was know to ultimately develop during the poling process, leading to the suggestion that the change in slope was due to increases in combined ferroelectric and ferroelastic texture. Lastly, it was found that electric field induced increases in ferroelectric texture by poling at 25 °C occurs while ferroelastic domain wall motion is largely suppressed. This change in ferroelectric texture severely hinders the rate at which subsequent ferroelastic domain wall motion can be induced during poling at elevated temperatures below TC, suggesting that hard PZT samples should be preheated to the poling temperature before poling begins.

Microstructure, microtexture and precipitation in the ultrafine-grained surface layer of an Al-Zn-Mg-Cu alloy processed by sliding friction treatment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Yanxia

2017-01-15

Precipitate redistribution and texture evolution are usually two concurrent aspects accompanying grain refinement induced by various surface treatment. However, the detailed precipitate redistribution characteristics and process, as well as crystallographic texture in the surface refined grain layer, are still far from full understanding. In this study, we focused on the microstructural and crystallographic features of the sliding friction treatment (SFT) induced surface deformation layer in a 7050 aluminum alloy. With the combination of transmission electron microscopy (TEM) and high angle angular dark field scanning TEM (HAADF-STEM) observations, a surface ultrafine grain (UFG) layer composed of both equiaxed and lamellar ultrafinemore » grains and decorated by high density of coarse grain boundary precipitates (GBPs) were revealed. Further precession electron diffraction (PED) assisted orientation mapping unraveled that high angle grain boundaries rather than low angle grain boundaries are the most favorable nucleation sites for GBPs. The prominent precipitate redistribution can be divided into three successive and interrelated stages, i.e. the mechanically induced precipitate dissolution, solute diffusion and reprecipitation. The quantitative prediction based on pipe diffusion along dislocations and grain boundary diffusion proved the distribution feasibility of GBPs around UFGs. Based on PED and electron backscatter diffraction (EBSD) analyses, the crystallographic texture of the surface UFG layer was identified as a shear texture composed of major rotated cube texture (001) 〈110〉 and minor (111) 〈112〉, while that of the adjoining lamellar coarse grained matrix was pure brass. The SFT induced surface severe shear deformation is responsible for texture evolution. - Highlights: •The surface ultrafine grain layer in a 7050 aluminum alloy was focused. •Precipitate redistribution and texture evolution were discussed. •The quantitative prediction proved the distribution feasibility of GBPs. •Precession electron diffraction orientation mapping showed a shear texture.« less

Building damage assessment from PolSAR data using texture parameters of statistical model

NASA Astrophysics Data System (ADS)

Li, Linlin; Liu, Xiuguo; Chen, Qihao; Yang, Shuai

2018-04-01

Accurate building damage assessment is essential in providing decision support for disaster relief and reconstruction. Polarimetric synthetic aperture radar (PolSAR) has become one of the most effective means of building damage assessment, due to its all-day/all-weather ability and richer backscatter information of targets. However, intact buildings that are not parallel to the SAR flight pass (termed oriented buildings) and collapsed buildings share similar scattering mechanisms, both of which are dominated by volume scattering. This characteristic always leads to misjudgments between assessments of collapsed buildings and oriented buildings from PolSAR data. Because the collapsed buildings and the intact buildings (whether oriented or parallel buildings) have different textures, a novel building damage assessment method is proposed in this study to address this problem by introducing texture parameters of statistical models. First, the logarithms of the estimated texture parameters of different statistical models are taken as a new texture feature to describe the collapse of the buildings. Second, the collapsed buildings and intact buildings are distinguished using an appropriate threshold. Then, the building blocks are classified into three levels based on the building block collapse rate. Moreover, this paper also discusses the capability for performing damage assessment using texture parameters from different statistical models or using different estimators. The RADARSAT-2 and ALOS-1 PolSAR images are used to present and analyze the performance of the proposed method. The results show that using the texture parameters avoids the problem of confusing collapsed and oriented buildings and improves the assessment accuracy. The results assessed by using the K/G0 distribution texture parameters estimated based on the second moment obtain the highest extraction accuracies. For the RADARSAT-2 and ALOS-1 data, the overall accuracy (OA) for these three types of buildings is 73.39% and 68.45%, respectively.

Optimization of surface morphology and scattering properties of TCO/AIT textured glass front electrode for thin film solar cells

NASA Astrophysics Data System (ADS)

Addonizio, M. L.; Fusco, L.; Antonaia, A.; Cominale, F.; Usatii, I.

2015-12-01

Aluminium induced texture (AIT) method has been used for obtaining highly textured glass substrate suitable for silicon based thin film solar cell technology. Wet etch step parameters of AIT process have been varied and effect of different etchants and different etching times on morphological and optical properties has been analyzed. The resulting morphology features (shape, size distribution, inclination angle) have been optimized in order to obtain the best scattering properties. ZnO:Ga (GZO) films have been deposited by sputtering technique on AIT-processed glass. Two different ZnO surface morphologies have been obtained, strongly depending on the underlying glass substrate morphology induced by different etching times. Very rough and porous texture (σrms ∼ 150 nm) was obtained on glass etched 2 min showing cauliflower-like structure, whereas a softer texture (σrms ∼ 78 nm) was obtained on glass etched 7 min giving wider and smoother U-shaped craters. The effect of different glass textures on optical confinement has been tested in amorphous silicon based p-i-n devices. Devices fabricated on GZO/high textured glass showed a quantum efficiency enhancement due to both an effective light trapping phenomenon and an effective anti-reflective optical behaviour. Short etching time produce smaller cavities (<1 μm) with deep U-shape characterized by high roughness, high inclination angle and low autocorrelation length. This surface morphology promoted a large light scattering phenomenon, as evidenced by haze value and by angular resolved scattering (ARS) behaviour, into a large range of diffraction angles, giving high probability of effective light trapping inside a PV device.

A Clinical Decision Support System Using Ultrasound Textures and Radiologic Features to Distinguish Metastasis From Tumor-Free Cervical Lymph Nodes in Patients With Papillary Thyroid Carcinoma.

PubMed

Abbasian Ardakani, Ali; Reiazi, Reza; Mohammadi, Afshin

2018-03-30

This study investigated the potential of a clinical decision support approach for the classification of metastatic and tumor-free cervical lymph nodes (LNs) in papillary thyroid carcinoma on the basis of radiologic and textural analysis through ultrasound (US) imaging. In this research, 170 metastatic and 170 tumor-free LNs were examined by the proposed clinical decision support method. To discover the difference between the groups, US imaging was used for the extraction of radiologic and textural features. The radiologic features in the B-mode scans included the echogenicity, margin, shape, and presence of microcalcification. To extract the textural features, a wavelet transform was applied. A support vector machine classifier was used to classify the LNs. In the training set data, a combination of radiologic and textural features represented the best performance with sensitivity, specificity, accuracy, and area under the curve (AUC) values of 97.14%, 98.57%, 97.86%, and 0.994, respectively, whereas the classification based on radiologic and textural features alone yielded lower performance, with AUCs of 0.964 and 0.922. On testing the data set, the proposed model could classify the tumor-free and metastatic LNs with an AUC of 0.952, which corresponded to sensitivity, specificity, and accuracy of 93.33%, 96.66%, and 95.00%. The clinical decision support method based on textural and radiologic features has the potential to characterize LNs via 2-dimensional US. Therefore, it can be used as a supplementary technique in daily clinical practice to improve radiologists' understanding of conventional US imaging for characterizing LNs. © 2018 by the American Institute of Ultrasound in Medicine.

Virtual environments for scene of crime reconstruction and analysis

NASA Astrophysics Data System (ADS)

Howard, Toby L. J.; Murta, Alan D.; Gibson, Simon

2000-02-01

This paper describes research conducted in collaboration with Greater Manchester Police (UK), to evalute the utility of Virtual Environments for scene of crime analysis, forensic investigation, and law enforcement briefing and training. We present an illustrated case study of the construction of a high-fidelity virtual environment, intended to match a particular real-life crime scene as closely as possible. We describe and evaluate the combination of several approaches including: the use of the Manchester Scene Description Language for constructing complex geometrical models; the application of a radiosity rendering algorithm with several novel features based on human perceptual consideration; texture extraction from forensic photography; and experiments with interactive walkthroughs and large-screen stereoscopic display of the virtual environment implemented using the MAVERIK system. We also discuss the potential applications of Virtual Environment techniques in the Law Enforcement and Forensic communities.

Effect of electrical and mechanical poling history on domain orientation and piezoelectric properties of soft and hard PZT ceramics

NASA Astrophysics Data System (ADS)

Marsilius, Mie; Granzow, Torsten; Jones, Jacob L.

2011-02-01

The superior piezoelectric properties of all polycrystalline ferroelectrics are based on the extent of non-180° domain wall motion under electrical and mechanical poling loads. To distinguish between 180° and non-180° domain wall motion in a soft-doped and a hard-doped lead zirconate titanate (PZT) ceramic, domain texture measurements were performed using x-ray and neutron diffraction after different loading procedures. Comparing the results to measurements of the remanent strain and piezoelectric coefficient allowed the differentiation between different microstructural contributions to the macroscopic parameters. Both types of ceramic showed similar behavior under electric field, but the hard-doped material was more susceptible to mechanical load. A considerable fraction of the piezoelectric coefficient originated from poling by the preferred orientation of 180° domains.

Comparison of energy and protein intakes of older people consuming a texture modified diet with a normal hospital diet.

PubMed

Wright, L; Cotter, D; Hickson, M; Frost, G

2005-06-01

There are very few studies looking at the energy and protein requirements of patients requiring texture modified diets. Dysphagia is the main indication for people to be recommended texture-modified diets. Older people post-stroke are the key group in the hospital setting who consume this type of diet. The diets can be of several consistencies ranging from pureed to soft textures. To compare the 24-hour dietary intake of older people consuming a texture modified diet in a clinical setting to older people consuming a normal hospital diet. Weighed food intakes and food record charts were used to quantify the patients' intakes, which were compared to their individual requirements. The oral intake of 55 patients was measured. Twenty-five of the patients surveyed were eating a normal diet and acted as controls for 30 patients who were prescribed a texture-modified diet. The results showed that the texture-modified group had significantly lower intakes of energy (3877 versus 6115 kJ, P < 0.0001) and protein (40 versus 60 g, P < 0.003) compared to consumption of the normal diet. The energy and protein deficit from estimated requirements was significantly greater in the texture-modified group (2549 versus 357 kJ, P < 0.0001; 6 versus 22 g, P = 0.013; respectively). These statistically significant results indicate that older people on texture-modified diets have a lower intake of energy and protein than those consuming a normal hospital diet and it is likely that other nutrients will be inadequate. All patients on texture-modified diets should be assessed by the dietitian for nutritional support. Evidence based strategies for improving overall nutrient intake should be identified.

Retaining {1 0 0} texture from initial columnar grains in 6.5 wt% Si electrical steels

NASA Astrophysics Data System (ADS)

Liang, Ruiyang; Yang, Ping; Mao, Weimin

2017-11-01

6.5 wt% Si electrical steel is a superior soft magnetic material with excellent magnetic properties which highly depends on texture. In this study, based on the heredity of 〈0 0 1〉 orientation in columnar grains, columnar grains are used as the initial material to prepare non-oriented 6.5 wt% Si electrical steel with excellent magnetic properties. EBSD and XRD techniques are adopted to explore the structure and texture evolution during hot rolling, warm rolling, cold rolling and annealing. The results show that, due to the heredity of "structure and texture" from the initial strong {1 0 0} columnar grains, annealed sheet with {1 0 0}〈0 0 1〉 texture had better magnetic properties, which can be used as non-oriented high-silicon electrical steel. Both preferred cube grain nucleation in deformed {1 1 3}〈3 6 1〉 grains in subsurface and coarse {1 0 0}〈0 0 1〉 deformed grains in center layer show the effect of initial columnar grains with {1 0 0} texture.

Physicochemical and sensory properties of fresh potato-based pasta (gnocchi).

PubMed

Alessandrini, Laura; Balestra, Federica; Romani, Santina; Rocculi, Pietro; Rosa, Marco Dalla

2010-01-01

This study dealt with the characterization and quality assessment of 3 kinds of potato-based pasta (gnocchi) made with steam-cooked, potato puree (water added to potato flakes), and reconstituted potatoes as main ingredients. The aim of the research was to evaluate the quality of the products in terms of physicochemical, textural, and sensory characteristics. Water content, water activity, color (L* and h°), and texture (texture profile analysis [TPA] and shearing test) were evaluated on both raw and cooked samples. In addition, on the recovered cooking water the loss of solid substances was determined and on the cooked gnocchi a sensory assessment was performed. Eight sensory attributes (yellowness, hardness, gumminess, adhesiveness, potato taste, sweet taste, flour taste, and sapidity) were investigated. Statistically significant differences among products were obtained, especially concerning textural properties. In fact, sample made with reconstituted potatoes and emulsifiers resulted the hardest (8.53 ± 1.22 N), the gummiest (2.90 ± 0.05 N), and the "chewiest" (2.90 ± 0.58 N) after cooking. Gnocchi made with potato puree or reconstituted potatoes significantly differed from the one produced with steam-cooked potatoes in terms of sensory properties (yellowness, hardness, flour taste, and sapidity). Pearson's correlation analysis between some textural instrumental and sensory parameters showed significant correlation coefficients (0.532 < r < 0.810). Score plot of principal component analysis (PCA) confirmed obtained results from physicochemical and sensory analyses, in terms of high discriminant capacity of colorimetric and textural characteristics. © 2010 Institute of Food Technologists®

Novel Texture-based Visualization Methods for High-dimensional Multi-field Data Sets

DTIC Science & Technology

2013-07-06

project: In standard format showing authors, title, journal, issue, pages, and date, for each category list the following: b) papers published...visual- isation [18]. Novel image acquisition and simulation tech- niques have made is possible to record a large number of co-located data fields...function, structure, anatomical changes, metabolic activity, blood perfusion, and cellular re- modelling. In this paper we investigate texture-based

A fast three-dimensional gamma evaluation using a GPU utilizing texture memory for on-the-fly interpolations.

PubMed

Persoon, Lucas C G G; Podesta, Mark; van Elmpt, Wouter J C; Nijsten, Sebastiaan M J J G; Verhaegen, Frank

2011-07-01

A widely accepted method to quantify differences in dose distributions is the gamma (gamma) evaluation. Currently, almost all gamma implementations utilize the central processing unit (CPU). Recently, the graphics processing unit (GPU) has become a powerful platform for specific computing tasks. In this study, we describe the implementation of a 3D gamma evaluation using a GPU to improve calculation time. The gamma evaluation algorithm was implemented on an NVIDIA Tesla C2050 GPU using the compute unified device architecture (CUDA). First, several cubic virtual phantoms were simulated. These phantoms were tested with varying dose cube sizes and set-ups, introducing artificial dose differences. Second, to show applicability in clinical practice, five patient cases have been evaluated using the 3D dose distribution from a treatment planning system as the reference and the delivered dose determined during treatment as the comparison. A calculation time comparison between the CPU and GPU was made with varying thread-block sizes including the option of using texture or global memory. A GPU over CPU speed-up of 66 +/- 12 was achieved for the virtual phantoms. For the patient cases, a speed-up of 57 +/- 15 using the GPU was obtained. A thread-block size of 16 x 16 performed best in all cases. The use of texture memory improved the total calculation time, especially when interpolation was applied. Differences between the CPU and GPU gammas were negligible. The GPU and its features, such as texture memory, decreased the calculation time for gamma evaluations considerably without loss of accuracy.

High-speed sorting of grains by color and surface texture

USDA-ARS?s Scientific Manuscript database

A high-speed, low-cost, image-based sorting device was developed to detect and separate grains with different colors/textures. The device directly combines a complementary metal–oxide–semiconductor (CMOS) color image sensor with a field-programmable gate array (FPGA) that was programmed to execute ...

Prediction of canned black bean texture (Phaseolus vulgaris L.) from intact dry seeds using visible/near infrared spectroscopy and hyperspectral imaging data.

PubMed

Mendoza, Fernando A; Cichy, Karen A; Sprague, Christy; Goffnett, Amanda; Lu, Renfu; Kelly, James D

2018-01-01

Texture is a major quality parameter for the acceptability of canned whole beans. Prior knowledge of this quality trait before processing would be useful to guide variety development by bean breeders and optimize handling protocols by processors. The objective of this study was to evaluate and compare the predictive power of visible and near infrared reflectance spectroscopy (visible/NIRS, 400-2498 nm) and hyperspectral imaging (HYPERS, 400-1000 nm) techniques for predicting texture of canned black beans from intact dry seeds. Black beans were grown in Michigan (USA) over three field seasons. The samples exhibited phenotypic variability for canned bean texture due to genetic variability and processing practice. Spectral preprocessing methods (i.e. smoothing, first and second derivatives, continuous wavelet transform, and two-band ratios), coupled with a feature selection method, were tested for optimizing the prediction accuracy in both techniques based on partial least squares regression (PLSR) models. Visible/NIRS and HYPERS were effective in predicting texture of canned beans using intact dry seeds, as indicated by their correlation coefficients for prediction (R pred ) and standard errors of prediction (SEP). Visible/NIRS was superior (R pred = 0.546-0.923, SEP = 7.5-1.9 kg 100 g -1 ) to HYPERS (R pred = 0.401-0.883, SEP = 7.6-2.4 kg 100 g -1 ), which is likely due to the wider wavelength range collected in visible/NIRS. However, a significant improvement was reached in both techniques when the two-band ratios preprocessing method was applied to the data, reducing SEP by at least 10.4% and 16.2% for visible/NIRS and HYPERS, respectively. Moreover, results from using the combination of the three-season data sets based on the two-band ratios showed that visible/NIRS (R pred = 0.886, SEP = 4.0 kg 100 g -1 ) and HYPERS (R pred = 0.844, SEP = 4.6 kg 100 g -1 ) models were consistently successful in predicting texture over a wide range of measurements. Visible/NIRS and HYPERS have great potential for predicting the texture of canned beans; the robustness of the models is impacted by genotypic diversity, planting year and phenotypic variability for canned bean texture used for model building, and hence, robust models can be built based on data sets with high phenotypic diversity in textural properties, and periodically maintained and updated with new data. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Improved sample manipulation at the STRESS-SPEC neutron diffractometer using an industrial 6-axis robot for texture and strain analyses

NASA Astrophysics Data System (ADS)

Randau, C.; Brokmeier, H. G.; Gan, W. M.; Hofmann, M.; Voeller, M.; Tekouo, W.; Al-hamdany, N.; Seidl, G.; Schreyer, A.

2015-09-01

The materials science neutron diffractometer STRESS-SPEC located at FRM II is a dedicated instrument for strain and pole figure measurements. Both methods make complementary demands on sample handling. On one hand pole figure measurements need a high degree of freedom to orient small samples and on the other hand in strain investigations it is often necessary to handle large and heavy components. Therefore a robot based sample positioning system was developed, which has the capability to provide both possibilities. Based on this new robot system further developments like a full automated sample changer system for texture measurements were accomplished. Moreover this system opens the door for combined strain and texture analysis at STRESS-SPEC.

Texture metric that predicts target detection performance

NASA Astrophysics Data System (ADS)

Culpepper, Joanne B.

2015-12-01

Two texture metrics based on gray level co-occurrence error (GLCE) are used to predict probability of detection and mean search time. The two texture metrics are local clutter metrics and are based on the statistics of GLCE probability distributions. The degree of correlation between various clutter metrics and the target detection performance of the nine military vehicles in complex natural scenes found in the Search_2 dataset are presented. Comparison is also made between four other common clutter metrics found in the literature: root sum of squares, Doyle, statistical variance, and target structure similarity. The experimental results show that the GLCE energy metric is a better predictor of target detection performance when searching for targets in natural scenes than the other clutter metrics studied.

Shape based segmentation of MRIs of the bones in the knee using phase and intensity information

NASA Astrophysics Data System (ADS)

Fripp, Jurgen; Bourgeat, Pierrick; Crozier, Stuart; Ourselin, Sébastien

2007-03-01

The segmentation of the bones from MR images is useful for performing subsequent segmentation and quantitative measurements of cartilage tissue. In this paper, we present a shape based segmentation scheme for the bones that uses texture features derived from the phase and intensity information in the complex MR image. The phase can provide additional information about the tissue interfaces, but due to the phase unwrapping problem, this information is usually discarded. By using a Gabor filter bank on the complex MR image, texture features (including phase) can be extracted without requiring phase unwrapping. These texture features are then analyzed using a support vector machine classifier to obtain probability tissue matches. The segmentation of the bone is fully automatic and performed using a 3D active shape model based approach driven using gradient and texture information. The 3D active shape model is automatically initialized using a robust affine registration. The approach is validated using a database of 18 FLASH MR images that are manually segmented, with an average segmentation overlap (Dice similarity coefficient) of 0.92 compared to 0.9 obtained using the classifier only.

Texture analysis applied to second harmonic generation image data for ovarian cancer classification

NASA Astrophysics Data System (ADS)

Wen, Bruce L.; Brewer, Molly A.; Nadiarnykh, Oleg; Hocker, James; Singh, Vikas; Mackie, Thomas R.; Campagnola, Paul J.

