Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters

PubMed Central

Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei

2016-01-01

Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme. PMID:27362762

Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters.

PubMed

Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei

2016-01-01

Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme.

Research on Remote Sensing Geological Information Extraction Based on Object Oriented Classification

NASA Astrophysics Data System (ADS)

Gao, Hui

2018-04-01

The northern Tibet belongs to the Sub cold arid climate zone in the plateau. It is rarely visited by people. The geological working conditions are very poor. However, the stratum exposures are good and human interference is very small. Therefore, the research on the automatic classification and extraction of remote sensing geological information has typical significance and good application prospect. Based on the object-oriented classification in Northern Tibet, using the Worldview2 high-resolution remote sensing data, combined with the tectonic information and image enhancement, the lithological spectral features, shape features, spatial locations and topological relations of various geological information are excavated. By setting the threshold, based on the hierarchical classification, eight kinds of geological information were classified and extracted. Compared with the existing geological maps, the accuracy analysis shows that the overall accuracy reached 87.8561 %, indicating that the classification-oriented method is effective and feasible for this study area and provides a new idea for the automatic extraction of remote sensing geological information.

Identification of Cichlid Fishes from Lake Malawi Using Computer Vision

PubMed Central

Joo, Deokjin; Kwan, Ye-seul; Song, Jongwoo; Pinho, Catarina; Hey, Jody; Won, Yong-Jin

2013-01-01

Background The explosively radiating evolution of cichlid fishes of Lake Malawi has yielded an amazing number of haplochromine species estimated as many as 500 to 800 with a surprising degree of diversity not only in color and stripe pattern but also in the shape of jaw and body among them. As these morphological diversities have been a central subject of adaptive speciation and taxonomic classification, such high diversity could serve as a foundation for automation of species identification of cichlids. Methodology/Principal Finding Here we demonstrate a method for automatic classification of the Lake Malawi cichlids based on computer vision and geometric morphometrics. For this end we developed a pipeline that integrates multiple image processing tools to automatically extract informative features of color and stripe patterns from a large set of photographic images of wild cichlids. The extracted information was evaluated by statistical classifiers Support Vector Machine and Random Forests. Both classifiers performed better when body shape information was added to the feature of color and stripe. Besides the coloration and stripe pattern, body shape variables boosted the accuracy of classification by about 10%. The programs were able to classify 594 live cichlid individuals belonging to 12 different classes (species and sexes) with an average accuracy of 78%, contrasting to a mere 42% success rate by human eyes. The variables that contributed most to the accuracy were body height and the hue of the most frequent color. Conclusions Computer vision showed a notable performance in extracting information from the color and stripe patterns of Lake Malawi cichlids although the information was not enough for errorless species identification. Our results indicate that there appears an unavoidable difficulty in automatic species identification of cichlid fishes, which may arise from short divergence times and gene flow between closely related species. PMID:24204918

Contour matching for a fish recognition and migration-monitoring system

NASA Astrophysics Data System (ADS)

Lee, Dah-Jye; Schoenberger, Robert B.; Shiozawa, Dennis; Xu, Xiaoqian; Zhan, Pengcheng

2004-12-01

Fish migration is being monitored year round to provide valuable information for the study of behavioral responses of fish to environmental variations. However, currently all monitoring is done by human observers. An automatic fish recognition and migration monitoring system is more efficient and can provide more accurate data. Such a system includes automatic fish image acquisition, contour extraction, fish categorization, and data storage. Shape is a very important characteristic and shape analysis and shape matching are studied for fish recognition. Previous work focused on finding critical landmark points on fish shape using curvature function analysis. Fish recognition based on landmark points has shown satisfying results. However, the main difficulty of this approach is that landmark points sometimes cannot be located very accurately. Whole shape matching is used for fish recognition in this paper. Several shape descriptors, such as Fourier descriptors, polygon approximation and line segments, are tested. A power cepstrum technique has been developed in order to improve the categorization speed using contours represented in tangent space with normalized length. Design and integration including image acquisition, contour extraction and fish categorization are discussed in this paper. Fish categorization results based on shape analysis and shape matching are also included.

Extracting Objects for Aerial Manipulation on UAVs Using Low Cost Stereo Sensors

PubMed Central

Ramon Soria, Pablo; Bevec, Robert; Arrue, Begoña C.; Ude, Aleš; Ollero, Aníbal

2016-01-01

Giving unmanned aerial vehicles (UAVs) the possibility to manipulate objects vastly extends the range of possible applications. This applies to rotary wing UAVs in particular, where their capability of hovering enables a suitable position for in-flight manipulation. Their manipulation skills must be suitable for primarily natural, partially known environments, where UAVs mostly operate. We have developed an on-board object extraction method that calculates information necessary for autonomous grasping of objects, without the need to provide the model of the object’s shape. A local map of the work-zone is generated using depth information, where object candidates are extracted by detecting areas different to our floor model. Their image projections are then evaluated using support vector machine (SVM) classification to recognize specific objects or reject bad candidates. Our method builds a sparse cloud representation of each object and calculates the object’s centroid and the dominant axis. This information is then passed to a grasping module. Our method works under the assumption that objects are static and not clustered, have visual features and the floor shape of the work-zone area is known. We used low cost cameras for creating depth information that cause noisy point clouds, but our method has proved robust enough to process this data and return accurate results. PMID:27187413

Extracting Objects for Aerial Manipulation on UAVs Using Low Cost Stereo Sensors.