2014-09-01

Remodeling of the extracellular matrix has been implicated in ovarian cancer. To quantitate the remodeling, we implement a form of texture analysis to delineate the collagen fibrillar morphology observed in second harmonic generation microscopy images of human normal and high grade malignant ovarian tissues. In the learning stage, a dictionary of "textons"-frequently occurring texture features that are identified by measuring the image response to a filter bank of various shapes, sizes, and orientations-is created. By calculating a representative model based on the texton distribution for each tissue type using a training set of respective second harmonic generation images, we then perform classification between images of normal and high grade malignant ovarian tissues. By optimizing the number of textons and nearest neighbors, we achieved classification accuracy up to 97% based on the area under receiver operating characteristic curves (true positives versus false positives). The local analysis algorithm is a more general method to probe rapidly changing fibrillar morphologies than global analyses such as FFT. It is also more versatile than other texture approaches as the filter bank can be highly tailored to specific applications (e.g., different disease states) by creating customized libraries based on common image features.

Multi-Sectional Views Textural Based SVM for MS Lesion Segmentation in Multi-Channels MRIs

PubMed Central

Abdullah, Bassem A; Younis, Akmal A; John, Nigel M

2012-01-01

In this paper, a new technique is proposed for automatic segmentation of multiple sclerosis (MS) lesions from brain magnetic resonance imaging (MRI) data. The technique uses a trained support vector machine (SVM) to discriminate between the blocks in regions of MS lesions and the blocks in non-MS lesion regions mainly based on the textural features with aid of the other features. The classification is done on each of the axial, sagittal and coronal sectional brain view independently and the resultant segmentations are aggregated to provide more accurate output segmentation. The main contribution of the proposed technique described in this paper is the use of textural features to detect MS lesions in a fully automated approach that does not rely on manually delineating the MS lesions. In addition, the technique introduces the concept of the multi-sectional view segmentation to produce verified segmentation. The proposed textural-based SVM technique was evaluated using three simulated datasets and more than fifty real MRI datasets. The results were compared with state of the art methods. The obtained results indicate that the proposed method would be viable for use in clinical practice for the detection of MS lesions in MRI. PMID:22741026

PCTO-SIM: Multiple-point geostatistical modeling using parallel conditional texture optimization

NASA Astrophysics Data System (ADS)

Pourfard, Mohammadreza; Abdollahifard, Mohammad J.; Faez, Karim; Motamedi, Sayed Ahmad; Hosseinian, Tahmineh

2017-05-01

Multiple-point Geostatistics is a well-known general statistical framework by which complex geological phenomena have been modeled efficiently. Pixel-based and patch-based are two major categories of these methods. In this paper, the optimization-based category is used which has a dual concept in texture synthesis as texture optimization. Our extended version of texture optimization uses the energy concept to model geological phenomena. While honoring the hard point, the minimization of our proposed cost function forces simulation grid pixels to be as similar as possible to training images. Our algorithm has a self-enrichment capability and creates a richer training database from a sparser one through mixing the information of all surrounding patches of the simulation nodes. Therefore, it preserves pattern continuity in both continuous and categorical variables very well. It also shows a fuzzy result in its every realization similar to the expected result of multi realizations of other statistical models. While the main core of most previous Multiple-point Geostatistics methods is sequential, the parallel main core of our algorithm enabled it to use GPU efficiently to reduce the CPU time. One new validation method for MPS has also been proposed in this paper.

Single-Image Super-Resolution Based on Rational Fractal Interpolation.

PubMed

Zhang, Yunfeng; Fan, Qinglan; Bao, Fangxun; Liu, Yifang; Zhang, Caiming

2018-08-01

This paper presents a novel single-image super-resolution (SR) procedure, which upscales a given low-resolution (LR) input image to a high-resolution image while preserving the textural and structural information. First, we construct a new type of bivariate rational fractal interpolation model and investigate its analytical properties. This model has different forms of expression with various values of the scaling factors and shape parameters; thus, it can be employed to better describe image features than current interpolation schemes. Furthermore, this model combines the advantages of rational interpolation and fractal interpolation, and its effectiveness is validated through theoretical analysis. Second, we develop a single-image SR algorithm based on the proposed model. The LR input image is divided into texture and non-texture regions, and then, the image is interpolated according to the characteristics of the local structure. Specifically, in the texture region, the scaling factor calculation is the critical step. We present a method to accurately calculate scaling factors based on local fractal analysis. Extensive experiments and comparisons with the other state-of-the-art methods show that our algorithm achieves competitive performance, with finer details and sharper edges.

An intelligent framework for medical image retrieval using MDCT and multi SVM.

PubMed

Balan, J A Alex Rajju; Rajan, S Edward

2014-01-01

Volumes of medical images are rapidly generated in medical field and to manage them effectively has become a great challenge. This paper studies the development of innovative medical image retrieval based on texture features and accuracy. The objective of the paper is to analyze the image retrieval based on diagnosis of healthcare management systems. This paper traces the development of innovative medical image retrieval to estimate both the image texture features and accuracy. The texture features of medical images are extracted using MDCT and multi SVM. Both the theoretical approach and the simulation results revealed interesting observations and they were corroborated using MDCT coefficients and SVM methodology. All attempts to extract the data about the image in response to the query has been computed successfully and perfect image retrieval performance has been obtained. Experimental results on a database of 100 trademark medical images show that an integrated texture feature representation results in 98% of the images being retrieved using MDCT and multi SVM. Thus we have studied a multiclassification technique based on SVM which is prior suitable for medical images. The results show the retrieval accuracy of 98%, 99% for different sets of medical images with respect to the class of image.

Hyperspectral remote sensing image retrieval system using spectral and texture features.

PubMed

Zhang, Jing; Geng, Wenhao; Liang, Xi; Li, Jiafeng; Zhuo, Li; Zhou, Qianlan

2017-06-01

Although many content-based image retrieval systems have been developed, few studies have focused on hyperspectral remote sensing images. In this paper, a hyperspectral remote sensing image retrieval system based on spectral and texture features is proposed. The main contributions are fourfold: (1) considering the "mixed pixel" in the hyperspectral image, endmembers as spectral features are extracted by an improved automatic pixel purity index algorithm, then the texture features are extracted with the gray level co-occurrence matrix; (2) similarity measurement is designed for the hyperspectral remote sensing image retrieval system, in which the similarity of spectral features is measured with the spectral information divergence and spectral angle match mixed measurement and in which the similarity of textural features is measured with Euclidean distance; (3) considering the limited ability of the human visual system, the retrieval results are returned after synthesizing true color images based on the hyperspectral image characteristics; (4) the retrieval results are optimized by adjusting the feature weights of similarity measurements according to the user's relevance feedback. The experimental results on NASA data sets can show that our system can achieve comparable superior retrieval performance to existing hyperspectral analysis schemes.

Texture for script identification.

PubMed

Busch, Andrew; Boles, Wageeh W; Sridharan, Sridha

2005-11-01

The problem of determining the script and language of a document image has a number of important applications in the field of document analysis, such as indexing and sorting of large collections of such images, or as a precursor to optical character recognition (OCR). In this paper, we investigate the use of texture as a tool for determining the script of a document image, based on the observation that text has a distinct visual texture. An experimental evaluation of a number of commonly used texture features is conducted on a newly created script database, providing a qualitative measure of which features are most appropriate for this task. Strategies for improving classification results in situations with limited training data and multiple font types are also proposed.

Multifractal modeling, segmentation, prediction, and statistical validation of posterior fossa tumors

NASA Astrophysics Data System (ADS)

Islam, Atiq; Iftekharuddin, Khan M.; Ogg, Robert J.; Laningham, Fred H.; Sivakumar, Bhuvaneswari

2008-03-01

In this paper, we characterize the tumor texture in pediatric brain magnetic resonance images (MRIs) and exploit these features for automatic segmentation of posterior fossa (PF) tumors. We focus on PF tumor because of the prevalence of such tumor in pediatric patients. Due to varying appearance in MRI, we propose to model the tumor texture with a multi-fractal process, such as a multi-fractional Brownian motion (mBm). In mBm, the time-varying Holder exponent provides flexibility in modeling irregular tumor texture. We develop a detailed mathematical framework for mBm in two-dimension and propose a novel algorithm to estimate the multi-fractal structure of tissue texture in brain MRI based on wavelet coefficients. This wavelet based multi-fractal feature along with MR image intensity and a regular fractal feature obtained using our existing piecewise-triangular-prism-surface-area (PTPSA) method, are fused in segmenting PF tumor and non-tumor regions in brain T1, T2, and FLAIR MR images respectively. We also demonstrate a non-patient-specific automated tumor prediction scheme based on these image features. We experimentally show the tumor discriminating power of our novel multi-fractal texture along with intensity and fractal features in automated tumor segmentation and statistical prediction. To evaluate the performance of our tumor prediction scheme, we obtain ROCs and demonstrate how sharply the curves reach the specificity of 1.0 sacrificing minimal sensitivity. Experimental results show the effectiveness of our proposed techniques in automatic detection of PF tumors in pediatric MRIs.

Computer Graphics Meets Image Fusion: the Power of Texture Baking to Simultaneously Visualise 3d Surface Features and Colour

NASA Astrophysics Data System (ADS)

Verhoeven, G. J.

2017-08-01

Since a few years, structure-from-motion and multi-view stereo pipelines have become omnipresent in the cultural heritage domain. The fact that such Image-Based Modelling (IBM) approaches are capable of providing a photo-realistic texture along the threedimensional (3D) digital surface geometry is often considered a unique selling point, certainly for those cases that aim for a visually pleasing result. However, this texture can very often also obscure the underlying geometrical details of the surface, making it very hard to assess the morphological features of the digitised artefact or scene. Instead of constantly switching between the textured and untextured version of the 3D surface model, this paper presents a new method to generate a morphology-enhanced colour texture for the 3D polymesh. The presented approach tries to overcome this switching between objects visualisations by fusing the original colour texture data with a specific depiction of the surface normals. Whether applied to the original 3D surface model or a lowresolution derivative, this newly generated texture does not solely convey the colours in a proper way but also enhances the smalland large-scale spatial and morphological features that are hard or impossible to perceive in the original textured model. In addition, the technique is very useful for low-end 3D viewers, since no additional memory and computing capacity are needed to convey relief details properly. Apart from simple visualisation purposes, the textured 3D models are now also better suited for on-surface interpretative mapping and the generation of line drawings.

Spoilage of sous vide cooked salmon (Salmo salar) stored under refrigeration.

PubMed

Díaz, P; Garrido, M D; Bañón, S

2011-02-01

The spoilage of Sous Vide 'SV' cooked salmon stored under refrigeration was studied. Samples were packaged under vacuum in polyamide-polypropylene pouches, cooked at an oven temperature/time of 80 (°)C/45 min, quickly chilled at 3 (°)C and stored at 2 (°)C for 0, 5 or 10 weeks for catering use. Microbial (aerobic and anaerobic psychrotrophs, lactic acid bacteria, molds and yeasts and Enterobacteriaceae), physical-chemical (pH, water activity, TBARS, acidity, L*a*b* color, texture profile analysis and shear force) and sensory (appearance, odor, flavor, texture and overall quality) parameters were determined. SV processing prevented the growth of aerobic and anaerobic psychrotrophs, lactic acid bacteria, molds and yeasts and Enterobacteriaceae. There were no relevant changes in pH, water activity, TBARS, CIELab color associated with cooked salmon spoilage. Instrumental texture data were contradictory. Slight decrease in lactic acid levels was found. In contrast, the SV cooked salmon suffered considerable sensory deterioration during its refrigerated storage, consisting of severe losses of cooked salmon odor and flavor, slight rancidity, discoloration associated with white precipitation, and moderates softness, and loss of chewiness and juiciness. No acidification, putrefaction or relevant rancidity was detected. The sensory spoilage preceded microbiological and physical-chemical spoilage, suggesting that microbiological quality alone may overestimate the shelf life of SV cooked salmon.

Application of Isfarzeh seed (Plantago ovate L.) mucilage as a fat mimetic in mayonnaise.

PubMed

Amiri Aghdaei, S S; Aalami, M; Babaei Geefan, Saeed; Ranjbar, A

2014-10-01

In present study, application of Isfarzeh seed (Plantago ovate L.) mucilage as fat replacer was studied in mayonnaise formulation. Fat was partially substituted by mucilage gels (2 and 3 % suspensions) at levels of 30, 40 and 50 % which were referred to as FM2-30 % (2 % gel and 30 % substitution level), FM2-40 %, FM2-50 %, FM3-30 %, FM3-40 %, and FM3-50 % formulations, respectively and the full fat (Ff) mayonnaise with 78 % oil was used as control. Physicochemical, texture and sensory analysis of Ff and Low fat (Lf) treatments were evaluated. Results indicated that Lf samples had considerably lower energy content compared with control, but higher water content than their Ff counterpart. In view of texture, FM3-30 % showed similar textural characteristics as those of control. Both Ff and Lf samples exhibited thixotropic and shear thinning behavior through rheological studies and all samples followed the power law model except FM3-40 % and FM3-50 %. Sensory evaluation demonstrated that all of mayonnaise samples, containing 3 % mucilage, were more acceptable. It was concluded that Isfarzeh seed mucilage can be used as a suitable fat replacer in mayonnaise formulation.

Direct Volume Rendering with Shading via Three-Dimensional Textures

NASA Technical Reports Server (NTRS)

VanGelder, Allen; Kim, Kwansik

1996-01-01

A new and easy-to-implement method for direct volume rendering that uses 3D texture maps for acceleration, and incorporates directional lighting, is described. The implementation, called Voltx, produces high-quality images at nearly interactive speeds on workstations with hardware support for three-dimensional texture maps. Previously reported methods did not incorporate a light model, and did not address issues of multiple texture maps for large volumes. Our research shows that these extensions impact performance by about a factor of ten. Voltx supports orthographic, perspective, and stereo views. This paper describes the theory and implementation of this technique, and compares it to the shear-warp factorization approach. A rectilinear data set is converted into a three-dimensional texture map containing color and opacity information. Quantized normal vectors and a lookup table provide efficiency. A new tesselation of the sphere is described, which serves as the basis for normal-vector quantization. A new gradient-based shading criterion is described, in which the gradient magnitude is interpreted in the context of the field-data value and the material classification parameters, and not in isolation. In the rendering phase, the texture map is applied to a stack of parallel planes, which effectively cut the texture into many slabs. The slabs are composited to form an image.

Synthesized interstitial lung texture for use in anthropomorphic computational phantoms

NASA Astrophysics Data System (ADS)

Becchetti, Marc F.; Solomon, Justin B.; Segars, W. Paul; Samei, Ehsan

2016-04-01

A realistic model of the anatomical texture from the pulmonary interstitium was developed with the goal of extending the capability of anthropomorphic computational phantoms (e.g., XCAT, Duke University), allowing for more accurate image quality assessment. Contrast-enhanced, high dose, thorax images for a healthy patient from a clinical CT system (Discovery CT750HD, GE healthcare) with thin (0.625 mm) slices and filtered back- projection (FBP) were used to inform the model. The interstitium which gives rise to the texture was defined using 24 volumes of interest (VOIs). These VOIs were selected manually to avoid vasculature, bronchi, and bronchioles. A small scale Hessian-based line filter was applied to minimize the amount of partial-volumed supernumerary vessels and bronchioles within the VOIs. The texture in the VOIs was characterized using 8 Haralick and 13 gray-level run length features. A clustered lumpy background (CLB) model with added noise and blurring to match CT system was optimized to resemble the texture in the VOIs using a genetic algorithm with the Mahalanobis distance as a similarity metric between the texture features. The most similar CLB model was then used to generate the interstitial texture to fill the lung. The optimization improved the similarity by 45%. This will substantially enhance the capabilities of anthropomorphic computational phantoms, allowing for more realistic CT simulations.

Haralick texture features from apparent diffusion coefficient (ADC) MRI images depend on imaging and pre-processing parameters.

PubMed

Brynolfsson, Patrik; Nilsson, David; Torheim, Turid; Asklund, Thomas; Karlsson, Camilla Thellenberg; Trygg, Johan; Nyholm, Tufve; Garpebring, Anders

2017-06-22

In recent years, texture analysis of medical images has become increasingly popular in studies investigating diagnosis, classification and treatment response assessment of cancerous disease. Despite numerous applications in oncology and medical imaging in general, there is no consensus regarding texture analysis workflow, or reporting of parameter settings crucial for replication of results. The aim of this study was to assess how sensitive Haralick texture features of apparent diffusion coefficient (ADC) MR images are to changes in five parameters related to image acquisition and pre-processing: noise, resolution, how the ADC map is constructed, the choice of quantization method, and the number of gray levels in the quantized image. We found that noise, resolution, choice of quantization method and the number of gray levels in the quantized images had a significant influence on most texture features, and that the effect size varied between different features. Different methods for constructing the ADC maps did not have an impact on any texture feature. Based on our results, we recommend using images with similar resolutions and noise levels, using one quantization method, and the same number of gray levels in all quantized images, to make meaningful comparisons of texture feature results between different subjects.

Effects of Texture and Grain Size on the Yield Strength of ZK61 Alloy Rods Processed by Cyclic Extrusion and Compression

PubMed Central

Zhang, Lixin; Zhang, Wencong; Cao, Biao; Chen, Wenzhen; Duan, Junpeng; Cui, Guorong

2017-01-01

The ZK61 alloy rods with different grain sizes and crystallographic texture were successfully fabricated by cyclic extrusion and compression (CEC). Their room-temperature tension & compression yield strength displayed a significant dependence on grain size and texture, essentially attributed to {10-12} twinning. The texture variations were characterized by the angle θ between the c-axis of the grain and the extrusion direction (ED) during the process. The contour map of room-temperature yield strength as a function of grain size and the angle θ was obtained. It showed that both the tension yield strength and the compression yield strength of ZK61 alloy were fully consistent with the Hall-Patch relationship at a certain texture, but the change trends of the tension yield strength and the compression yield strength were completely opposite at the same grain size while texture altered. The friction stresses of different deformation modes calculated based on the texture confirmed the tension yield strength of the CECed ZK61 alloy rods, which was determined by both the basal slip and the tension twinning slip during the tension deformation at room temperature, while the compression yield strength was mainly determined by the basal slip during the compression deformation. PMID:29072616

Calcium and zirconium as texture modifiers during rolling and annealing of magnesium–zinc alloys

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bohlen, Jan, E-mail: jan.bohlen@hzg.de; Wendt, Joachim; Nienaber, Maria

2015-03-15

Rolling experiments were carried out on a ternary Mg–Zn–Ca alloy and its modification with zirconium. Short time annealing of as-rolled sheets is used to reveal the microstructure and texture development. The texture of the as-rolled sheets can be characterised by basal pole figures with split peak towards the rolling direction (RD) and a broad transverse angular spread of basal planes towards the transverse direction (TD). During annealing the RD split peaks as well as orientations in the sheet plane vanish whereas the distribution of orientations tilted towards the TD remains. It is shown in EBSD measurements that during rolling bandsmore » of twin containing structures form. During subsequent annealing basal orientations close to the sheet plane vanish based on a grain nucleation and growth mechanism of recrystallisation. Orientations with tilt towards the TD remain in grains that do not undergo such a mechanism. The addition of Zr delays texture weakening. - Highlights: • Ca in Mg–Zn-alloys contributes to a significant texture weakening during rolling and annealing. • Grain nucleation and growth in structures consisting of twins explain a texture randomisation during annealing. • Grains with transverse tilt of basal planes preferentially do not undergo a grain nucleation and growth mechanism. • Zr delays the microstructure and texture development.« less

Cross-Modal Associations between Sounds and Drink Tastes/Textures: A Study with Spontaneous Production of Sound-Symbolic Words.

PubMed

Sakamoto, Maki; Watanabe, Junji

2016-03-01

Many languages have a word class whose speech sounds are linked to sensory experiences. Several recent studies have demonstrated cross-modal associations (or correspondences) between sounds and gustatory sensations by asking participants to match predefined sound-symbolic words (e.g., "maluma/takete") with the taste/texture of foods. Here, we further explore cross-modal associations using the spontaneous production of words and semantic ratings of sensations. In the experiment, after drinking liquids, participants were asked to express their taste/texture using Japanese sound-symbolic words, and at the same time, to evaluate it in terms of criteria expressed by adjectives. Because the Japanese language has a large vocabulary of sound-symbolic words, and Japanese people frequently use them to describe taste/texture, analyzing a variety of Japanese sound-symbolic words spontaneously produced to express taste/textures might enable us to explore the mechanism of taste/texture categorization. A hierarchical cluster analysis based on the relationship between linguistic sounds and taste/texture evaluations revealed the structure of sensation categories. The results indicate that an emotional evaluation like pleasant/unpleasant is the primary cluster in gustation. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Correlation between sensory and instrumental measurements of standard and crisp-texture southern highbush blueberries (Vaccinium corymbosum L. interspecific hybrids)

PubMed Central

Blaker, Kendra M; Plotto, Anne; Baldwin, Elizabeth A; Olmstead, James W

2014-01-01

BACKGROUND Fruit texture is a primary selection trait in southern highbush blueberry (SHB) breeding to increase fresh fruit postharvest quality and consumer acceptance. A novel crisp fruit texture has recently been identified among SHB germplasm. In this study, we developed a common set of descriptors that align sensory evaluation of blueberry fruit texture with instrumental measures that could be used for quantitative measurements during pre- and postharvest evaluation. RESULTS Sensory and instrumental characteristics were measured in 36 and 49 genotypes in 2010 and 2011, respectively. A trained sensory panel evaluated fresh fruit based on five common textural attributes in 2010 and 2011: bursting energy, flesh firmness, skin toughness, juiciness and mealiness. Instrumental measures of compression and bioyield forces were significantly different among cultivars and correlated with sensory scores for bursting energy, flesh firmness and skin toughness (R > 0.7, except skin toughness in 2011), but correlations with sensory scores for juiciness and mealiness were low (R < 0.4). CONCLUSION The results of sensory and instrumental measures supported the use of both compression and bioyield force measures in distinguishing crisp from standard-texture genotypes, and suggest that crisp texture in SHB is related to the sensory perception of bursting energy, flesh firmness and skin toughness. PMID:24619938

Inferring pterosaur diets through quantitative 3D textural analysis of tooth microwear in extant analogues

NASA Astrophysics Data System (ADS)

Bestwick, Jordan; Unwin, David; Butler, Richard; Henderson, Don; Purnell, Mark

2017-04-01

Pterosaurs (Pterosauria) were a successful group of Mesozoic flying reptiles. For 150 million years they were integral components of terrestrial and coastal ecosystems, yet their feeding ecology remains poorly constrained. Postulated pterosaur diets include insectivory, piscivory and/or carnivory, but many dietary hypotheses are speculative and/or based on little evidence, highlighting the need for alternative approaches to provide robust data. One method involves quantitative analysis of the micron-scale 3D textures of worn pterosaur tooth surfaces - dental microwear texture analysis. Microwear is produced as scratches and chips generated by food items create characteristic tooth surface textures. Microwear analysis has never been applied to pterosaurs, but we might expect microwear textures to differ between pterosaurs with different diets. An important step in investigating pterosaur microwear is to examine microwear from extant organisms with known diets to provide a comparative data set. This has been achieved through analysis of non-occlusal microwear textures in extant bats, crocodilians and monitor lizards, clades within which species exhibit insectivorous, piscivorous and carnivorous diets. The results - the first test of the hypothesis that non-occlusal microwear textures in these extant clades vary with diet - provide the context for the first robust quantitative tests of pterosaur diets.

Structure-Property Correlations in Al-Li Alloy Integrally Stiffened Extrusions

NASA Technical Reports Server (NTRS)

Hales, Stephen J.; Hafley, Robert A.

2001-01-01

The objective of this investigation was to establish the relationship between mechanical property anisotropy, microstructure and crystallographic texture in integrally 'T'-stiffened extruded panels fabricated from the Al-Li alloys 2195, 2098 and 2096. In-plane properties were measured as a function of orientation at two locations in the panels, namely mid-way between (Skin), and directly beneath (Base), the integral 'T' stiffeners. The 2195 extrusion exhibited the best combination of strength and toughness, but was the most anisotropic. The 2098 extrusion exhibited lower strength and comparable toughness, but was more isotropic than 2195. The 2096 extrusion exhibited the lowest strength and poor toughness, but was the most isotropic. All three alloys exhibited highly elongated grain structures and similar location-dependent variations in grain morphology. The textural characteristics comprised a beta + <100> fiber texture, similar to rolled product, in the Skin regions and alpha <111> + <100> fiber texture, comparable to axisymmetric extruded product, in the Base regions. In an attempt to quantitatively correlate texture with yield strength anisotropy, the original 'full constraint' Taylor model and a variant of the 'relaxed constraint' model, explored by Wert et al., were applied to the data. A comparison of the results revealed that the Wert model was consistently more accurate than the Taylor model.

SU-F-R-18: Updates to the Computational Environment for Radiological Research for Image Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Apte, Aditya P.; Deasy, Joseph O.

2016-06-15

Purpose: To present new tools in CERR for Texture Analysis and Visualization. Method: (1) Quantitative Image Analysis: We added the ability to compute Haralick texture features based on local neighbourhood. The Texture features depend on many parameters used in their derivation. For example: (a) directionality, (b) quantization of image, (c) patch-size for the neighborhood, (d) handling of the edge voxels within the region of interest, (e) Averaging co-occurance matrix vs texture features for different directions etc. A graphical user interface was built to set these parameters and then visualize their impact on the resulting texture maps. The entire functionality wasmore » written in Matlab. Array indexing was used to speed up the texture calculation. The computation speed is very competitive with the ITK library. Moreover, our implementation works with multiple CPUs and the computation time can be further reduced by using multiple processor threads. In order to reduce the Haralick texture maps into scalar features, we propose the use of Texture Volume Histograms. This lets users make use of the entire distribution of texture values within the region of interest rather than using just the mean and the standard deviations. (2) Qualitative/Visualization tools: The derived texture maps are stored as a new scan (derived) within CERR’s planC data structure. A display that compares various scans was built to show the raw image and the derived texture maps side-by-side. These images are positionally linked and can be navigated together. CERR’s graphics handling was updated and sped-up to be compatible with the newer Matlab versions. As a result, the users can use (a) different window levels and colormaps for different viewports, (b) click-and-drag or use mouse scroll-wheel to navigate slices. Results: The new features and updates are available via https://www.github.com/adityaapte/cerr . Conclusion: Features added to CERR increase its utility in Radiomics and Outcomes modeling.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, B; Yu, H; Jara, H

Purpose: To compare enhanced Laws texture derived from parametric proton density (PD) maps to other MRI-based surrogate markers (T2, PD, ADC) in assessing degrees of liver fibrosis in a murine model of hepatic fibrosis using 11.7T scanner. Methods: This animal study was IACUC approved. Fourteen mice were divided into control (n=1) and experimental (n=13). The latter were fed a DDC-supplemented diet to induce hepatic fibrosis. Liver specimens were imaged using an 11.7T scanner; the parametric PD, T2, and ADC maps were generated from spin-echo pulsed field gradient and multi-echo spin-echo acquisitions. Enhanced Laws texture analysis was applied to the PDmore » maps: first, hepatic blood vessels and liver margins were segmented/removed using an automated dual-clustering algorithm; secondly, an optimal thresholding algorithm was applied to reduce the partial volume artifact; next, mean and stdev were corrected to minimize grayscale variation across images; finally, Laws texture was extracted. Degrees of fibrosis was assessed by an experienced pathologist and digital image analysis (%Area Fibrosis). Scatterplots comparing enhanced Laws texture, T2, PD, and ADC values to degrees of fibrosis were generated and correlation coefficients were calculated. Unenhanced Laws texture was also compared to assess the effectiveness of the proposed enhancements. Results: Hepatic fibrosis and the enhanced Laws texture were strongly correlated with higher %Area Fibrosis associated with higher Laws texture (r=0.89). Only a moderate correlation was detected between %Area Fibrosis and unenhanced Laws texture (r=0.70). Strong correlation also existed between ADC and %Area Fibrosis (r=0.86). Moderate correlations were seen between %Area Fibrosis and PD (r=0.65) and T2 (r=0.66). Conclusions: Higher degrees of hepatic fibrosis are associated with increased Laws texture. The proposed enhancements improve the accuracy of Laws texture. Enhanced Laws texture features are more accurate than PD and T2 in assessing fibrosis, and can potentially serve as an accurate surrogate marker for hepatic fibrosis.« less

Negotiation Based Deconfliction in Air-traffic Control

DTIC Science & Technology

2008-01-15

specifying the object models and their location in the world. Skybox Layer is able to show any background textures behind the defined world in the...visual- ization. The skybox is constructed as a standard large cube, thus six textures are mapped to each of its side. No-flight Zones Layer gives

Develop draft chip seal cover aggregate specification based on aggregate imaging system (AIMS) angularity, shape, and texture test results : final report.

DOT National Transportation Integrated Search

2014-01-01

The objective of the study is to improve Oklahoma Department of Transportation (ODOT) chip seal design and performance through introducing new criteria for the selection of cover aggregate and binder. The study evaluates the shape and texture-related...

Generation of synthetic image sequences for the verification of matching and tracking algorithms for deformation analysis

NASA Astrophysics Data System (ADS)

Bethmann, F.; Jepping, C.; Luhmann, T.

2013-04-01

This paper reports on a method for the generation of synthetic image data for almost arbitrary static or dynamic 3D scenarios. Image data generation is based on pre-defined 3D objects, object textures, camera orientation data and their imaging properties. The procedure does not focus on the creation of photo-realistic images under consideration of complex imaging and reflection models as they are used by common computer graphics programs. In contrast, the method is designed with main emphasis on geometrically correct synthetic images without radiometric impact. The calculation process includes photogrammetric distortion models, hence cameras with arbitrary geometric imaging characteristics can be applied. Consequently, image sets can be created that are consistent to mathematical photogrammetric models to be used as sup-pixel accurate data for the assessment of high-precision photogrammetric processing methods. In the first instance the paper describes the process of image simulation under consideration of colour value interpolation, MTF/PSF and so on. Subsequently the geometric quality of the synthetic images is evaluated with ellipse operators. Finally, simulated image sets are used to investigate matching and tracking algorithms as they have been developed at IAPG for deformation measurement in car safety testing.

Detection of Focal Cortical Dysplasia Lesions in MRI Using Textural Features

NASA Astrophysics Data System (ADS)

Loyek, Christian; Woermann, Friedrich G.; Nattkemper, Tim W.

Focal cortical dysplasia (FCD) is a frequent cause of medically refractory partial epilepsy. The visual identification of FCD lesions on magnetic resonance images (MRI) is a challenging task in standard radiological analysis. Quantitative image analysis which tries to assist in the diagnosis of FCD lesions is an active field of research. In this work we investigate the potential of different texture features, in order to explore to what extent they are suitable for detecting lesional tissue. As a result we can show first promising results based on segmentation and texture classification.

Real-time visual tracking of less textured three-dimensional objects on mobile platforms

NASA Astrophysics Data System (ADS)

Seo, Byung-Kuk; Park, Jungsik; Park, Hanhoon; Park, Jong-Il

2012-12-01

Natural feature-based approaches are still challenging for mobile applications (e.g., mobile augmented reality), because they are feasible only in limited environments such as highly textured and planar scenes/objects, and they need powerful mobile hardware for fast and reliable tracking. In many cases where conventional approaches are not effective, three-dimensional (3-D) knowledge of target scenes would be beneficial. We present a well-established framework for real-time visual tracking of less textured 3-D objects on mobile platforms. Our framework is based on model-based tracking that efficiently exploits partially known 3-D scene knowledge such as object models and a background's distinctive geometric or photometric knowledge. Moreover, we elaborate on implementation in order to make it suitable for real-time vision processing on mobile hardware. The performance of the framework is tested and evaluated on recent commercially available smartphones, and its feasibility is shown by real-time demonstrations.

Texture and haptic cues in slant discrimination: reliability-based cue weighting without statistically optimal cue combination

NASA Astrophysics Data System (ADS)

Rosas, Pedro; Wagemans, Johan; Ernst, Marc O.; Wichmann, Felix A.

2005-05-01

A number of models of depth-cue combination suggest that the final depth percept results from a weighted average of independent depth estimates based on the different cues available. The weight of each cue in such an average is thought to depend on the reliability of each cue. In principle, such a depth estimation could be statistically optimal in the sense of producing the minimum-variance unbiased estimator that can be constructed from the available information. Here we test such models by using visual and haptic depth information. Different texture types produce differences in slant-discrimination performance, thus providing a means for testing a reliability-sensitive cue-combination model with texture as one of the cues to slant. Our results show that the weights for the cues were generally sensitive to their reliability but fell short of statistically optimal combination - we find reliability-based reweighting but not statistically optimal cue combination.

Reconstructing White Walls: Multi-View Multi-Shot 3d Reconstruction of Textureless Surfaces

NASA Astrophysics Data System (ADS)

Ley, Andreas; Hänsch, Ronny; Hellwich, Olaf

2016-06-01

The reconstruction of the 3D geometry of a scene based on image sequences has been a very active field of research for decades. Nevertheless, there are still existing challenges in particular for homogeneous parts of objects. This paper proposes a solution to enhance the 3D reconstruction of weakly-textured surfaces by using standard cameras as well as a standard multi-view stereo pipeline. The underlying idea of the proposed method is based on improving the signal-to-noise ratio in weakly-textured regions while adaptively amplifying the local contrast to make better use of the limited numerical range in 8-bit images. Based on this premise, multiple shots per viewpoint are used to suppress statistically uncorrelated noise and enhance low-contrast texture. By only changing the image acquisition and adding a preprocessing step, a tremendous increase of up to 300% in completeness of the 3D reconstruction is achieved.

Identification of natural images and computer-generated graphics based on statistical and textural features.

PubMed

Peng, Fei; Li, Jiao-ting; Long, Min

2015-03-01

To discriminate the acquisition pipelines of digital images, a novel scheme for the identification of natural images and computer-generated graphics is proposed based on statistical and textural features. First, the differences between them are investigated from the view of statistics and texture, and 31 dimensions of feature are acquired for identification. Then, LIBSVM is used for the classification. Finally, the experimental results are presented. The results show that it can achieve an identification accuracy of 97.89% for computer-generated graphics, and an identification accuracy of 97.75% for natural images. The analyses also demonstrate the proposed method has excellent performance, compared with some existing methods based only on statistical features or other features. The method has a great potential to be implemented for the identification of natural images and computer-generated graphics. © 2014 American Academy of Forensic Sciences.

Runoff initiation from falling raindrops - comparison of smooth impervious surface and asphalt pavements. Effects of surface inclination and texture.

NASA Astrophysics Data System (ADS)

Nezlobin, David; Pariente, Sarah; Lavee, Hanoch; Sachs, Eyal; Levenberg, Eyal

2017-04-01

The processes of runoff initiation on smooth impervious surfaces and various asphalt pavements are investigated in laboratory rain simulator experiments and outdoor sprinkling tests. Visual and FLIR observations indicate that runoff initiation is associated with coalescence of drop clusters on the surface and complex changes in micro-connectivity. Depending on surface inclination, several morphological regimes of flow initiation have been observed. In the case of very small inclination the runoff initiation is governed by critical merging of drop clusters on the surface and develops in broad flows (very abrupt, but delayed). For larger inclinations, the runoff occurs in rivulets or strongly directed flow threads. On asphalt pavements the runoff initiation is also strongly affected by pavement SVF (Surface Void Fraction), texture and even by the asphalt hydrophobicity. A simplified bi-level model of the pavement surface may explain principal differences in the runoff initiation on asphalts with small, intermediate and large SVF values. For small SVF (standard fresh asphalts) the runoff develops on the upper surface level, and filling of the surface voids is not always required (especially for the large inclinations). For intermediate SVF (considerably deteriorated asphalts) the runoff develops as well on the upper surface level, but only after considerable filling of the surface voids. Finally, on severely deteriorated asphalts (very large SVFs) the runoff develops on the "bottom" level of asphalt surface, after only partial filling of the surface voids. Other factors, such as drops splash and splitting, also affect the process of runoff initiation and explain rather considerable differences (sometimes of 2-3 mm rain depth) in the runoff thresholds on various non-porous asphalt pavements. Similar phenomena can be probably observed on certain types of rock outcrops.

Face recognition via edge-based Gabor feature representation for plastic surgery-altered images

NASA Astrophysics Data System (ADS)

Chude-Olisah, Chollette C.; Sulong, Ghazali; Chude-Okonkwo, Uche A. K.; Hashim, Siti Z. M.

2014-12-01

Plastic surgery procedures on the face introduce skin texture variations between images of the same person (intra-subject), thereby making the task of face recognition more difficult than in normal scenario. Usually, in contemporary face recognition systems, the original gray-level face image is used as input to the Gabor descriptor, which translates to encoding some texture properties of the face image. The texture-encoding process significantly degrades the performance of such systems in the case of plastic surgery due to the presence of surgically induced intra-subject variations. Based on the proposition that the shape of significant facial components such as eyes, nose, eyebrow, and mouth remains unchanged after plastic surgery, this paper employs an edge-based Gabor feature representation approach for the recognition of surgically altered face images. We use the edge information, which is dependent on the shapes of the significant facial components, to address the plastic surgery-induced texture variation problems. To ensure that the significant facial components represent useful edge information with little or no false edges, a simple illumination normalization technique is proposed for preprocessing. Gabor wavelet is applied to the edge image to accentuate on the uniqueness of the significant facial components for discriminating among different subjects. The performance of the proposed method is evaluated on the Georgia Tech (GT) and the Labeled Faces in the Wild (LFW) databases with illumination and expression problems, and the plastic surgery database with texture changes. Results show that the proposed edge-based Gabor feature representation approach is robust against plastic surgery-induced face variations amidst expression and illumination problems and outperforms the existing plastic surgery face recognition methods reported in the literature.

Skin image retrieval using Gabor wavelet texture feature.

PubMed

Ou, X; Pan, W; Zhang, X; Xiao, P

2016-12-01

Skin imaging plays a key role in many clinical studies. We have used many skin imaging techniques, including the recently developed capacitive contact skin imaging based on fingerprint sensors. The aim of this study was to develop an effective skin image retrieval technique using Gabor wavelet transform, which can be used on different types of skin images, but with a special focus on skin capacitive contact images. Content-based image retrieval (CBIR) is a useful technology to retrieve stored images from database by supplying query images. In a typical CBIR, images are retrieved based on colour, shape, texture, etc. In this study, texture feature is used for retrieving skin images, and Gabor wavelet transform is used for texture feature description and extraction. The results show that the Gabor wavelet texture features can work efficiently on different types of skin images. Although Gabor wavelet transform is slower compared with other image retrieval techniques, such as principal component analysis (PCA) and grey-level co-occurrence matrix (GLCM), Gabor wavelet transform is the best for retrieving skin capacitive contact images and facial images with different orientations. Gabor wavelet transform can also work well on facial images with different expressions and skin cancer/disease images. We have developed an effective skin image retrieval method based on Gabor wavelet transform, that it is useful for retrieving different types of images, namely digital colour face images, digital colour skin cancer and skin disease images, and particularly greyscale skin capacitive contact images. Gabor wavelet transform can also be potentially useful for face recognition (with different orientation and expressions) and skin cancer/disease diagnosis. © 2016 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

Commentary: legal minimum tread depth for passenger car tires in the U.S.A.--a survey.

PubMed

Blythe, William; Seguin, Debra E

2006-06-01

Available tire traction is a significant highway safety issue, particularly on wet roads. Tire-roadway friction on dry, clean roads is essentially independent of tread depth, and depends primarily on roadway surface texture. However, tire-wet-roadway friction, both for longitudinal braking and lateral cornering forces, depends on several variables, most importantly on water depth, speed and tire tread depth, and the roadway surface texture. The car owner-operator has control over speed and tire condition, but not on water depth or road surface texture. Minimum tire tread depth is legislated throughout most of the United States and Europe. Speed reduction for wet road conditions is not.A survey of state requirements for legal minimum tread depth for passenger vehicle tires in the United States is presented. Most states require a minimum of 2/32 of an inch (approximately 1.6 mm) of tread, but two require less, some have no requirements, and some defer to the federal criterion for commercial vehicle safety inspections. The requirement of 2/32 of an inch is consistent with the height of the tread-wear bars built in to passenger car tires sold in the United States, but the rationale for that requirement, or other existing requirements, is not clear. Recent research indicates that a minimum tread depth of 2/32 of an inch does not prevent significant loss of friction at highway speeds, even for minimally wet roadways. The research suggests that tires with less than 4/32 of an inch tread depth may lose approximately 50 percent of available friction in those circumstances, even before hydroplaning occurs. It is concluded that the present requirements for minimum passenger car tire tread depth are not based upon rational safety considerations, and that an increase in the minimum tread depth requirements would have a beneficial effect on highway safety.

High Severity Wildfire Effect On Rainfall Infiltration And Runoff: A Cellular Automata Based Simulation

NASA Astrophysics Data System (ADS)

Vergara-Blanco, J. E.; Leboeuf-Pasquier, J.; Benavides-Solorio, J. D. D.

2017-12-01

A simulation software that reproduces rainfall infiltration and runoff for a storm event in a particular forest area is presented. A cellular automaton is utilized to represent space and time. On the time scale, the simulation is composed by a sequence of discrete time steps. On the space scale, the simulation is composed of forest surface cells. The software takes into consideration rain intensity and length, individual forest cell soil absorption capacity evolution, and surface angle of inclination. The software is developed with the C++ programming language. The simulation is executed on a 100 ha area within La Primavera Forest in Jalisco, Mexico. Real soil texture for unburned terrain and high severity wildfire affected terrain is employed to recreate the specific infiltration profile. Historical rainfall data of a 92 minute event is used. The Horton infiltration equation is utilized for infiltration capacity calculation. A Digital Elevation Model (DEM) is employed to reproduce the surface topography. The DEM is displayed with a 3D mesh graph where individual surface cells can be observed. The plot colouring renders water content development at the cell level throughout the storm event. The simulation shows that the cumulative infiltration and runoff which take place at the surface cell level depend on the specific storm intensity, fluctuation and length, overall terrain topography, cell slope, and soil texture. Rainfall cumulative infiltration for unburned and high severity wildfire terrain are compared: unburned terrain exhibits a significantly higher amount of rainfall infiltration.It is concluded that a cellular automaton can be utilized with a C++ program to reproduce rainfall infiltration and runoff under diverse soil texture, topographic and rainfall conditions in a forest setting. This simulation is geared for an optimization program to pinpoint the locations of a series of forest land remediation efforts to support reforestation or to minimize runoff.

Automated retrieval of forest structure variables based on multi-scale texture analysis of VHR satellite imagery

NASA Astrophysics Data System (ADS)

Beguet, Benoit; Guyon, Dominique; Boukir, Samia; Chehata, Nesrine

2014-10-01

The main goal of this study is to design a method to describe the structure of forest stands from Very High Resolution satellite imagery, relying on some typical variables such as crown diameter, tree height, trunk diameter, tree density and tree spacing. The emphasis is placed on the automatization of the process of identification of the most relevant image features for the forest structure retrieval task, exploiting both spectral and spatial information. Our approach is based on linear regressions between the forest structure variables to be estimated and various spectral and Haralick's texture features. The main drawback of this well-known texture representation is the underlying parameters which are extremely difficult to set due to the spatial complexity of the forest structure. To tackle this major issue, an automated feature selection process is proposed which is based on statistical modeling, exploring a wide range of parameter values. It provides texture measures of diverse spatial parameters hence implicitly inducing a multi-scale texture analysis. A new feature selection technique, we called Random PRiF, is proposed. It relies on random sampling in feature space, carefully addresses the multicollinearity issue in multiple-linear regression while ensuring accurate prediction of forest variables. Our automated forest variable estimation scheme was tested on Quickbird and Pléiades panchromatic and multispectral images, acquired at different periods on the maritime pine stands of two sites in South-Western France. It outperforms two well-established variable subset selection techniques. It has been successfully applied to identify the best texture features in modeling the five considered forest structure variables. The RMSE of all predicted forest variables is improved by combining multispectral and panchromatic texture features, with various parameterizations, highlighting the potential of a multi-resolution approach for retrieving forest structure variables from VHR satellite images. Thus an average prediction error of ˜ 1.1 m is expected on crown diameter, ˜ 0.9 m on tree spacing, ˜ 3 m on height and ˜ 0.06 m on diameter at breast height.

SU-E-J-262: Variability in Texture Analysis of Gynecological Tumors in the Context of An 18F-FDG PET Adaptive Protocol

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nawrocki, J; Chino, J; Das, S

Purpose: This study examines the effect on texture analysis due to variable reconstruction of PET images in the context of an adaptive FDG PET protocol for node positive gynecologic cancer patients. By measuring variability in texture features from baseline and intra-treatment PET-CT, we can isolate unreliable texture features due to large variation. Methods: A subset of seven patients with node positive gynecological cancers visible on PET was selected for this study. Prescribed dose varied between 45–50.4Gy, with a 55–70Gy boost to the PET positive nodes. A baseline and intratreatment (between 30–36Gy) PET-CT were obtained on a Siemens Biograph mCT. Eachmore » clinical PET image set was reconstructed 6 times using a TrueX+TOF algorithm with varying iterations and Gaussian filter. Baseline and intra-treatment primary GTVs were segmented using PET Edge (MIM Software Inc., Cleveland, OH), a semi-automatic gradient-based algorithm, on the clinical PET and transferred to the other reconstructed sets. Using an in-house MATLAB program, four 3D texture matrices describing relationships between voxel intensities in the GTV were generated: co-occurrence, run length, size zone, and neighborhood difference. From these, 39 textural features characterizing texture were calculated in addition to SUV histogram features. The percent variability among parameters was first calculated. Each reconstructed texture feature from baseline and intra-treatment per patient was normalized to the clinical baseline scan and compared using the Wilcoxon signed-rank test in order to isolate variations due to reconstruction parameters. Results: For the baseline scans, 13 texture features showed a mean range greater than 10%. For the intra scans, 28 texture features showed a mean range greater than 10%. Comparing baseline to intra scans, 25 texture features showed p <0.05. Conclusion: Variability due to different reconstruction parameters increased with treatment, however, the majority of texture features showed significant changes during treatment independent of reconstruction effects.« less

Ultrahigh Piezoelectric Properties in Textured (K,Na)NbO3 -Based Lead-Free Ceramics.

PubMed

Li, Peng; Zhai, Jiwei; Shen, Bo; Zhang, Shujun; Li, Xiaolong; Zhu, Fangyuan; Zhang, Xingmin

2018-02-01

High-performance lead-free piezoelectric materials are in great demand for next-generation electronic devices to meet the requirement of environmentally sustainable society. Here, ultrahigh piezoelectric properties with piezoelectric coefficients (d 33 ≈700 pC N -1 , d 33 * ≈980 pm V -1 ) and planar electromechanical coupling factor (k p ≈76%) are achieved in highly textured (K,Na)NbO 3 (KNN)-based ceramics. The excellent piezoelectric properties can be explained by the strong anisotropic feature, optimized engineered domain configuration in the textured ceramics, and facilitated polarization rotation induced by the intermediate phase. In addition, the nanodomain structures with decreased domain wall energy and increased domain wall mobility also contribute to the ultrahigh piezoelectric properties. This work not only demonstrates the tremendous potential of KNN-based ceramics to replace lead-based piezoelectrics but also provides a good strategy to design high-performance piezoelectrics by controlling appropriate phase and crystallographic orientation. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Using Parameters of Dynamic Pulse Function for 3d Modeling in LOD3 Based on Random Textures

NASA Astrophysics Data System (ADS)

Alizadehashrafi, B.

2015-12-01

The pulse function (PF) is a technique based on procedural preprocessing system to generate a computerized virtual photo of the façade with in a fixed size square(Alizadehashrafi et al., 2009, Musliman et al., 2010). Dynamic Pulse Function (DPF) is an enhanced version of PF which can create the final photo, proportional to real geometry. This can avoid distortion while projecting the computerized photo on the generated 3D model(Alizadehashrafi and Rahman, 2013). The challenging issue that might be handled for having 3D model in LoD3 rather than LOD2, is the final aim that have been achieved in this paper. In the technique based DPF the geometries of the windows and doors are saved in an XML file schema which does not have any connections with the 3D model in LoD2 and CityGML format. In this research the parameters of Dynamic Pulse Functions are utilized via Ruby programming language in SketchUp Trimble to generate (exact position and deepness) the windows and doors automatically in LoD3 based on the same concept of DPF. The advantage of this technique is automatic generation of huge number of similar geometries e.g. windows by utilizing parameters of DPF along with defining entities and window layers. In case of converting the SKP file to CityGML via FME software or CityGML plugins the 3D model contains the semantic database about the entities and window layers which can connect the CityGML to MySQL(Alizadehashrafi and Baig, 2014). The concept behind DPF, is to use logical operations to project the texture on the background image which is dynamically proportional to real geometry. The process of projection is based on two vertical and horizontal dynamic pulses starting from upper-left corner of the background wall in down and right directions respectively based on image coordinate system. The logical one/zero on the intersections of two vertical and horizontal dynamic pulses projects/does not project the texture on the background image. It is possible to define priority for each layer. For instance the priority of the door layer can be higher than window layer which means that window texture cannot be projected on the door layer. Orthogonal and rectified perpendicular symmetric photos of the 3D objects that are proportional to the real façade geometry must be utilized for the generation of the output frame for DPF. The DPF produces very high quality and small data size of output image files in quite smaller dimension compare with the photorealistic texturing method. The disadvantage of DPF is its preprocessing method to generate output image file rather than online processing to generate the texture within the 3D environment such as CityGML. Furthermore the result of DPF can be utilized for 3D model in LOD2 rather than LOD3. In the current work the random textures of the window layers are created based on parameters of DPF within Ruby console of SketchUp Trimble to generate the deeper geometries of the windows and their exact position on the façade automatically along with random textures to increase Level of Realism (LoR)(Scarpino, 2010). As the output frame in DPF is proportional to real geometry (height and width of the façade) it is possible to query the XML database and convert them to units such as meter automatically. In this technique, the perpendicular terrestrial photo from the façade is rectified by employing projective transformation based on the frame which is in constrain proportion to real geometry. The rectified photos which are not suitable for texturing but necessary for measuring, can be resized in constrain proportion to real geometry before measuring process. Height and width of windows, doors, horizontal and vertical distance between windows from upper left corner of the photo dimensions of doors and windows are parameters that should be measured to run the program as a plugins in SketchUp Trimble. The system can use these parameters and texture file names and file paths to create the façade semi-automatically. To avoid leaning geometry the textures of windows, doors and etc, should be cropped and rectified from perpendicular photos, so that they can be used in the program to create the whole façade along with its geometries. Texture enhancement should be done in advance such as removing disturbing objects, exposure setting, left-right up-down transformation, and so on. In fact, the quality, small data size, scale and semantic database for each façade are the prominent advantages of this method.

Improved opponent color local binary patterns: an effective local image descriptor for color texture classification

NASA Astrophysics Data System (ADS)

Bianconi, Francesco; Bello-Cerezo, Raquel; Napoletano, Paolo

2018-01-01

Texture classification plays a major role in many computer vision applications. Local binary patterns (LBP) encoding schemes have largely been proven to be very effective for this task. Improved LBP (ILBP) are conceptually simple, easy to implement, and highly effective LBP variants based on a point-to-average thresholding scheme instead of a point-to-point one. We propose the use of this encoding scheme for extracting intra- and interchannel features for color texture classification. We experimentally evaluated the resulting improved opponent color LBP alone and in concatenation with the ILBP of the local color contrast map on a set of image classification tasks over 9 datasets of generic color textures and 11 datasets of biomedical textures. The proposed approach outperformed other grayscale and color LBP variants in nearly all the datasets considered and proved competitive even against image features from last generation convolutional neural networks, particularly for the classification of biomedical images.

The effect of precipitation on the evolution of recrystallization textures in an AA 8011 aluminum alloy sheet

NASA Astrophysics Data System (ADS)

Ryu, Jong-Ho; Lee, Yoon-Soo; Lee, Dong Nyung

2001-06-01

The texture of an AA 8011 aluminum alloy sheet cold rolled by 95% showed a typical β-fiber, which runs from the copper orientation [C={112}<111>] over S [{123}<634>] to brass [B={011}<112>]. The development of annealing textures depended on annealing temperatures due to the interaction between precipitation and recrystallization. Upon annealing at a low temperature of 275°C, precipitation took place before recrystallization. This led to a weak recrystallization texture consisting of {011}<122>, {001˜<100>, and {hk0}<001>, among which the {011}<122> orientation developed near large FeAl3 particles as the main orientation and the cube [{001}<100>] orientation originating from the matrix was relatively weak. After annealing at 350 and 500°C, a strong cube texture developed along with a weak {011}<122> orientation. When the cube orientation developed, the copper orientation disappeared most rapidly. These results were discussed based on the interaction between precipitation and recrystallization.

Frictional Behavior of Micro/nanotextured Surfaces Investigated by Atomic Force Microscope: a Review

NASA Astrophysics Data System (ADS)

Zhang, Xiaoliang; Jia, Junhong

2015-08-01

Tribological issues between friction pair are fundamental problems for minimized devices because of their higher surface-to-volume ratio. Micro/nanotexturing is an effective technique to reduce actual contact area between contact pair at the nanoscale. Micro/nanotexture made a great impact on the frictional behavior of textured surfaces. This paper summarizes the recent advancements in the field of frictional behavior of micro/nanotextured surfaces, which are based on solid surface contact in atmosphere environment, especially focusing on the factors influencing the frictional behavior: Surface property, texturing density, texturing height, texturing structure and size of contact pair (atomic force microscope (AFM) tip) and texturing structures. Summarizing the effects of these factors on the frictional behavior is helpful for the understanding and designing of the surfaces in sliding micro/nanoelectromechanical systems (MEMS/NEMS). Controlling and reducing the friction force in moving mechanical systems is very important for the performance and reliability of nanosystems, which contribute to a sustainable future.

The relation of apple texture with cell wall nanostructure studied using an atomic force microscope.

PubMed

Cybulska, Justyna; Zdunek, Artur; Psonka-Antonczyk, Katarzyna M; Stokke, Bjørn T

2013-01-30

In this study, the relation of the nanostructure of cell walls with their texture was investigated for six different apple cultivars. Cell wall material (CWM) and cellulose microfibrils were imaged by atomic force microscope (AFM). The mean diameter of cellulose microfibrils for each cultivar was estimated based on the AFM height topographs obtained using the tapping mode of dried specimens. Additionally, crystallinity of cellulose microfibrils and pectin content was determined. Texture of apple cultivars was evaluated by sensory and instrumental analysis. Differences in cellulose diameter as determined from the AFM height topographs of the nanostructure of cell walls of the apple cultivars are found to relate to the degree of crystallinity and pectin content. Cultivars with thicker cellulose microfibrils also revealed crisper, harder and juicier texture, and greater acoustic emission. The data suggest that microfibril thickness affects the mechanical strength of cell walls which has consequences for sensory and instrumental texture. Copyright © 2012 Elsevier Ltd. All rights reserved.

Inference of segmented color and texture description by tensor voting.

PubMed

Jia, Jiaya; Tang, Chi-Keung

2004-06-01

A robust synthesis method is proposed to automatically infer missing color and texture information from a damaged 2D image by (N)D tensor voting (N > 3). The same approach is generalized to range and 3D data in the presence of occlusion, missing data and noise. Our method translates texture information into an adaptive (N)D tensor, followed by a voting process that infers noniteratively the optimal color values in the (N)D texture space. A two-step method is proposed. First, we perform segmentation based on insufficient geometry, color, and texture information in the input, and extrapolate partitioning boundaries by either 2D or 3D tensor voting to generate a complete segmentation for the input. Missing colors are synthesized using (N)D tensor voting in each segment. Different feature scales in the input are automatically adapted by our tensor scale analysis. Results on a variety of difficult inputs demonstrate the effectiveness of our tensor voting approach.

Highly ultraviolet transparent textured indium tin oxide thin films and the application in light emitting diodes

NASA Astrophysics Data System (ADS)

Chen, Zimin; Zhuo, Yi; Tu, Wenbin; Ma, Xuejin; Pei, Yanli; Wang, Chengxin; Wang, Gang

2017-06-01

Various kinds of materials have been developed as transparent conductors for applications in semiconductor optoelectronic devices. However, there is a bottleneck that transparent conductive materials lose their transparency at ultraviolet (UV) wavelengths and could not meet the demands for commercial UV device applications. In this work, textured indium tin oxide (ITO) is grown and its potential to be used at UV wavelengths is explored. It is observed that the pronounced Burstein-Moss effect could widen the optical bandgap of the textured ITO to 4.7 eV. The average transmittance in UVA (315 nm-400 nm) and UVB (280 nm-315 nm) ranges is as high as 94% and 74%, respectively. The excellent optical property of textured ITO is attributed to its unique structural property. The compatibility of textured ITO thin films to the device fabrication is demonstrated on 368-nm nitride-based light emitting diodes, and the enhancement of light output power by 14.8% is observed compared to sputtered ITO.

Quantification of Microtexture at Weld Nugget of Friction Stir-Welded Carbon Steel

NASA Astrophysics Data System (ADS)

Husain, Md M.; Sarkar, R.; Pal, T. K.; Ghosh, M.; Prabhu, N.

2017-05-01

Friction stir welding of C-Mn steel was carried out under 800-1400 rpm tool rotation. Tool traversing speed of 50 mm/min remained same for all joints. Effect of thermal state and deformation on texture and microstructure at weld nugget was investigated. Weld nugget consisted of ferrite + bainite/Widmanstatten ferrite with different matrix grain sizes depending on peak temperature. A texture around ( ϕ 2 = 0°, φ = 30°, ϕ 2 = 45°) was developed at weld nugget. Grain boundary misorientation at weld nugget indicated that continuous dynamic recrystallization influenced the development of fine equiaxed grain structure. Pole figures and orientation distribution function were used to determine crystallographic texture at weld nugget and base metal. Shear texture components D1, D2 and F were present at weld nugget. D1 shear texture was more prominent among all. Large number of high-angle grain boundaries ( 60-70%) was observed at weld nugget and was the resultant of accumulation of high amount of dislocation, followed by subgrain formation.

Stratigraphic reconstruction of two debris avalanche deposits at Colima Volcano (Mexico): Insights into pre-failure conditions and climate influence

NASA Astrophysics Data System (ADS)

Roverato, M.; Capra, L.; Sulpizio, R.; Norini, G.

2011-10-01

Throughout its history, Colima Volcano has experienced numerous partial edifice collapses with associated emplacement of debris avalanche deposits of contrasting volume, morphology and texture. A detailed stratigraphic study in the south-eastern sector of the volcano allowed the recognition of two debris avalanche deposits, named San Marcos (> 28,000 cal yr BP, V = ~ 1.3 km 3) and Tonila (15,000-16,000 cal yr BP, V = ~ 1 km 3 ). This work sheds light on the pre-failure conditions of the volcano based primarily on a detailed textural study of debris avalanche deposits and their associated pyroclastic and volcaniclastic successions. Furthermore, we show how the climate at the time of the Tonila collapse influenced the failure mechanisms. The > 28,000 cal yr BP San Marcos collapse was promoted by edifice steep flanks and ongoing tectonic and volcanotectonic deformation, and was followed by a magmatic eruption that emplaced pyroclastic flow deposits. In contrast, the Tonila failure occurred just after the Last Glacial Maximum (22,000-18,000 cal BP) and, in addition to the typical debris avalanche textural characteristics (angular to sub-angular clasts, coarse matrix, jigsaw fit) it shows a hybrid facies characterized by debris avalanche blocks embedded in a finer, homogenous and partially cemented matrix, a texture more characteristic of debris flow deposits. The Tonila debris avalanche is directly overlain by a 7-m thick hydromagmatic pyroclastic succession. Massive debris flow deposits, often more than 10 m thick and containing large amounts of tree trunk logs, represent the top unit in the succession. Fluvial deposits also occur throughout all successions; these represent periods of highly localized stream reworking. All these lines of evidence point to the presence of water in the edifice prior to the Tonila failure, suggesting it may have been a weakening factor. The Tonila failure appears to represent an anomalous event related to the particular climatic conditions at the time of the collapse. The presence of extensive water at the onset of deglaciation modified the mobility of the debris avalanche, and led to the formation of a thick sequence of debris flows. The possibility that such a combination of events can occur, and that their probability is likely to increase during the rainy season, should be taken into consideration when evaluating hazards associated with future collapses at Colima volcano.

Texture classification of normal tissues in computed tomography using Gabor filters

NASA Astrophysics Data System (ADS)

Dettori, Lucia; Bashir, Alia; Hasemann, Julie

2007-03-01

The research presented in this article is aimed at developing an automated imaging system for classification of normal tissues in medical images obtained from Computed Tomography (CT) scans. Texture features based on a bank of Gabor filters are used to classify the following tissues of interests: liver, spleen, kidney, aorta, trabecular bone, lung, muscle, IP fat, and SQ fat. The approach consists of three steps: convolution of the regions of interest with a bank of 32 Gabor filters (4 frequencies and 8 orientations), extraction of two Gabor texture features per filter (mean and standard deviation), and creation of a Classification and Regression Tree-based classifier that automatically identifies the various tissues. The data set used consists of approximately 1000 DIACOM images from normal chest and abdominal CT scans of five patients. The regions of interest were labeled by expert radiologists. Optimal trees were generated using two techniques: 10-fold cross-validation and splitting of the data set into a training and a testing set. In both cases, perfect classification rules were obtained provided enough images were available for training (~65%). All performance measures (sensitivity, specificity, precision, and accuracy) for all regions of interest were at 100%. This significantly improves previous results that used Wavelet, Ridgelet, and Curvelet texture features, yielding accuracy values in the 85%-98% range The Gabor filters' ability to isolate features at different frequencies and orientations allows for a multi-resolution analysis of texture essential when dealing with, at times, very subtle differences in the texture of tissues in CT scans.

Histogram-based adaptive gray level scaling for texture feature classification of colorectal polyps

NASA Astrophysics Data System (ADS)

Pomeroy, Marc; Lu, Hongbing; Pickhardt, Perry J.; Liang, Zhengrong

2018-02-01

Texture features have played an ever increasing role in computer aided detection (CADe) and diagnosis (CADx) methods since their inception. Texture features are often used as a method of false positive reduction for CADe packages, especially for detecting colorectal polyps and distinguishing them from falsely tagged residual stool and healthy colon wall folds. While texture features have shown great success there, the performance of texture features for CADx have lagged behind primarily because of the more similar features among different polyps types. In this paper, we present an adaptive gray level scaling and compare it to the conventional equal-spacing of gray level bins. We use a dataset taken from computed tomography colonography patients, with 392 polyp regions of interest (ROIs) identified and have a confirmed diagnosis through pathology. Using the histogram information from the entire ROI dataset, we generate the gray level bins such that each bin contains roughly the same number of voxels Each image ROI is the scaled down to two different numbers of gray levels, using both an equal spacing of Hounsfield units for each bin, and our adaptive method. We compute a set of texture features from the scaled images including 30 gray level co-occurrence matrix (GLCM) features and 11 gray level run length matrix (GLRLM) features. Using a random forest classifier to distinguish between hyperplastic polyps and all others (adenomas and adenocarcinomas), we find that the adaptive gray level scaling can improve performance based on the area under the receiver operating characteristic curve by up to 4.6%.

Variability in soil-water retention properties and implications for physics-based simulation of landslide early warning criteria

USGS Publications Warehouse

Thomas, Matthew A.; Mirus, Benjamin B.; Collins, Brian D.; Lu, Ning; Godt, Jonathan W.

2018-01-01

Rainfall-induced shallow landsliding is a persistent hazard to human life and property. Despite the observed connection between infiltration through the unsaturated zone and shallow landslide initiation, there is considerable uncertainty in how estimates of unsaturated soil-water retention properties affect slope stability assessment. This source of uncertainty is critical to evaluating the utility of physics-based hydrologic modeling as a tool for landslide early warning. We employ a numerical model of variably saturated groundwater flow parameterized with an ensemble of texture-, laboratory-, and field-based estimates of soil-water retention properties for an extensively monitored landslide-prone site in the San Francisco Bay Area, CA, USA. Simulations of soil-water content, pore-water pressure, and the resultant factor of safety show considerable variability across and within these different parameter estimation techniques. In particular, we demonstrate that with the same permeability structure imposed across all simulations, the variability in soil-water retention properties strongly influences predictions of positive pore-water pressure coincident with widespread shallow landsliding. We also find that the ensemble of soil-water retention properties imposes an order-of-magnitude and nearly two-fold variability in seasonal and event-scale landslide susceptibility, respectively. Despite the reduced factor of safety uncertainty during wet conditions, parameters that control the dry end of the soil-water retention function markedly impact the ability of a hydrologic model to capture soil-water content dynamics observed in the field. These results suggest that variability in soil-water retention properties should be considered for objective physics-based simulation of landslide early warning criteria.

Research for Key Techniques of Geophysical Recognition System of Hydrocarbon-induced Magnetic Anomalies Based on Hydrocarbon Seepage Theory

NASA Astrophysics Data System (ADS)

Zhang, L.; Hao, T.; Zhao, B.

2009-12-01

Hydrocarbon seepage effects can cause magnetic alteration zones in near surface, and the magnetic anomalies induced by the alteration zones can thus be used to locate oil-gas potential regions. In order to reduce the inaccuracy and multi-resolution of the hydrocarbon anomalies recognized only by magnetic data, and to meet the requirement of integrated management and sythetic analysis of multi-source geoscientfic data, it is necessary to construct a recognition system that integrates the functions of data management, real-time processing, synthetic evaluation, and geologic mapping. In this paper research for the key techniques of the system is discussed. Image processing methods can be applied to potential field images so as to make it easier for visual interpretation and geological understanding. For gravity or magnetic images, the anomalies with identical frequency-domain characteristics but different spatial distribution will reflect differently in texture and relevant textural statistics. Texture is a description of structural arrangements and spatial variation of a dataset or an image, and has been applied in many research fields. Textural analysis is a procedure that extracts textural features by image processing methods and thus obtains a quantitative or qualitative description of texture. When the two kinds of anomalies have no distinct difference in amplitude or overlap in frequency spectrum, they may be distinguishable due to their texture, which can be considered as textural contrast. Therefore, for the recognition system we propose a new “magnetic spots” recognition method based on image processing techniques. The method can be divided into 3 major steps: firstly, separate local anomalies caused by shallow, relatively small sources from the total magnetic field, and then pre-process the local magnetic anomaly data by image processing methods such that magnetic anomalies can be expressed as points, lines and polygons with spatial correlation, which includes histogram-equalization based image display, object recognition and extraction; then, mine the spatial characteristics and correlations of the magnetic anomalies using textural statistics and analysis, and study the features of known anomalous objects (closures, hydrocarbon-bearing structures, igneous rocks, etc.) in the same research area; finally, classify the anomalies, cluster them according to their similarity, and predict hydrocarbon induced “magnetic spots” combined with geologic, drilling and rock core data. The system uses the ArcGIS as the secondary development platform, inherits the basic functions of the ArcGIS, and develops two main sepecial functional modules, the module for conventional potential-field data processing methods and the module for feature extraction and enhancement based on image processing and analysis techniques. The system can be applied to realize the geophysical detection and recognition of near-surface hydrocarbon seepage anomalies, provide technical support for locating oil-gas potential regions, and promote geophysical data processing and interpretation to advance more efficiently.

Texture Feature Extraction and Classification for Iris Diagnosis

NASA Astrophysics Data System (ADS)

Ma, Lin; Li, Naimin

Appling computer aided techniques in iris image processing, and combining occidental iridology with the traditional Chinese medicine is a challenging research area in digital image processing and artificial intelligence. This paper proposes an iridology model that consists the iris image pre-processing, texture feature analysis and disease classification. To the pre-processing, a 2-step iris localization approach is proposed; a 2-D Gabor filter based texture analysis and a texture fractal dimension estimation method are proposed for pathological feature extraction; and at last support vector machines are constructed to recognize 2 typical diseases such as the alimentary canal disease and the nerve system disease. Experimental results show that the proposed iridology diagnosis model is quite effective and promising for medical diagnosis and health surveillance for both hospital and public use.

Aircraft Detection in High-Resolution SAR Images Based on a Gradient Textural Saliency Map.

PubMed

Tan, Yihua; Li, Qingyun; Li, Yansheng; Tian, Jinwen

2015-09-11

This paper proposes a new automatic and adaptive aircraft target detection algorithm in high-resolution synthetic aperture radar (SAR) images of airport. The proposed method is based on gradient textural saliency map under the contextual cues of apron area. Firstly, the candidate regions with the possible existence of airport are detected from the apron area. Secondly, directional local gradient distribution detector is used to obtain a gradient textural saliency map in the favor of the candidate regions. In addition, the final targets will be detected by segmenting the saliency map using CFAR-type algorithm. The real high-resolution airborne SAR image data is used to verify the proposed algorithm. The results demonstrate that this algorithm can detect aircraft targets quickly and accurately, and decrease the false alarm rate.

Growth and characterization of textured well-faceted ZnO on planar Si(100), planar Si(111), and textured Si(100) substrates for solar cell applications.

PubMed

Tsai, Chin-Yi; Lai, Jyong-Di; Feng, Shih-Wei; Huang, Chien-Jung; Chen, Chien-Hsun; Yang, Fann-Wei; Wang, Hsiang-Chen; Tu, Li-Wei

2017-01-01

In this work, textured, well-faceted ZnO materials grown on planar Si(100), planar Si(111), and textured Si(100) substrates by low-pressure chemical vapor deposition (LPCVD) were analyzed by X-ray diffraction (XRD), scanning electron microscopy (SEM), atomic force microscopy (AFM), and cathode luminescence (CL) measurements. The results show that ZnO grown on planar Si(100), planar Si(111), and textured Si(100) substrates favor the growth of ZnO(110) ridge-like, ZnO(002) pyramid-like, and ZnO(101) pyramidal-tip structures, respectively. This could be attributed to the constraints of the lattice mismatch between the ZnO and Si unit cells. The average grain size of ZnO on the planar Si(100) substrate is slightly larger than that on the planar Si(111) substrate, while both of them are much larger than that on the textured Si(100) substrate. The average grain sizes (about 10-50 nm) of the ZnO grown on the different silicon substrates decreases with the increase of their strains. These results are shown to strongly correlate with the results from the SEM, AFM, and CL as well. The reflectance spectra of these three samples show that the antireflection function provided by theses samples mostly results from the nanometer-scaled texture of the ZnO films, while the micrometer-scaled texture of the Si substrate has a limited contribution. The results of this work provide important information for optimized growth of textured and well-faceted ZnO grown on wafer-based silicon solar cells and can be utilized for efficiency enhancement and optimization of device materials and structures, such as heterojunction with intrinsic thin layer (HIT) solar cells.

Parenchymal texture measures weighted by breast anatomy: preliminary optimization in a case-control study

NASA Astrophysics Data System (ADS)

Gastounioti, Aimilia; Keller, Brad M.; Hsieh, Meng-Kang; Conant, Emily F.; Kontos, Despina

2016-03-01

Growing evidence suggests that quantitative descriptors of the parenchymal texture patterns hold a valuable role in assessing an individual woman's risk for breast cancer. In this work, we assess the hypothesis that breast cancer risk factors are not uniformly expressed in the breast parenchymal tissue and, therefore, breast-anatomy-weighted parenchymal texture descriptors, where different breasts ROIs have non uniform contributions, may enhance breast cancer risk assessment. To this end, we introduce an automated breast-anatomy-driven methodology which generates a breast atlas, which is then used to produce a weight map that reinforces the contributions of the central and upper-outer breast areas. We incorporate this methodology to our previously validated lattice-based strategy for parenchymal texture analysis. In the framework of a pilot case-control study, including digital mammograms from 424 women, our proposed breast-anatomy-weighted texture descriptors are optimized and evaluated against non weighted texture features, using regression analysis with leave-one-out cross validation. The classification performance is assessed in terms of the area under the curve (AUC) of the receiver operating characteristic. The collective discriminatory capacity of the weighted texture features was maximized (AUC=0.87) when the central breast area was considered more important than the upperouter area, with significant performance improvement (DeLong's test, p-value<0.05) against the non-weighted texture features (AUC=0.82). Our results suggest that breast-anatomy-driven methodologies have the potential to further upgrade the promising role of parenchymal texture analysis in breast cancer risk assessment and may serve as a reference in the design of future studies towards image-driven personalized recommendations regarding women's cancer risk evaluation.

Surface inspection of flat products by means of texture analysis: on-line implementation using neural networks

NASA Astrophysics Data System (ADS)

Fernandez, Carlos; Platero, Carlos; Campoy, Pascual; Aracil, Rafael

1994-11-01

This paper describes some texture-based techniques that can be applied to quality assessment of flat products continuously produced (metal strips, wooden surfaces, cork, textile products, ...). Since the most difficult task is that of inspecting for product appearance, human-like inspection ability is required. A common feature to all these products is the presence of non- deterministic texture on their surfaces. Two main subjects are discussed: statistical techniques for both surface finishing determination and surface defect analysis as well as real-time implementation for on-line inspection in high-speed applications. For surface finishing determination a Gray Level Difference technique is presented to perform over low resolution images, that is, no-zoomed images. Defect analysis is performed by means of statistical texture analysis over defective portions of the surface. On-line implementation is accomplished by means of neural networks. When a defect arises, textural analysis is applied which result in a data-vector, acting as input of a neural net, previously trained in a supervised way. This approach tries to reach on-line performance in automated visual inspection applications when texture is presented in flat product surfaces.

Semiconductor films on flexible iridium substrates

DOEpatents

Goyal, Amit

2005-03-29

A laminate semiconductor article includes a flexible substrate, an optional biaxially textured oxide buffer system on the flexible substrate, a biaxially textured Ir-based buffer layer on the substrate or the buffer system, and an epitaxial layer of a semiconductor. Ir can serve as a substrate with an epitaxial layer of a semiconductor thereon.

Texture properties of raw and cooked broiler breast fillets with the wooden breast condition

USDA-ARS?s Scientific Manuscript database

This study evaluated the effects of the wooden breast condition (WBC) on the texture properties of raw and cooked broiler breast fillets (Pectoralis major). Breast fillets (deboned at 3 h postmortem) were collected from a commercial broiler processing plant based on the wooden breast condition (norm...

3D Texture Analysis in Renal Cell Carcinoma Tissue Image Grading

PubMed Central

Cho, Nam-Hoon; Choi, Heung-Kook

2014-01-01

One of the most significant processes in cancer cell and tissue image analysis is the efficient extraction of features for grading purposes. This research applied two types of three-dimensional texture analysis methods to the extraction of feature values from renal cell carcinoma tissue images, and then evaluated the validity of the methods statistically through grade classification. First, we used a confocal laser scanning microscope to obtain image slices of four grades of renal cell carcinoma, which were then reconstructed into 3D volumes. Next, we extracted quantitative values using a 3D gray level cooccurrence matrix (GLCM) and a 3D wavelet based on two types of basis functions. To evaluate their validity, we predefined 6 different statistical classifiers and applied these to the extracted feature sets. In the grade classification results, 3D Haar wavelet texture features combined with principal component analysis showed the best discrimination results. Classification using 3D wavelet texture features was significantly better than 3D GLCM, suggesting that the former has potential for use in a computer-based grading system. PMID:25371701

An application of Chan-Vese method used to determine the ROI area in CT lung screening

NASA Astrophysics Data System (ADS)

Prokop, Paweł; Surtel, Wojciech

2016-09-01

The article presents two approaches of determining the ROI area in CT lung screening. First approach is based on a classic method of framing the image in order to determine the ROI by using a MaZda tool. Second approach is based on segmentation of CT images of the lungs and reducing the redundant information from the image. Of the two approaches of an Active Contour, it was decided to choose the Chan-Vese method. In order to determine the effectiveness of the approach, it was performed an analysis of received ROI texture and extraction of textural features. In order to determine the effectiveness of the method, it was performed an analysis of the received ROI textures and extraction of the texture features, by using a Mazda tool. The results were compared and presented in the form of the radar graphs. The second approach proved to be effective and appropriate and consequently it is used for further analysis of CT images, in the computer-aided diagnosis of sarcoidosis.

Modeling the Flow Behavior, Recrystallization, and Crystallographic Texture in Hot-Deformed Fe-30 Wt Pct Ni Austenite

NASA Astrophysics Data System (ADS)

Abbod, M. F.; Sellars, C. M.; Cizek, P.; Linkens, D. A.; Mahfouf, M.

2007-10-01

The present work describes a hybrid modeling approach developed for predicting the flow behavior, recrystallization characteristics, and crystallographic texture evolution in a Fe-30 wt pct Ni austenitic model alloy subjected to hot plane strain compression. A series of compression tests were performed at temperatures between 850 °C and 1050 °C and strain rates between 0.1 and 10 s-1. The evolution of grain structure, crystallographic texture, and dislocation substructure was characterized in detail for a deformation temperature of 950 °C and strain rates of 0.1 and 10 s-1, using electron backscatter diffraction and transmission electron microscopy. The hybrid modeling method utilizes a combination of empirical, physically-based, and neuro-fuzzy models. The flow stress is described as a function of the applied variables of strain rate and temperature using an empirical model. The recrystallization behavior is predicted from the measured microstructural state variables of internal dislocation density, subgrain size, and misorientation between subgrains using a physically-based model. The texture evolution is modeled using artificial neural networks.

A new Downscaling Approach for SMAP, SMOS and ASCAT by predicting sub-grid Soil Moisture Variability based on Soil Texture

NASA Astrophysics Data System (ADS)

Montzka, C.; Rötzer, K.; Bogena, H. R.; Vereecken, H.

2017-12-01

Improving the coarse spatial resolution of global soil moisture products from SMOS, SMAP and ASCAT is currently an up-to-date topic. Soil texture heterogeneity is known to be one of the main sources of soil moisture spatial variability. A method has been developed that predicts the soil moisture standard deviation as a function of the mean soil moisture based on soil texture information. It is a closed-form expression using stochastic analysis of 1D unsaturated gravitational flow in an infinitely long vertical profile based on the Mualem-van Genuchten model and first-order Taylor expansions. With the recent development of high resolution maps of basic soil properties such as soil texture and bulk density, relevant information to estimate soil moisture variability within a satellite product grid cell is available. Here, we predict for each SMOS, SMAP and ASCAT grid cell the sub-grid soil moisture variability based on the SoilGrids1km data set. We provide a look-up table that indicates the soil moisture standard deviation for any given soil moisture mean. The resulting data set provides important information for downscaling coarse soil moisture observations of the SMOS, SMAP and ASCAT missions. Downscaling SMAP data by a field capacity proxy indicates adequate accuracy of the sub-grid soil moisture patterns.

Please Don't Move-Evaluating Motion Artifact From Peripheral Quantitative Computed Tomography Scans Using Textural Features.

PubMed

Rantalainen, Timo; Chivers, Paola; Beck, Belinda R; Robertson, Sam; Hart, Nicolas H; Nimphius, Sophia; Weeks, Benjamin K; McIntyre, Fleur; Hands, Beth; Siafarikas, Aris

Most imaging methods, including peripheral quantitative computed tomography (pQCT), are susceptible to motion artifacts particularly in fidgety pediatric populations. Methods currently used to address motion artifact include manual screening (visual inspection) and objective assessments of the scans. However, previously reported objective methods either cannot be applied on the reconstructed image or have not been tested for distal bone sites. Therefore, the purpose of the present study was to develop and validate motion artifact classifiers to quantify motion artifact in pQCT scans. Whether textural features could provide adequate motion artifact classification performance in 2 adolescent datasets with pQCT scans from tibial and radial diaphyses and epiphyses was tested. The first dataset was split into training (66% of sample) and validation (33% of sample) datasets. Visual classification was used as the ground truth. Moderate to substantial classification performance (J48 classifier, kappa coefficients from 0.57 to 0.80) was observed in the validation dataset with the novel texture-based classifier. In applying the same classifier to the second cross-sectional dataset, a slight-to-fair (κ = 0.01-0.39) classification performance was observed. Overall, this novel textural analysis-based classifier provided a moderate-to-substantial classification of motion artifact when the classifier was specifically trained for the measurement device and population. Classification based on textural features may be used to prescreen obviously acceptable and unacceptable scans, with a subsequent human-operated visual classification of any remaining scans. Copyright © 2017 The International Society for Clinical Densitometry. Published by Elsevier Inc. All rights reserved.

Automatic small bowel tumor diagnosis by using multi-scale wavelet-based analysis in wireless capsule endoscopy images.

PubMed

Barbosa, Daniel C; Roupar, Dalila B; Ramos, Jaime C; Tavares, Adriano C; Lima, Carlos S

2012-01-11

Wireless capsule endoscopy has been introduced as an innovative, non-invasive diagnostic technique for evaluation of the gastrointestinal tract, reaching places where conventional endoscopy is unable to. However, the output of this technique is an 8 hours video, whose analysis by the expert physician is very time consuming. Thus, a computer assisted diagnosis tool to help the physicians to evaluate CE exams faster and more accurately is an important technical challenge and an excellent economical opportunity. The set of features proposed in this paper to code textural information is based on statistical modeling of second order textural measures extracted from co-occurrence matrices. To cope with both joint and marginal non-Gaussianity of second order textural measures, higher order moments are used. These statistical moments are taken from the two-dimensional color-scale feature space, where two different scales are considered. Second and higher order moments of textural measures are computed from the co-occurrence matrices computed from images synthesized by the inverse wavelet transform of the wavelet transform containing only the selected scales for the three color channels. The dimensionality of the data is reduced by using Principal Component Analysis. The proposed textural features are then used as the input of a classifier based on artificial neural networks. Classification performances of 93.1% specificity and 93.9% sensitivity are achieved on real data. These promising results open the path towards a deeper study regarding the applicability of this algorithm in computer aided diagnosis systems to assist physicians in their clinical practice.

The combined effect of mammographic texture and density on breast cancer risk: a cohort study.

PubMed

Wanders, Johanna O P; van Gils, Carla H; Karssemeijer, Nico; Holland, Katharina; Kallenberg, Michiel; Peeters, Petra H M; Nielsen, Mads; Lillholm, Martin

2018-05-02

Texture patterns have been shown to improve breast cancer risk segregation in addition to area-based mammographic density. The additional value of texture pattern scores on top of volumetric mammographic density measures in a large screening cohort has never been studied. Volumetric mammographic density and texture pattern scores were assessed automatically for the first available digital mammography (DM) screening examination of 51,400 women (50-75 years of age) participating in the Dutch biennial breast cancer screening program between 2003 and 2011. The texture assessment method was developed in a previous study and validated in the current study. Breast cancer information was obtained from the screening registration system and through linkage with the Netherlands Cancer Registry. All screen-detected breast cancers diagnosed at the first available digital screening examination were excluded. During a median follow-up period of 4.2 (interquartile range (IQR) 2.0-6.2) years, 301 women were diagnosed with breast cancer. The associations between texture pattern scores, volumetric breast density measures and breast cancer risk were determined using Cox proportional hazard analyses. Discriminatory performance was assessed using c-indices. The median age of the women at the time of the first available digital mammography examination was 56 years (IQR 51-63). Texture pattern scores were positively associated with breast cancer risk (hazard ratio (HR) 3.16 (95% CI 2.16-4.62) (p value for trend <0.001), for quartile (Q) 4 compared to Q1). The c-index of texture was 0.61 (95% CI 0.57-0.64). Dense volume and percentage dense volume showed positive associations with breast cancer risk (HR 1.85 (95% CI 1.32-2.59) (p value for trend <0.001) and HR 2.17 (95% CI 1.51-3.12) (p value for trend <0.001), respectively, for Q4 compared to Q1). When adding texture measures to models with dense volume or percentage dense volume, c-indices increased from 0.56 (95% CI 0.53-0.59) to 0.62 (95% CI 0.58-0.65) (p < 0.001) and from 0.58 (95% CI 0.54-0.61) to 0.60 (95% CI 0.57-0.63) (p = 0.054), respectively. Deep-learning-based texture pattern scores, measured automatically on digital mammograms, are associated with breast cancer risk, independently of volumetric mammographic density, and augment the capacity to discriminate between future breast cancer and non-breast cancer cases.

Uncertainty in Pedotransfer Functions from Soil Survey Data

NASA Astrophysics Data System (ADS)

Pachepsky, Y. A.; Rawls, W. J.

2002-05-01

Pedotransfer functions (PTFs) are empirical relationships between hard-to-get soil parameters, i.e. hydraulic properties, and more easily obtainable basic soil properties, such as texture. Use of PTFs in large-scale projects and pilot studies relies on data of soil survey that provides soil basic data as a categorical information. Unlike numerical variables, categorical data cannot be directly used in statistical regressions or neural networks to develop PTFs. Objectives of this work were (a) to find and test techniques to develop PTFs for soil water retention and saturated hydraulic conductivity with soil categorical data as inputs, (b) to evaluate sources of uncertainty in results of such PTFs and to research opportunities of mitigating the uncertainty. We used a subset of about 12,000 samples from the US National Soil characterization database to estimate water retention, and the data set for circa 1000 hydraulic conductivity measurements done in the US. Regression trees and polynomial neural networks based on dummy coding were the techniques tried for the PTF development. The jackknife validation was used to prevent the over-parameterization. Both techniques were equally efficient in developing PTFs, but regression trees gave much more transparent results. Textural class was the leading predictor with RMSE values of about 6.5 and 4.1 vol.% for water retention at -33 and -1500 kPa, respectively. The RMSE values decreased 10% when the laboratory textural analysis was used to establish the textural class. Textural class in the field was determined correctly only in 41% of all cases. To mitigate this source of error, we added slopes, position on the slope classes, and land surface shape classes to the list of PTF inputs. Regression trees generated topotextural groups that encompassed several textural classes. Using topographic variables and soil horizon appeared to be the way to make up for errors made in field determination of texture. Adding field descriptors of soil structure to the field-determined textural class gave similar results. No large improvement was achieved probably because textural class, topographic descriptors and structure descriptors were correlated predictors in many cases. Both median values and uncertainty of the saturated hydraulic conductivity had a power-law decrease as clay content increased. Defining two classes of bulk density helped to estimate hydraulic conductivity within textural classes. We conclude that categorical field soil survey data can be used in PTF-based estimating soil water retention and saturated hydraulic conductivity with quantified uncertainty

Use of registration-based contour propagation in texture analysis for esophageal cancer pathologic response prediction

NASA Astrophysics Data System (ADS)

Yip, Stephen S. F.; Coroller, Thibaud P.; Sanford, Nina N.; Huynh, Elizabeth; Mamon, Harvey; Aerts, Hugo J. W. L.; Berbeco, Ross I.

2016-01-01

Change in PET-based textural features has shown promise in predicting cancer response to treatment. However, contouring tumour volumes on longitudinal scans is time-consuming. This study investigated the usefulness of contour propagation in texture analysis for the purpose of pathologic response prediction in esophageal cancer. Forty-five esophageal cancer patients underwent PET/CT scans before and after chemo-radiotherapy. Patients were classified into responders and non-responders after the surgery. Physician-defined tumour ROIs on pre-treatment PET were propagated onto the post-treatment PET using rigid and ten deformable registration algorithms. PET images were converted into 256 discrete values. Co-occurrence, run-length, and size zone matrix textures were computed within all ROIs. The relative difference of each texture at different treatment time-points was used to predict the pathologic responders. Their predictive value was assessed using the area under the receiver-operating-characteristic curve (AUC). Propagated ROIs from different algorithms were compared using Dice similarity index (DSI). Contours propagated by the fast-demons, fast-free-form and rigid algorithms did not fully capture the high FDG uptake regions of tumours. Fast-demons propagated ROIs had the least agreement with other contours (DSI  =  58%). Moderate to substantial overlap were found in the ROIs propagated by all other algorithms (DSI  =  69%-79%). Rigidly propagated ROIs with co-occurrence texture failed to significantly differentiate between responders and non-responders (AUC  =  0.58, q-value  =  0.33), while the differentiation was significant with other textures (AUC  =  0.71‒0.73, p  <  0.009). Among the deformable algorithms, fast-demons (AUC  =  0.68‒0.70, q-value  <  0.03) and fast-free-form (AUC  =  0.69‒0.74, q-value  <  0.04) were the least predictive. ROIs propagated by all other deformable algorithms with any texture significantly predicted pathologic responders (AUC  =  0.72‒0.78, q-value  <  0.01). Propagated ROIs using deformable registration for all textures can lead to accurate prediction of pathologic response, potentially expediting the temporal texture analysis process. However, fast-demons, fast-free-form, and rigid algorithms should be applied with care due to their inferior performance compared to other algorithms.

Deep learning and texture-based semantic label fusion for brain tumor segmentation

NASA Astrophysics Data System (ADS)

Vidyaratne, L.; Alam, M.; Shboul, Z.; Iftekharuddin, K. M.

2018-02-01

Brain tumor segmentation is a fundamental step in surgical treatment and therapy. Many hand-crafted and learning based methods have been proposed for automatic brain tumor segmentation from MRI. Studies have shown that these approaches have their inherent advantages and limitations. This work proposes a semantic label fusion algorithm by combining two representative state-of-the-art segmentation algorithms: texture based hand-crafted, and deep learning based methods to obtain robust tumor segmentation. We evaluate the proposed method using publicly available BRATS 2017 brain tumor segmentation challenge dataset. The results show that the proposed method offers improved segmentation by alleviating inherent weaknesses: extensive false positives in texture based method, and the false tumor tissue classification problem in deep learning method, respectively. Furthermore, we investigate the effect of patient's gender on the segmentation performance using a subset of validation dataset. Note the substantial improvement in brain tumor segmentation performance proposed in this work has recently enabled us to secure the first place by our group in overall patient survival prediction task at the BRATS 2017 challenge.

Deep Learning and Texture-Based Semantic Label Fusion for Brain Tumor Segmentation.

PubMed

Vidyaratne, L; Alam, M; Shboul, Z; Iftekharuddin, K M

2018-01-01

Brain tumor segmentation is a fundamental step in surgical treatment and therapy. Many hand-crafted and learning based methods have been proposed for automatic brain tumor segmentation from MRI. Studies have shown that these approaches have their inherent advantages and limitations. This work proposes a semantic label fusion algorithm by combining two representative state-of-the-art segmentation algorithms: texture based hand-crafted, and deep learning based methods to obtain robust tumor segmentation. We evaluate the proposed method using publicly available BRATS 2017 brain tumor segmentation challenge dataset. The results show that the proposed method offers improved segmentation by alleviating inherent weaknesses: extensive false positives in texture based method, and the false tumor tissue classification problem in deep learning method, respectively. Furthermore, we investigate the effect of patient's gender on the segmentation performance using a subset of validation dataset. Note the substantial improvement in brain tumor segmentation performance proposed in this work has recently enabled us to secure the first place by our group in overall patient survival prediction task at the BRATS 2017 challenge.

Identification and classification of similar looking food grains

NASA Astrophysics Data System (ADS)

Anami, B. S.; Biradar, Sunanda D.; Savakar, D. G.; Kulkarni, P. V.

2013-01-01

This paper describes the comparative study of Artificial Neural Network (ANN) and Support Vector Machine (SVM) classifiers by taking a case study of identification and classification of four pairs of similar looking food grains namely, Finger Millet, Mustard, Soyabean, Pigeon Pea, Aniseed, Cumin-seeds, Split Greengram and Split Blackgram. Algorithms are developed to acquire and process color images of these grains samples. The developed algorithms are used to extract 18 colors-Hue Saturation Value (HSV), and 42 wavelet based texture features. Back Propagation Neural Network (BPNN)-based classifier is designed using three feature sets namely color - HSV, wavelet-texture and their combined model. SVM model for color- HSV model is designed for the same set of samples. The classification accuracies ranging from 93% to 96% for color-HSV, ranging from 78% to 94% for wavelet texture model and from 92% to 97% for combined model are obtained for ANN based models. The classification accuracy ranging from 80% to 90% is obtained for color-HSV based SVM model. Training time required for the SVM based model is substantially lesser than ANN for the same set of images.

Study of texture stitching in 3D modeling of lidar point cloud based on per-pixel linear interpolation along loop line buffer

NASA Astrophysics Data System (ADS)

Xu, Jianxin; Liang, Hong

2013-07-01

Terrestrial laser scanning creates a point cloud composed of thousands or millions of 3D points. Through pre-processing, generating TINs, mapping texture, a 3D model of a real object is obtained. When the object is too large, the object is separated into some parts. This paper mainly focuses on problem of gray uneven of two adjacent textures' intersection. The new algorithm is presented in the paper, which is per-pixel linear interpolation along loop line buffer .The experiment data derives from point cloud of stone lion which is situated in front of west gate of Henan Polytechnic University. The model flow is composed of three parts. First, the large object is separated into two parts, and then each part is modeled, finally the whole 3D model of the stone lion is composed of two part models. When the two part models are combined, there is an obvious fissure line in the overlapping section of two adjacent textures for the two models. Some researchers decrease brightness value of all pixels for two adjacent textures by some algorithms. However, some algorithms are effect and the fissure line still exists. Gray uneven of two adjacent textures is dealt by the algorithm in the paper. The fissure line in overlapping section textures is eliminated. The gray transition in overlapping section become more smoothly.

Correlation between sensory and instrumental measurements of standard and crisp-texture southern highbush blueberries (Vaccinium corymbosum L. interspecific hybrids).

PubMed

Blaker, Kendra M; Plotto, Anne; Baldwin, Elizabeth A; Olmstead, James W

2014-10-01

Fruit texture is a primary selection trait in southern highbush blueberry (SHB) breeding to increase fresh fruit postharvest quality and consumer acceptance. A novel crisp fruit texture has recently been identified among SHB germplasm. In this study, we developed a common set of descriptors that align sensory evaluation of blueberry fruit texture with instrumental measures that could be used for quantitative measurements during pre- and postharvest evaluation. Sensory and instrumental characteristics were measured in 36 and 49 genotypes in 2010 and 2011, respectively. A trained sensory panel evaluated fresh fruit based on five common textural attributes in 2010 and 2011: bursting energy, flesh firmness, skin toughness, juiciness and mealiness. Instrumental measures of compression and bioyield forces were significantly different among cultivars and correlated with sensory scores for bursting energy, flesh firmness and skin toughness (R > 0.7, except skin toughness in 2011), but correlations with sensory scores for juiciness and mealiness were low (R < 0.4). The results of sensory and instrumental measures supported the use of both compression and bioyield force measures in distinguishing crisp from standard-texture genotypes, and suggest that crisp texture in SHB is related to the sensory perception of bursting energy, flesh firmness and skin toughness. © 2014 The Authors. Journal of the Science of Food and Agriculture published by JohnWiley & Sons Ltd on behalf of Society of Chemical Industry.

Temporal and spatial evolution characteristics of gas-liquid two-phase flow pattern based on image texture spectrum descriptor

NASA Astrophysics Data System (ADS)

Zhou, Xi-Guo; Jin, Ning-De; Wang, Zhen-Ya; Zhang, Wen-Yin

2009-11-01

The dynamic image information of typical gas-liquid two-phase flow patterns in vertical upward pipe is captured by a highspeed dynamic camera. The texture spectrum descriptor is used to describe the texture characteristics of the processed images whose content is represented in the form of texture spectrum histogram, and four time-varying characteristic parameter indexes which represent image texture structure of different flow patterns are extracted. The study results show that the amplitude fluctuation of texture characteristic parameter indexes of bubble flow is lowest and shows very random complex dynamic behavior; the amplitude fluctuation of slug flow is higher and shows intermittent motion behavior between gas slug and liquid slug, and the amplitude fluctuation of churn flow is the highest and shows better periodicity; the amplitude fluctuation of bubble-slug flow is from low to high and oscillating frequence is higher than that of slug flow, and includes the features of both slug flow and bubble flow; the slug-churn flow loses the periodicity of slug flow and churn flow, and the amplitude fluctuation is high. The results indicate that the image texture characteristic parameter indexes of different flow pattern can reflect the flow characteristics of gas-liquid two-phase flow, which provides a new approach to understand the temporal and spatial evolution of flow pattern dynamics.

Plasmodium species differentiation by non-expert on-line volunteers for remote malaria field diagnosis.

PubMed

Ortiz-Ruiz, Alejandra; Postigo, María; Gil-Casanova, Sara; Cuadrado, Daniel; Bautista, José M; Rubio, José Miguel; Luengo-Oroz, Miguel; Linares, María

2018-01-30

Routine field diagnosis of malaria is a considerable challenge in rural and low resources endemic areas mainly due to lack of personnel, training and sample processing capacity. In addition, differential diagnosis of Plasmodium species has a high level of misdiagnosis. Real time remote microscopical diagnosis through on-line crowdsourcing platforms could be converted into an agile network to support diagnosis-based treatment and malaria control in low resources areas. This study explores whether accurate Plasmodium species identification-a critical step during the diagnosis protocol in order to choose the appropriate medication-is possible through the information provided by non-trained on-line volunteers. 88 volunteers have performed a series of questionnaires over 110 images to differentiate species (Plasmodium falciparum, Plasmodium ovale, Plasmodium vivax, Plasmodium malariae, Plasmodium knowlesi) and parasite staging from thin blood smear images digitalized with a smartphone camera adapted to the ocular of a conventional light microscope. Visual cues evaluated in the surveys include texture and colour, parasite shape and red blood size. On-line volunteers are able to discriminate Plasmodium species (P. falciparum, P. malariae, P. vivax, P. ovale, P. knowlesi) and stages in thin-blood smears according to visual cues observed on digitalized images of parasitized red blood cells. Friendly textual descriptions of the visual cues and specialized malaria terminology is key for volunteers learning and efficiency. On-line volunteers with short-training are able to differentiate malaria parasite species and parasite stages from digitalized thin smears based on simple visual cues (shape, size, texture and colour). While the accuracy of a single on-line expert is far from perfect, a single parasite classification obtained by combining the opinions of multiple on-line volunteers over the same smear, could improve accuracy and reliability of Plasmodium species identification in remote malaria diagnosis.

A texture-component Avrami model for predicting recrystallization textures, kinetics and grain size

NASA Astrophysics Data System (ADS)

Raabe, Dierk

2007-03-01

The study presents an analytical model for predicting crystallographic textures and the final grain size during primary static recrystallization of metals using texture components. The kinetics is formulated as a matrix variant of the Johnson-Mehl-Avrami-Kolmogorov equation. The matrix form is required since the kinetic and crystallographic evolution of the microstructure is described in terms of a limited set of growing (recrystallizing) and swept (deformed) texture components. The number of components required (5-10) defines the order of the matrix since the kinetic coupling occurs between all recrystallizing and all deformed components. Each such couple is characterized by corresponding values for the nucleation energy and grain boundary mobility. The values of these parameters can be obtained by analytical or numerical coarse graining according to a renormalization scheme which replaces many individual grains which grow via recrystallization in a deformed texture component by a single equivalent recrystallization texture component or by fitting to experimental data. Each deformed component is further characterized by an average stored deformation energy. Each element of the kinetic matrix, reflecting one of the possible couplings between a deformed and a recrystallizing texture component, is then derived in each time step by a set of two differential equations. The first equation describes the thermally activated nucleation and growth processes for the expanded (free) volume for a particular couple of a deformed and a recrystallizing texture component and the second equation is used for calculating the constrained (real) volume for that couple which corrects the free volume for those portions of the deformation component which were already swept. The new method is particularly developed for the fast and physically based process simulation of recrystallization textures with respect to processing. The present paper introduces the method and applies it to the primary recrystallization of low carbon steels.

Nanoscale silver-assisted wet etching of crystalline silicon for anti-reflection surface textures.

PubMed

Li, Rui; Wang, Shuling; Chuwongin, Santhad; Zhou, Weidong

2013-01-01

We report here an electro-less metal-assisted chemical etching (MacEtch) process as light management surface-texturing technique for single crystalline Si photovoltaics. Random Silver nanostructures were formed on top of the Si surface based on the thin film evaporation and annealing process. Significant reflection reduction was obtained from the fabricated Si sample, with approximately 2% reflection over a wide spectra range (300 to 1050 nm). The work demonstrates the potential of MacEtch process for anti-reflection surface texture fabrication of large area, high efficiency, and low cost thin film solar cell.

The Influence of Texture Symmetry in Marker Pointing:. Experimenting with Humans and Algorithms

NASA Astrophysics Data System (ADS)

Cardaci, M.; Tabacchi, M. E.

2012-12-01

Symmetry plays a fundamental role in aiding the visual system, to organize its environmental stimuli and to detect visual patterns of natural and artificial objects. Various kinds of symmetry exist, and we will discuss how internal symmetry due to textures influences the choice of direction in visual tasks. Two experiments are presented: the first, with human subjects, deals with the effect of textures on preferences for a pointing direction. The second emulates the performances obtained in the first through the use of an algorithm based on a physic metaphor. Results from both experiments are shown and comment.

Early detection of chemotherapy-refractory patients by monitoring textural alterations in diffuse optical spectroscopic images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sadeghi-Naini, Ali; Falou, Omar; Czarnota, Gregory J., E-mail: Gregory.Czarnota@sunnybrook.ca

2015-11-15

Purpose: Changes in textural characteristics of diffuse optical spectroscopic (DOS) functional images, accompanied by alterations in their mean values, are demonstrated here for the first time as early surrogates of ultimate treatment response in locally advanced breast cancer (LABC) patients receiving neoadjuvant chemotherapy (NAC). NAC, as a standard component of treatment for LABC patient, induces measurable heterogeneous changes in tumor metabolism which were evaluated using DOS-based metabolic maps. This study characterizes such inhomogeneous nature of response development, by determining alterations in textural properties of DOS images apparent at early stages of therapy, followed later by gross changes in mean valuesmore » of these functional metabolic maps. Methods: Twelve LABC patients undergoing NAC were scanned before and at four times after treatment initiation, and tomographic DOS images were reconstructed at each time. Ultimate responses of patients were determined clinically and pathologically, based on a reduction in tumor size and assessment of residual tumor cellularity. The mean-value parameters and textural features were extracted from volumetric DOS images for several functional and metabolic parameters prior to the treatment initiation. Changes in these DOS-based biomarkers were also monitored over the course of treatment. The measured biomarkers were applied to differentiate patient responses noninvasively and compared to clinical and pathologic responses. Results: Responding and nonresponding patients demonstrated different changes in DOS-based textural and mean-value parameters during chemotherapy. Whereas none of the biomarkers measured prior the start of therapy demonstrated a significant difference between the two patient populations, statistically significant differences were observed at week one after treatment initiation using the relative change in contrast/homogeneity of seven functional maps (0.001 < p < 0.049), and mean value of water content in tissue (p = 0.010). The cross-validated sensitivity and specificity of these parameters at week one of therapy ranged between 80%–100% and 67%–100%, respectively. Higher levels of statistically significant differences were exhibited at week four after start of treatment, with cross-validated sensitivities and specificities ranging between 80% and 100% for three textural and three mean-value parameters. The combination of the textural and mean-value parameters in a “hybrid” profile could better separate the two patient populations early on during a course of treatment, with cross-validated sensitivities and specificities of up to 100% (p = 0.001). Conclusions: The results of this study suggest that alterations in textural characteristics of DOS images, in conjunction with changes in their mean values, can classify noninvasively the ultimate clinical and pathologic response of LABC patients to chemotherapy, as early as one week after start of their treatment. This provides a basis for using DOS imaging as a tool for therapy personalization.« less

Early detection of chemotherapy-refractory patients by monitoring textural alterations in diffuse optical spectroscopic images.

PubMed

Sadeghi-Naini, Ali; Vorauer, Eric; Chin, Lee; Falou, Omar; Tran, William T; Wright, Frances C; Gandhi, Sonal; Yaffe, Martin J; Czarnota, Gregory J

2015-11-01

Changes in textural characteristics of diffuse optical spectroscopic (DOS) functional images, accompanied by alterations in their mean values, are demonstrated here for the first time as early surrogates of ultimate treatment response in locally advanced breast cancer (LABC) patients receiving neoadjuvant chemotherapy (NAC). NAC, as a standard component of treatment for LABC patient, induces measurable heterogeneous changes in tumor metabolism which were evaluated using DOS-based metabolic maps. This study characterizes such inhomogeneous nature of response development, by determining alterations in textural properties of DOS images apparent at early stages of therapy, followed later by gross changes in mean values of these functional metabolic maps. Twelve LABC patients undergoing NAC were scanned before and at four times after treatment initiation, and tomographic DOS images were reconstructed at each time. Ultimate responses of patients were determined clinically and pathologically, based on a reduction in tumor size and assessment of residual tumor cellularity. The mean-value parameters and textural features were extracted from volumetric DOS images for several functional and metabolic parameters prior to the treatment initiation. Changes in these DOS-based biomarkers were also monitored over the course of treatment. The measured biomarkers were applied to differentiate patient responses noninvasively and compared to clinical and pathologic responses. Responding and nonresponding patients demonstrated different changes in DOS-based textural and mean-value parameters during chemotherapy. Whereas none of the biomarkers measured prior the start of therapy demonstrated a significant difference between the two patient populations, statistically significant differences were observed at week one after treatment initiation using the relative change in contrast/homogeneity of seven functional maps (0.001

The Sines industrial complex monitoring programme: A preliminary report.

PubMed

Jones, M P; Catarino, F M; Sérgio, C; Bento-Pereira, F

1981-06-01

It is anticipated that the establishment of the industrial complex at Sines, Alentejo, Portugal, will have some impact on the environment. Details of the methods used in the monitoring programme are provided. Records of the epiphytic lichen vegetation in permanent quadrats have been made and changes shown in selected sites over a three year period are discussed. Material has been collected for analysis for heavy metals and the results discussed. There is considerable variation in replicates and in interspecies values. The problem of age and bio-accumulation is mentioned. Scanning electron microscopy has shown the accumulation of particulates, as yet unidentified, the quantity varying with increase in age and surface texture. A broadly based study of the local epiphytic flora is being carried out to record the present day diversity. There appears, as yet, to be no detectable influence of the industrial complex on the epiphytic flora of the permanent quadrats.

Anti-biofouling superhydrophobic surface fabricated by picosecond laser texturing of stainless steel

NASA Astrophysics Data System (ADS)

Sun, Ke; Yang, Huan; Xue, Wei; He, An; Zhu, Dehua; Liu, Wenwen; Adeyemi, Kenneth; Cao, Yu

2018-04-01

Anti-biofouling technology is based on specifically designed materials and coatings. This is an enduring goal in the maritime industries, such as shipping, offshore oil exploration, and aquaculture. Recently, research of the relationship between wettability and antifouling effectiveness has attracted considerable attention, due to the anti-biofouling properties of the lotus leaf and shark skin. In this study, super-hydrophobic surfaces (SHSs) with controllable periodic structures were fabricated on AISI304 stainless steel by a picosecond laser, and their anti-biofouling performance were investigated by seawater immersion for five weeks in summertime. The results showed that the specimens with SHS demonstrate significant anti-biofouling effect as compared with the bare stainless steel plate. We observed that nearly 50% decrease of the average microbe attachment area ratio (Avg. MAAR) could be obtained. The micro-groove SHS with more abundant hierarchical micro-nano structures showed better anti-biofouling performance than the micro-pit SHS.

Theory of high-resolution tunneling spin transport on a magnetic skyrmion

NASA Astrophysics Data System (ADS)

Palotás, Krisztián; Rózsa, Levente; Szunyogh, László

2018-05-01

Tunneling spin transport characteristics of a magnetic skyrmion are described theoretically in magnetic scanning tunneling microscopy (STM). The spin-polarized charge current in STM (SP-STM) and tunneling spin transport vector quantities, the longitudinal spin current and the spin transfer torque, are calculated in high spatial resolution within the same theoretical framework. A connection between the conventional charge current SP-STM image contrasts and the magnitudes of the spin transport vectors is demonstrated that enables the estimation of tunneling spin transport properties based on experimentally measured SP-STM images. A considerable tunability of the spin transport vectors by the involved spin polarizations is also highlighted. These possibilities and the combined theory of tunneling charge and vector spin transport pave the way for gaining deep insight into electric-current-induced tunneling spin transport properties in SP-STM and to the related dynamics of complex magnetic textures at surfaces.

Textural, nutritional and functional attributes in tomato genotypes for breeding better quality varieties.

PubMed

Saha, Supradip; Hedau, Nirmal K; Mahajan, Vinay; Singh, Gyanendra; Gupta, Hari S; Gahalain, Anita

2010-01-30

Screening of natural biodiversity for their better quality attributes is of prime importance for quality breeding programmes. A set of 53 tomato genotypes was measured for their textural [skin firmness, pericarp thickness, total soluble solids (TSS)], nutritional [phosphorus (P), potassium (K), iron (Fe), zinc (Zn), copper (Cu), manganese (Mn) and titrable acidity (TA)] and functional (beta-carotene, lycopene and ascorbic acid) quality attributes. Three sets of data (textural, nutritional and functional attributes) were obtained and analysed for their mutual relationships. Wide variations were observed in most of the measurements, e.g. skin firmness (coefficient of variability (CV) 269-612 g), pericarp thickness (CV 1.4-4.9 mm), potassium (CV 229-371 mg 100 g(-1)), iron (CV 611-1772 mg 100 g(-1)), ascorbic acid (CV 12-86 mg 100 g(-1)), suggesting that there are considerable levels of genetic diversity. Significant correlations (P < 0.05, 0.01) were also detected among different attributes of tomato genotypes, such as phosphorus and zinc with a correlation coefficient of 0.74, ascorbic acid and copper of 0.57, pericarp thickness and lycopene of - 0.52. However, there were no correlations between textural and nutritional attributes. Five factors were computed by principal component analysis that explained 66% of the variation in the attributes, among which all micronutrients other than iron, TSS, firmness and beta-carotene were most important. Functional attributes except beta-carotene played a less important role in explaining total variation. This knowledge could aid in the efficient conservation of important parts of the agricultural biodiversity of India. These results are also potentially useful for tomato breeders working on the development of new varieties. (c) 2009 Society of Chemical Industry.

Computation of reliable textural indices from multimodal brain MRI: suggestions based on a study of patients with diffuse intrinsic pontine glioma

NASA Astrophysics Data System (ADS)

Goya-Outi, Jessica; Orlhac, Fanny; Calmon, Raphael; Alentorn, Agusti; Nioche, Christophe; Philippe, Cathy; Puget, Stéphanie; Boddaert, Nathalie; Buvat, Irène; Grill, Jacques; Frouin, Vincent; Frouin, Frederique

2018-05-01

Few methodological studies regarding widely used textural indices robustness in MRI have been reported. In this context, this study aims to propose some rules to compute reliable textural indices from multimodal 3D brain MRI. Diagnosis and post-biopsy MR scans including T1, post-contrast T1, T2 and FLAIR images from thirty children with diffuse intrinsic pontine glioma (DIPG) were considered. The hybrid white stripe method was adapted to standardize MR intensities. Sixty textural indices were then computed for each modality in different regions of interest (ROI), including tumor and white matter (WM). Three types of intensity binning were compared : constant bin width and relative bounds; constant number of bins and relative bounds; constant number of bins and absolute bounds. The impact of the volume of the region was also tested within the WM. First, the mean Hellinger distance between patient-based intensity distributions decreased by a factor greater than 10 in WM and greater than 2.5 in gray matter after standardization. Regarding the binning strategy, the ranking of patients was highly correlated for 188/240 features when comparing with , but for only 20 when comparing with , and nine when comparing with . Furthermore, when using or texture indices reflected tumor heterogeneity as assessed visually by experts. Last, 41 features presented statistically significant differences between contralateral WM regions when ROI size slightly varies across patients, and none when using ROI of the same size. For regions with similar size, 224 features were significantly different between WM and tumor. Valuable information from texture indices can be biased by methodological choices. Recommendations are to standardize intensities in MR brain volumes, to use intensity binning with constant bin width, and to define regions with the same volumes to get reliable textural indices.

Artificial and natural radionuclides in soils of the southern and middle taiga zones of Komi Republic

NASA Astrophysics Data System (ADS)

Beznosikov, V. A.; Lodygin, E. D.; Shuktomova, I. I.

2017-07-01

Specific activities of artificial (137Cs, 90Sr) and natural (40K, 232Th, 226Ra) radionuclides in background soils of southern and middle taiga of Komi Republic have been estimated with consideration for the landscape-geochemical features of the territory. It has been shown that their accumulation and migration in soils are determined by the following factors: position in relief, texture, and organic matter content. No anomalous zones with increased contents of radionuclides in soils have been revealed.

Ada style guide (version 1.1)

NASA Technical Reports Server (NTRS)

Seidewitz, Edwin V.; Agresti, William; Ferry, Daniel; Lavallee, David; Maresca, Paul; Nelson, Robert; Quimby, Kelvin; Rosenberg, Jacob; Roy, Daniel; Shell, Allyn

1987-01-01

Ada is a programming language of considerable expressive power. The Ada Language Reference Manual provides a thorough definition of the language. However, it does not offer sufficient guidance on the appropriate use of Ada's powerful features. For this reason, the Goddard Space Flight Center Ada User's Group has produced this style guide which addresses such program style issues. The guide covers three areas of Ada program style: the structural decomposition of a program; the coding and the use of specific Ada features; and the textural formatting of a program.

Design and Evaluation of an Energy-Dense, Light-Weight Combat Ration to Sustain Land Forces Involved in High-Intensity, Short-Duration Operations

DTIC Science & Technology

2015-03-01

8260 kJ provided, and was less than the target of at least 90% consumption . The effect of this on cognitive and physical performance is unknown and...texture and flavour. Packaging, serve size, palatability in different environments, effects on morale, ease of consumption , preparation considerations...acids (found in fatty fish ), which may have several beneficial effects on military health and fitness (Lewis et al, 2011; Lewis & Bailes, 2011

Relationships between surface free energy, surface texture parameters and controlled drug release in hydrophilic matrices.

PubMed

Saurí, J; Suñé-Negre, J M; Díaz-Marcos, J; Vilana, J; Millán, D; Ticó, J R; Miñarro, M; Pérez-Lozano, P; García-Montoya, E

2015-01-15

The study of controlled release and drug release devices has been dominated by considerations of the bulk or average properties of material or devices. Yet the outermost surface atoms play a central role in their performance. The objective of this article has been to characterize the surface of hydrophilic matrix tablets using the contact angle (CA) method to ascertain the surface free energy, and atomic force microscopy (AFM) and confocal microscopy (CM) for the physical characterization of the surface of the hydrophilic matrix. The surface free energy results obtained show that hydroxypropylmethylcellulose K15M hinders the spreading of water on the surface of the tablet, such that the concentration of HPMC K15M increases the reaction rate of the hydrophobic interactions between the chains of HPMC K15M which increases with respect to the rate of penetration of water into the tablet. In this study, we developed a new method to characterize the swelling of the tablets and established a relationship between the new method based on microswelling and the swelling ratio parameter. The surface texture parameters have been determined and the morphology of the tablets of the different formulations and the evolution of the surface morphology after interacting with the water, swelling and forming a gel layer were characterized. This work represents significant progress in the characterization of matrix tablets. Copyright © 2014 Elsevier B.V. All rights reserved.

Diagenetic effects of compaction on reservoir properties: The case of early callovian ``Dalle Nacrée'' formation (Paris basin, France)

NASA Astrophysics Data System (ADS)

Nader, Fadi H.; Champenois, France; Barbier, Mickaël; Adelinet, Mathilde; Rosenberg, Elisabeth; Houel, Pascal; Delmas, Jocelyne; Swennen, Rudy

2016-11-01

The impact of compaction diagenesis on reservoir properties is addressed by means of observations made on five boreholes with different burial histories of the Early Callovian ;Dalle Nacrée; Formation in the Paris Basin. Petrographic analyses were carried out in order to investigate the rock-texture, pore space type and volume, micro-fabrics, and cement phases. Based on the acquired data, a chronologically ordered sequence of diagenetic events (paragenesis) for each borehole was reconstructed taking the burial history into account. Point counting and a segmentation algorithm (Matlab) were used to quantify porosity, as well as the amounts of grain constituents and cement phases on scanned images of studied thin sections. In addition, four key samples were analyzed by 3D imaging using microfocus X-ray computer tomography. Basin margin grainstones display a different burial diagenesis when compared to basin centre grainstones and wackestones. The former have been affected by considerable cementation (especially by blocky calcite) prior to effective burial, in contrast to the basin centre lithologies where burial and compaction prevailed with relatively less cementation. Fracturing and bed-parallel stylolitization, observed especially in basinal wackestone facies also invoke higher levels of mechanical and chemical compaction than observed in basin marginal equivalents. Compaction fluids may have migrated at the time of burial from the basin centre towards its margins, affecting hence the reservoir properties of similar rock textures and facies and resulting in cross-basin spatial diagenetic heterogeneities.

Flow Charts: Visualization of Vector Fields on Arbitrary Surfaces

PubMed Central

Li, Guo-Shi; Tricoche, Xavier; Weiskopf, Daniel; Hansen, Charles

2009-01-01

We introduce a novel flow visualization method called Flow Charts, which uses a texture atlas approach for the visualization of flows defined over curved surfaces. In this scheme, the surface and its associated flow are segmented into overlapping patches, which are then parameterized and packed in the texture domain. This scheme allows accurate particle advection across multiple charts in the texture domain, providing a flexible framework that supports various flow visualization techniques. The use of surface parameterization enables flow visualization techniques requiring the global view of the surface over long time spans, such as Unsteady Flow LIC (UFLIC), particle-based Unsteady Flow Advection Convolution (UFAC), or dye advection. It also prevents visual artifacts normally associated with view-dependent methods. Represented as textures, Flow Charts can be naturally integrated into hardware accelerated flow visualization techniques for interactive performance. PMID:18599918

Fusion method of SAR and optical images for urban object extraction

NASA Astrophysics Data System (ADS)

Jia, Yonghong; Blum, Rick S.; Li, Fangfang

2007-11-01

A new image fusion method of SAR, Panchromatic (Pan) and multispectral (MS) data is proposed. First of all, SAR texture is extracted by ratioing the despeckled SAR image to its low pass approximation, and is used to modulate high pass details extracted from the available Pan image by means of the á trous wavelet decomposition. Then, high pass details modulated with the texture is applied to obtain the fusion product by HPFM (High pass Filter-based Modulation) fusion method. A set of image data including co-registered Landsat TM, ENVISAT SAR and SPOT Pan is used for the experiment. The results demonstrate accurate spectral preservation on vegetated regions, bare soil, and also on textured areas (buildings and road network) where SAR texture information enhances the fusion product, and the proposed approach is effective for image interpret and classification.

The Science of Soil Textures

ERIC Educational Resources Information Center

Bigham, Gary

2010-01-01

Off-road motorcycle racing and ATV riding. Gardening and fishing. What do these high-adrenaline and slower-paced pastimes have in common? Each requires soil, and the texture of that soil has an effect on all of them. In the inquiry-based lessons described here, students work both in the field or laboratory and in the classroom to collect soil…

Texture-based approach to palmprint retrieval for personal identification

NASA Astrophysics Data System (ADS)

Li, Wenxin; Zhang, David; Xu, Z.; You, J.

2000-12-01

This paper presents a new approach to palmprint retrieval for personal identification. Three key issues in image retrieval are considered - feature selection, similarity measures and dynamic search for the best matching of the sample in the image database. We propose a texture-based method for palmprint feature representation. The concept of texture energy is introduced to define a palm print's global and local features, which are characterized with high convergence of inner-palm similarities and good dispersion of inter-palm discrimination. The search is carried out in a layered fashion: first global features are used to guide the fast selection of a small set of similar candidates from the database from the database and then local features are used to decide the final output within the candidate set. The experimental results demonstrate the effectiveness and accuracy of the proposed method.

Texture-based approach to palmprint retrieval for personal identification

NASA Astrophysics Data System (ADS)

Li, Wenxin; Zhang, David; Xu, Z.; You, J.

2001-01-01

This paper presents a new approach to palmprint retrieval for personal identification. Three key issues in image retrieval are considered - feature selection, similarity measures and dynamic search for the best matching of the sample in the image database. We propose a texture-based method for palmprint feature representation. The concept of texture energy is introduced to define a palm print's global and local features, which are characterized with high convergence of inner-palm similarities and good dispersion of inter-palm discrimination. The search is carried out in a layered fashion: first global features are used to guide the fast selection of a small set of similar candidates from the database from the database and then local features are used to decide the final output within the candidate set. The experimental results demonstrate the effectiveness and accuracy of the proposed method.

Spin Seebeck effect and thermoelectric phenomena in superconducting hybrids with magnetic textures or spin-orbit coupling

PubMed Central

Bathen, Marianne Etzelmüller; Linder, Jacob

2017-01-01

We theoretically consider the spin Seebeck effect, the charge Seebeck coefficient, and the thermoelectric figure of merit in superconducting hybrid structures including either magnetic textures or intrinsic spin-orbit coupling. We demonstrate that large magnitudes for all these quantities are obtainable in Josephson-based systems with either zero or a small externally applied magnetic field. This provides an alternative to the thermoelectric effects generated in high-field (~1 T) superconducting hybrid systems, which were recently experimentally demonstrated. The systems studied contain either conical ferromagnets, spin-active interfaces, or spin-orbit coupling. We present a framework for calculating the linear thermoelectric response for both spin and charge of a system upon applying temperature and voltage gradients based on quasiclassical theory which allows for arbitrary spin-dependent textures and fields to be conveniently incorporated. PMID:28139667

A challenging hysteresis operator for the simulation of Goss-textured magnetic materials

NASA Astrophysics Data System (ADS)

Cardelli, Ermanno; Faba, Antonio; Laudani, Antonino; Pompei, Michele; Quondam Antonio, Simone; Fulginei, Francesco Riganti; Salvini, Alessandro

2017-06-01

A new hysteresis operator for the simulation of Goss-textured ferromagnets is here defined. The operator is derived from the classic Stoner-Wohlfarth model, where the anisotropy energy is assumed to be cubic instead of uniaxial, in order to reproduce the magnetic behavior of Goss textured ferromagnetic materials, such as grain-oriented Fe-Si alloys, Ni-Fe alloys, and Ni-Co alloys. A vector hysteresis model based on a single hysteresis operator is then implemented and used for the prediction of the rotational magnetizations that have been measured in a sample of grain-oriented electrical steel. This is especially promising for FEM based calculations, where the magnetization state in each point must be recalculated at each time step. Finally, the computed loops, as well as the magnetic losses, are compared to the measured data.

(100)-Textured KNN-based thick film with enhanced piezoelectric property for intravascular ultrasound imaging

PubMed Central

Zhu, Benpeng; Zhang, Zhiqiang; Ma, Teng; Yang, Xiaofei; Li, Yongxiang; Shung, K. Kirk; Zhou, Qifa

2015-01-01

Using tape-casting technology, 35 μm free-standing (100)-textured Li doped KNN (KNLN) thick film was prepared by employing NaNbO3 (NN) as template. It exhibited similar piezoelectric behavior to lead containing materials: a longitudinal piezoelectric coefficient (d33) of ∼150 pm/V and an electromechanical coupling coefficient (kt) of 0.44. Based on this thick film, a 52 MHz side-looking miniature transducer with a bandwidth of 61.5% at −6 dB was built for Intravascular ultrasound (IVUS) imaging. In comparison with 40 MHz PMN-PT single crystal transducer, the rabbit aorta image had better resolution and higher noise-to-signal ratio, indicating that lead-free (100)-textured KNLN thick film may be suitable for IVUS (>50 MHz) imaging. PMID:25991874

Aircraft Detection in High-Resolution SAR Images Based on a Gradient Textural Saliency Map

PubMed Central

Tan, Yihua; Li, Qingyun; Li, Yansheng; Tian, Jinwen

2015-01-01

This paper proposes a new automatic and adaptive aircraft target detection algorithm in high-resolution synthetic aperture radar (SAR) images of airport. The proposed method is based on gradient textural saliency map under the contextual cues of apron area. Firstly, the candidate regions with the possible existence of airport are detected from the apron area. Secondly, directional local gradient distribution detector is used to obtain a gradient textural saliency map in the favor of the candidate regions. In addition, the final targets will be detected by segmenting the saliency map using CFAR-type algorithm. The real high-resolution airborne SAR image data is used to verify the proposed algorithm. The results demonstrate that this algorithm can detect aircraft targets quickly and accurately, and decrease the false alarm rate. PMID:26378543

Spin Seebeck effect and thermoelectric phenomena in superconducting hybrids with magnetic textures or spin-orbit coupling.

PubMed

Bathen, Marianne Etzelmüller; Linder, Jacob

2017-01-31

We theoretically consider the spin Seebeck effect, the charge Seebeck coefficient, and the thermoelectric figure of merit in superconducting hybrid structures including either magnetic textures or intrinsic spin-orbit coupling. We demonstrate that large magnitudes for all these quantities are obtainable in Josephson-based systems with either zero or a small externally applied magnetic field. This provides an alternative to the thermoelectric effects generated in high-field (~1 T) superconducting hybrid systems, which were recently experimentally demonstrated. The systems studied contain either conical ferromagnets, spin-active interfaces, or spin-orbit coupling. We present a framework for calculating the linear thermoelectric response for both spin and charge of a system upon applying temperature and voltage gradients based on quasiclassical theory which allows for arbitrary spin-dependent textures and fields to be conveniently incorporated.

Collagen morphology and texture analysis: from statistics to classification

PubMed Central

Mostaço-Guidolin, Leila B.; Ko, Alex C.-T.; Wang, Fei; Xiang, Bo; Hewko, Mark; Tian, Ganghong; Major, Arkady; Shiomi, Masashi; Sowa, Michael G.

2013-01-01

In this study we present an image analysis methodology capable of quantifying morphological changes in tissue collagen fibril organization caused by pathological conditions. Texture analysis based on first-order statistics (FOS) and second-order statistics such as gray level co-occurrence matrix (GLCM) was explored to extract second-harmonic generation (SHG) image features that are associated with the structural and biochemical changes of tissue collagen networks. Based on these extracted quantitative parameters, multi-group classification of SHG images was performed. With combined FOS and GLCM texture values, we achieved reliable classification of SHG collagen images acquired from atherosclerosis arteries with >90% accuracy, sensitivity and specificity. The proposed methodology can be applied to a wide range of conditions involving collagen re-modeling, such as in skin disorders, different types of fibrosis and muscular-skeletal diseases affecting ligaments and cartilage. PMID:23846580

Uncovering three-dimensional gradients in fibrillar orientation in an impact-resistant biological armour.

PubMed

Zhang, Y; Paris, O; Terrill, N J; Gupta, H S

2016-05-23

The complex hierarchical structure in biological and synthetic fibrous nanocomposites entails considerable difficulties in the interpretation of the crystallographic texture from diffraction data. Here, we present a novel reconstruction method to obtain the 3D distribution of fibres in such systems. An analytical expression is derived for the diffraction intensity from fibres, explaining the azimuthal intensity distribution in terms of the angles of the three dimensional fibre orientation distributions. The telson of stomatopod (mantis shrimp) serves as an example of natural biological armour whose high impact resistance property is believed to arise from the hierarchical organization of alpha chitin nanofibrils into fibres and twisted plywood (Bouligand) structures at the sub-micron and micron scale. Synchrotron microfocus scanning X-ray diffraction data on stomatopod telson were used as a test case to map the 3D fibre orientation across the entire tissue section. The method is applicable to a range of biological and biomimetic structures with graded 3D fibre texture at the sub-micron and micron length scales.

Uncovering three-dimensional gradients in fibrillar orientation in an impact-resistant biological armour

NASA Astrophysics Data System (ADS)

Zhang, Y.; Paris, O.; Terrill, N. J.; Gupta, H. S.

2016-05-01

The complex hierarchical structure in biological and synthetic fibrous nanocomposites entails considerable difficulties in the interpretation of the crystallographic texture from diffraction data. Here, we present a novel reconstruction method to obtain the 3D distribution of fibres in such systems. An analytical expression is derived for the diffraction intensity from fibres, explaining the azimuthal intensity distribution in terms of the angles of the three dimensional fibre orientation distributions. The telson of stomatopod (mantis shrimp) serves as an example of natural biological armour whose high impact resistance property is believed to arise from the hierarchical organization of alpha chitin nanofibrils into fibres and twisted plywood (Bouligand) structures at the sub-micron and micron scale. Synchrotron microfocus scanning X-ray diffraction data on stomatopod telson were used as a test case to map the 3D fibre orientation across the entire tissue section. The method is applicable to a range of biological and biomimetic structures with graded 3D fibre texture at the sub-micron and micron length scales.

22.7% efficient PERL silicon solar cell module with a textured front surface

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, J.; Wang, A.; Campbell, P.

1997-12-31

This paper describes a solar cell module efficiency of 22.7% independently measured at Sandia National Laboratories. This is the highest ever confirmed efficiency for a photovoltaic module of this size achieved by cells made from any material. This 778-cm{sup 2} module used 40 large-area double layer antireflection coated PERL (passivated emitter, rear locally-diffused) silicon cells of average efficiency of 23.1%. A textured front module surface considerably improve the module efficiency. Also reported is an independently confirmed efficiency of 23.7% for a 21.6 cm{sup 2} cell of the type used in the module. Using these PERL cells in the 1996 Worldmore » Solar Challenge solar car race from Darwin to Adelaide across Australia, Honda`s Dream and Aisin Seiki`s Aisol III were placed first and third, respectively. Honda also set a new record by reaching Adelaide in four days with an average speed of 90km/h over the 3010 km course.« less

Uncovering three-dimensional gradients in fibrillar orientation in an impact-resistant biological armour

PubMed Central

Zhang, Y.; Paris, O.; Terrill, N. J.; Gupta, H. S.

2016-01-01

The complex hierarchical structure in biological and synthetic fibrous nanocomposites entails considerable difficulties in the interpretation of the crystallographic texture from diffraction data. Here, we present a novel reconstruction method to obtain the 3D distribution of fibres in such systems. An analytical expression is derived for the diffraction intensity from fibres, explaining the azimuthal intensity distribution in terms of the angles of the three dimensional fibre orientation distributions. The telson of stomatopod (mantis shrimp) serves as an example of natural biological armour whose high impact resistance property is believed to arise from the hierarchical organization of alpha chitin nanofibrils into fibres and twisted plywood (Bouligand) structures at the sub-micron and micron scale. Synchrotron microfocus scanning X-ray diffraction data on stomatopod telson were used as a test case to map the 3D fibre orientation across the entire tissue section. The method is applicable to a range of biological and biomimetic structures with graded 3D fibre texture at the sub-micron and micron length scales. PMID:27211574

Tunisian date (Phoenix dactylifera L.) by-products: Characterization and potential effects on sensory, textural and antioxidant properties of dairy desserts.

PubMed

Jridi, Mourad; Souissi, Nabil; Salem, Marwa Ben; Ayadi, M A; Nasri, Moncef; Azabou, Samia

2015-12-01

Three Tunisian date varieties, Deglet Nour, Kentichi and Allig, served to produce syrups and powders, which were then examined for their physico-chemical composition and antioxidant properties. Different proportions of these sweetening-like agents were incorporated to produce nine different formulations of dairy desserts, with lower amount of added sugars to avoid any artificial flavoring or coloring agents. Sensory and color evaluation data revealed that incorporating Deglet Nour and Kentichi syrup offers the most desirable formulation. Furthermore, syrup polysaccharides and fibers contribute to better maintain the final product texture. In addition, date by-products create a good source of natural thickening agents, involved in enhancing apparent viscosity and spontaneous exudation. Thanks to their high content in phenolic compounds, date by-products considerably improve antioxidant activities of the formulated desserts. Therefore, they could be valued as natural ingredients in the formulation of novel dairy products with high nutritional-properties. Copyright © 2015 Elsevier Ltd. All rights reserved.

Inlining 3d Reconstruction, Multi-Source Texture Mapping and Semantic Analysis Using Oblique Aerial Imagery

NASA Astrophysics Data System (ADS)

Frommholz, D.; Linkiewicz, M.; Poznanska, A. M.

2016-06-01

This paper proposes an in-line method for the simplified reconstruction of city buildings from nadir and oblique aerial images that at the same time are being used for multi-source texture mapping with minimal resampling. Further, the resulting unrectified texture atlases are analyzed for façade elements like windows to be reintegrated into the original 3D models. Tests on real-world data of Heligoland/ Germany comprising more than 800 buildings exposed a median positional deviation of 0.31 m at the façades compared to the cadastral map, a correctness of 67% for the detected windows and good visual quality when being rendered with GPU-based perspective correction. As part of the process building reconstruction takes the oriented input images and transforms them into dense point clouds by semi-global matching (SGM). The point sets undergo local RANSAC-based regression and topology analysis to detect adjacent planar surfaces and determine their semantics. Based on this information the roof, wall and ground surfaces found get intersected and limited in their extension to form a closed 3D building hull. For texture mapping the hull polygons are projected into each possible input bitmap to find suitable color sources regarding the coverage and resolution. Occlusions are detected by ray-casting a full-scale digital surface model (DSM) of the scene and stored in pixel-precise visibility maps. These maps are used to derive overlap statistics and radiometric adjustment coefficients to be applied when the visible image parts for each building polygon are being copied into a compact texture atlas without resampling whenever possible. The atlas bitmap is passed to a commercial object-based image analysis (OBIA) tool running a custom rule set to identify windows on the contained façade patches. Following multi-resolution segmentation and classification based on brightness and contrast differences potential window objects are evaluated against geometric constraints and conditionally grown, fused and filtered morphologically. The output polygons are vectorized and reintegrated into the previously reconstructed buildings by sparsely ray-tracing their vertices. Finally the enhanced 3D models get stored as textured geometry for visualization and semantically annotated "LOD-2.5" CityGML objects for GIS applications.

Investigation of quartz grain surface textures by atomic force microscopy for forensic analysis.

PubMed

Konopinski, D I; Hudziak, S; Morgan, R M; Bull, P A; Kenyon, A J

2012-11-30

This paper presents a study of quartz sand grain surface textures using atomic force microscopy (AFM) to image the surface. Until now scanning electron microscopy (SEM) has provided the primary technique used in the forensic surface texture analysis of quartz sand grains as a means of establishing the provenance of the grains for forensic reconstructions. The ability to independently corroborate the grain type classifications is desirable and provides additional weight to the findings of SEM analysis of the textures of quartz grains identified in forensic soil/sediment samples. AFM offers a quantitative means of analysis that complements SEM examination, and is a non-destructive technique that requires no sample preparation prior to scanning. It therefore has great potential to be used for forensic analysis where sample preservation is highly valuable. By taking quantitative topography scans, it is possible to produce 3D representations of microscopic surface textures and diagnostic features for examination. Furthermore, various empirical measures can be obtained from analysing the topography scans, including arithmetic average roughness, root-mean-square surface roughness, skewness, kurtosis, and multiple gaussian fits to height distributions. These empirical measures, combined with qualitative examination of the surfaces can help to discriminate between grain types and provide independent analysis that can corroborate the morphological grain typing based on the surface textures assigned using SEM. Furthermore, the findings from this study also demonstrate that quartz sand grain surfaces exhibit a statistically self-similar fractal nature that remains unchanged across scales. This indicates the potential for a further quantitative measure that could be utilised in the discrimination of quartz grains based on their provenance for forensic investigations. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Radiomics Evaluation of Histological Heterogeneity Using Multiscale Textures Derived From 3D Wavelet Transformation of Multispectral Images.

PubMed

Chaddad, Ahmad; Daniel, Paul; Niazi, Tamim

2018-01-01

Colorectal cancer (CRC) is markedly heterogeneous and develops progressively toward malignancy through several stages which include stroma (ST), benign hyperplasia (BH), intraepithelial neoplasia (IN) or precursor cancerous lesion, and carcinoma (CA). Identification of the malignancy stage of CRC pathology tissues (PT) allows the most appropriate therapeutic intervention. This study investigates multiscale texture features extracted from CRC pathology sections using 3D wavelet transform (3D-WT) filter. Multiscale features were extracted from digital whole slide images of 39 patients that were segmented in a pre-processing step using an active contour model. The capacity for multiscale texture to compare and classify between PTs was investigated using ANOVA significance test and random forest classifier models, respectively. 12 significant features derived from the multiscale texture (i.e., variance, entropy, and energy) were found to discriminate between CRC grades at a significance value of p  < 0.01 after correction. Combining multiscale texture features lead to a better predictive capacity compared to prediction models based on individual scale features with an average (±SD) classification accuracy of 93.33 (±3.52)%, sensitivity of 88.33 (± 4.12)%, and specificity of 96.89 (± 3.88)%. Entropy was found to be the best classifier feature across all the PT grades with an average of the area under the curve (AUC) value of 91.17, 94.21, 97.70, 100% for ST, BH, IN, and CA, respectively. Our results suggest that multiscale texture features based on 3D-WT are sensitive enough to discriminate between CRC grades with the entropy feature, the best predictor of pathology grade.

Electrostatic-Force-Assisted Dispensing Printing to Construct High-Aspect-Ratio of 0.79 Electrodes on a Textured Surface with Improved Adhesion and Contact Resistivity

PubMed Central

Shin, Dong-Youn; Yoo, Sung-Soo; Song, Hee-eun; Tak, Hyowon; Byun, Doyoung

2015-01-01

As a novel route to construct fine and abnormally high-aspect-ratio electrodes with excellent adhesion and reduced contact resistivity on a textured surface, an electrostatic-force-assisted dispensing printing technique is reported and compared with conventional dispensing and electrohydrodynamic jet printing techniques. The electrostatic force applied between a silver paste and the textured surface of a crystalline silicon solar cell wafer significantly improves the physical adhesion of the electrodes, whereas those fabricated using a conventional dispensing printing technique peel off with a silver paste containing 2 wt% of a fluorosurfactant. Moreover, the contact resistivity and dimensionless deviation of total resistance are significantly reduced from 2.19 ± 1.53 mΩ·cm2 to 0.98 ± 0.92 mΩ·cm2 and from 0.10 to 0.03, respectively. By utilizing electrodes with an abnormally high-aspect-ratio of 0.79 (the measured thickness and width are 30.4 μm and 38.3 μm, respectively), the cell efficiency is 17.2% on a polycrystalline silicon solar cell with an emitter sheet resistance of 60 Ω/sq. This cell efficiency is considerably higher than previously reported values obtained using a conventional electrohydrodynamic jet printing technique, by +0.48–3.5%p. PMID:26576857

Ferroelectricity emerging in strained (111)-textured ZrO{sub 2} thin films

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fan, Zhen, E-mail: a0082709@u.nus.edu, E-mail: msecj@nus.edu.sg; Deng, Jinyu; Liu, Ziyan

2016-01-04

(Anti-)ferroelectricity in complementary metal-oxide-semiconductor (CMOS)-compatible binary oxides have attracted considerable research interest recently. Here, we show that by using substrate-induced strain, the orthorhombic phase and the desired ferroelectricity could be achieved in ZrO{sub 2} thin films. Our theoretical analyses suggest that the strain imposed on the ZrO{sub 2} (111) film by the TiN/MgO (001) substrate would energetically favor the tetragonal (t) and orthorhombic (o) phases over the monoclinic (m) phase of ZrO{sub 2}, and the compressive strain along certain 〈11-2〉 directions may further stabilize the o-phase. Experimentally ZrO{sub 2} thin films are sputtered onto the MgO (001) substrates buffered bymore » epitaxial TiN layers. ZrO{sub 2} thin films exhibit t- and o-phases, which are highly (111)-textured and strained, as evidenced by X-ray diffraction and transmission electron microscopy. Both polarization-electric field (P-E) loops and corresponding current responses to voltage stimulations measured with appropriate applied fields reveal the ferroelectric sub-loop behavior of the ZrO{sub 2} films at certain thicknesses, confirming that the ferroelectric o-phase has been developed in the strained (111)-textured ZrO{sub 2} films. However, further increasing the applied field leads to the disappearance of ferroelectric hysteresis, the possible reasons of which are discussed.« less

Texture, flavor, and sensory quality of buffalo milk Cheddar cheese as influenced by reducing sodium salt content.

PubMed

Murtaza, M A; Huma, N; Sameen, A; Murtaza, M S; Mahmood, S; Mueen-ud-Din, G; Meraj, A

2014-11-01

The adverse health effects of dietary sodium demand the production of cheese with reduced salt content. The study was aimed to assess the effect of reducing the level of sodium chloride on the texture, flavor, and sensory qualities of Cheddar cheese. Cheddar cheese was manufactured from buffalo milk standardized at 4% fat level by adding sodium chloride at 2.5, 2.0, 1.5, 1.0, and 0.5% (wt/wt of the curd obtained). Cheese samples were ripened at 6 to 8 °C for 180 d and analyzed for chemical composition after 1 wk; for texture and proteolysis after 1, 60, 120, and 180 d; and for volatile flavor compounds and sensory quality after 180 d of ripening. Decreasing the salt level significantly reduced the salt-in-moisture and pH and increased the moisture-in-nonfat-substances and water activity. Cheese hardness, toughness, and crumbliness decreased but proteolysis increased considerably on reducing the sodium content and during cheese ripening. Lowering the salt levels appreciably enhanced the concentration of volatile compounds associated with flavor but negatively affected the sensory perception. We concluded that salt level in cheese can be successfully reduced to a great extent if proteolysis and development of off-flavors resulted by the growth of starter and nonstarter bacteria can be controlled. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

From Pixels to Response Maps: Discriminative Image Filtering for Face Alignment in the Wild.

PubMed

Asthana, Akshay; Zafeiriou, Stefanos; Tzimiropoulos, Georgios; Cheng, Shiyang; Pantic, Maja

2015-06-01

We propose a face alignment framework that relies on the texture model generated by the responses of discriminatively trained part-based filters. Unlike standard texture models built from pixel intensities or responses generated by generic filters (e.g. Gabor), our framework has two important advantages. First, by virtue of discriminative training, invariance to external variations (like identity, pose, illumination and expression) is achieved. Second, we show that the responses generated by discriminatively trained filters (or patch-experts) are sparse and can be modeled using a very small number of parameters. As a result, the optimization methods based on the proposed texture model can better cope with unseen variations. We illustrate this point by formulating both part-based and holistic approaches for generic face alignment and show that our framework outperforms the state-of-the-art on multiple "wild" databases. The code and dataset annotations are available for research purposes from http://ibug.doc.ic.ac.uk/resources.

[An object-based information extraction technology for dominant tree species group types].

PubMed

Tian, Tian; Fan, Wen-yi; Lu, Wei; Xiao, Xiang

2015-06-01

Information extraction for dominant tree group types is difficult in remote sensing image classification, howevers, the object-oriented classification method using high spatial resolution remote sensing data is a new method to realize the accurate type information extraction. In this paper, taking the Jiangle Forest Farm in Fujian Province as the research area, based on the Quickbird image data in 2013, the object-oriented method was adopted to identify the farmland, shrub-herbaceous plant, young afforested land, Pinus massoniana, Cunninghamia lanceolata and broad-leave tree types. Three types of classification factors including spectral, texture, and different vegetation indices were used to establish a class hierarchy. According to the different levels, membership functions and the decision tree classification rules were adopted. The results showed that the method based on the object-oriented method by using texture, spectrum and the vegetation indices achieved the classification accuracy of 91.3%, which was increased by 5.7% compared with that by only using the texture and spectrum.

Accelerating Time-Varying Hardware Volume Rendering Using TSP Trees and Color-Based Error Metrics

NASA Technical Reports Server (NTRS)

Ellsworth, David; Chiang, Ling-Jen; Shen, Han-Wei; Kwak, Dochan (Technical Monitor)

2000-01-01

This paper describes a new hardware volume rendering algorithm for time-varying data. The algorithm uses the Time-Space Partitioning (TSP) tree data structure to identify regions within the data that have spatial or temporal coherence. By using this coherence, the rendering algorithm can improve performance when the volume data is larger than the texture memory capacity by decreasing the amount of textures required. This coherence can also allow improved speed by appropriately rendering flat-shaded polygons instead of textured polygons, and by not rendering transparent regions. To reduce the polygonization overhead caused by the use of the hierarchical data structure, we introduce an optimization method using polygon templates. The paper also introduces new color-based error metrics, which more accurately identify coherent regions compared to the earlier scalar-based metrics. By showing experimental results from runs using different data sets and error metrics, we demonstrate that the new methods give substantial improvements in volume rendering performance.

Automatic system for radar echoes filtering based on textural features and artificial intelligence

NASA Astrophysics Data System (ADS)

Hedir, Mehdia; Haddad, Boualem

2017-10-01

Among the very popular Artificial Intelligence (AI) techniques, Artificial Neural Network (ANN) and Support Vector Machine (SVM) have been retained to process Ground Echoes (GE) on meteorological radar images taken from Setif (Algeria) and Bordeaux (France) with different climates and topologies. To achieve this task, AI techniques were associated with textural approaches. We used Gray Level Co-occurrence Matrix (GLCM) and Completed Local Binary Pattern (CLBP); both methods were largely used in image analysis. The obtained results show the efficiency of texture to preserve precipitations forecast on both sites with the accuracy of 98% on Bordeaux and 95% on Setif despite the AI technique used. 98% of GE are suppressed with SVM, this rate is outperforming ANN skills. CLBP approach associated to SVM eliminates 98% of GE and preserves precipitations forecast on Bordeaux site better than on Setif's, while it exhibits lower accuracy with ANN. SVM classifier is well adapted to the proposed application since the average filtering rate is 95-98% with texture and 92-93% with CLBP. These approaches allow removing Anomalous Propagations (APs) too with a better accuracy of 97.15% with texture and SVM. In fact, textural features associated to AI techniques are an efficient tool for incoherent radars to surpass spurious echoes.

Simultaneously enhanced strength and ductility for 3D-printed stainless steel 316L by selective laser melting

NASA Astrophysics Data System (ADS)

Sun, Zhongji; Tan, Xipeng; Tor, Shu Beng; Chua, Chee Kai

2018-04-01

Laser-based powder-bed fusion additive manufacturing or three-dimensional printing technology has gained tremendous attention due to its controllable, digital, and automated manufacturing process, which can afford a refined microstructure and superior strength. However, it is a major challenge to additively manufacture metal parts with satisfactory ductility and toughness. Here we report a novel selective laser melting process to simultaneously enhance the strength and ductility of stainless steel 316L by in-process engineering its microstructure into a <011> crystallographic texture. We find that the tensile strength and ductility of SLM-built stainless steel 316L samples could be enhanced by 16% and 40% respectively, with the engineered <011> textured microstructure compared to the common <001> textured microstructure. This is because the favorable nano-twinning mechanism was significantly more activated in the <011> textured stainless steel 316L samples during plastic deformation. In addition, kinetic simulations were performed to unveil the relationship between the melt pool geometry and crystallographic texture. The new additive manufacturing strategy of engineering the crystallographic texture can be applied to other metals and alloys with twinning-induced plasticity. This work paves the way to additively manufacture metal parts with high strength and high ductility.

Fast segmentation of industrial quality pavement images using Laws texture energy measures and k -means clustering

NASA Astrophysics Data System (ADS)

Mathavan, Senthan; Kumar, Akash; Kamal, Khurram; Nieminen, Michael; Shah, Hitesh; Rahman, Mujib

2016-09-01

Thousands of pavement images are collected by road authorities daily for condition monitoring surveys. These images typically have intensity variations and texture nonuniformities that make their segmentation challenging. The automated segmentation of such pavement images is crucial for accurate, thorough, and expedited health monitoring of roads. In the pavement monitoring area, well-known texture descriptors, such as gray-level co-occurrence matrices and local binary patterns, are often used for surface segmentation and identification. These, despite being the established methods for texture discrimination, are inherently slow. This work evaluates Laws texture energy measures as a viable alternative for pavement images for the first time. k-means clustering is used to partition the feature space, limiting the human subjectivity in the process. Data classification, hence image segmentation, is performed by the k-nearest neighbor method. Laws texture energy masks are shown to perform well with resulting accuracy and precision values of more than 80%. The implementations of the algorithm, in both MATLAB® and OpenCV/C++, are extensively compared against the state of the art for execution speed, clearly showing the advantages of the proposed method. Furthermore, the OpenCV-based segmentation shows a 100% increase in processing speed when compared to the fastest algorithm available in literature.

Quantitative Analysis of the Cervical Texture by Ultrasound and Correlation with Gestational Age.

PubMed

Baños, Núria; Perez-Moreno, Alvaro; Migliorelli, Federico; Triginer, Laura; Cobo, Teresa; Bonet-Carne, Elisenda; Gratacos, Eduard; Palacio, Montse

2017-01-01

Quantitative texture analysis has been proposed to extract robust features from the ultrasound image to detect subtle changes in the textures of the images. The aim of this study was to evaluate the feasibility of quantitative cervical texture analysis to assess cervical tissue changes throughout pregnancy. This was a cross-sectional study including singleton pregnancies between 20.0 and 41.6 weeks of gestation from women who delivered at term. Cervical length was measured, and a selected region of interest in the cervix was delineated. A model to predict gestational age based on features extracted from cervical images was developed following three steps: data splitting, feature transformation, and regression model computation. Seven hundred images, 30 per gestational week, were included for analysis. There was a strong correlation between the gestational age at which the images were obtained and the estimated gestational age by quantitative analysis of the cervical texture (R = 0.88). This study provides evidence that quantitative analysis of cervical texture can extract features from cervical ultrasound images which correlate with gestational age. Further research is needed to evaluate its applicability as a biomarker of the risk of spontaneous preterm birth, as well as its role in cervical assessment in other clinical situations in which cervical evaluation might be relevant. © 2016 S. Karger AG, Basel.