PubMed

Ramon Soria, Pablo; Bevec, Robert; Arrue, Begoña C; Ude, Aleš; Ollero, Aníbal

2016-05-14

Giving unmanned aerial vehicles (UAVs) the possibility to manipulate objects vastly extends the range of possible applications. This applies to rotary wing UAVs in particular, where their capability of hovering enables a suitable position for in-flight manipulation. Their manipulation skills must be suitable for primarily natural, partially known environments, where UAVs mostly operate. We have developed an on-board object extraction method that calculates information necessary for autonomous grasping of objects, without the need to provide the model of the object's shape. A local map of the work-zone is generated using depth information, where object candidates are extracted by detecting areas different to our floor model. Their image projections are then evaluated using support vector machine (SVM) classification to recognize specific objects or reject bad candidates. Our method builds a sparse cloud representation of each object and calculates the object's centroid and the dominant axis. This information is then passed to a grasping module. Our method works under the assumption that objects are static and not clustered, have visual features and the floor shape of the work-zone area is known. We used low cost cameras for creating depth information that cause noisy point clouds, but our method has proved robust enough to process this data and return accurate results.

Applying high resolution remote sensing image and DEM to falling boulder hazard assessment

NASA Astrophysics Data System (ADS)

Huang, Changqing; Shi, Wenzhong; Ng, K. C.

2005-10-01

Boulder fall hazard assessing generally requires gaining the boulder information. The extensive mapping and surveying fieldwork is a time-consuming, laborious and dangerous conventional method. So this paper proposes an applying image processing technology to extract boulder and assess boulder fall hazard from high resolution remote sensing image. The method can replace the conventional method and extract the boulder information in high accuracy, include boulder size, shape, height and the slope and aspect of its position. With above boulder information, it can be satisfied for assessing, prevention and cure boulder fall hazard.

Airway extraction from 3D chest CT volumes based on iterative extension of VOI enhanced by cavity enhancement filter

NASA Astrophysics Data System (ADS)

Meng, Qier; Kitasaka, Takayuki; Oda, Masahiro; Mori, Kensaku

2017-03-01

Airway segmentation is an important step in analyzing chest CT volumes for computerized lung cancer detection, emphysema diagnosis, asthma diagnosis, and pre- and intra-operative bronchoscope navigation. However, obtaining an integrated 3-D airway tree structure from a CT volume is a quite challenging task. This paper presents a novel airway segmentation method based on intensity structure analysis and bronchi shape structure analysis in volume of interest (VOI). This method segments the bronchial regions by applying the cavity enhancement filter (CEF) to trace the bronchial tree structure from the trachea. It uses the CEF in each VOI to segment each branch and to predict the positions of VOIs which envelope the bronchial regions in next level. At the same time, a leakage detection is performed to avoid the leakage by analysing the pixel information and the shape information of airway candidate regions extracted in the VOI. Bronchial regions are finally obtained by unifying the extracted airway regions. The experiments results showed that the proposed method can extract most of the bronchial region in each VOI and led good results of the airway segmentation.

Extraction of endoscopic images for biomedical figure classification

NASA Astrophysics Data System (ADS)

Xue, Zhiyun; You, Daekeun; Chachra, Suchet; Antani, Sameer; Long, L. R.; Demner-Fushman, Dina; Thoma, George R.

2015-03-01

Modality filtering is an important feature in biomedical image searching systems and may significantly improve the retrieval performance of the system. This paper presents a new method for extracting endoscopic image figures from photograph images in biomedical literature, which are found to have highly diverse content and large variability in appearance. Our proposed method consists of three main stages: tissue image extraction, endoscopic image candidate extraction, and ophthalmic image filtering. For tissue image extraction we use image patch level clustering and MRF relabeling to detect images containing skin/tissue regions. Next, we find candidate endoscopic images by exploiting the round shape characteristics that commonly appear in these images. However, this step needs to compensate for images where endoscopic regions are not entirely round. In the third step we filter out the ophthalmic images which have shape characteristics very similar to the endoscopic images. We do this by using text information, specifically, anatomy terms, extracted from the figure caption. We tested and evaluated our method on a dataset of 115,370 photograph figures, and achieved promising precision and recall rates of 87% and 84%, respectively.

A statistical shape modelling framework to extract 3D shape biomarkers from medical imaging data: assessing arch morphology of repaired coarctation of the aorta.

PubMed

Bruse, Jan L; McLeod, Kristin; Biglino, Giovanni; Ntsinjana, Hopewell N; Capelli, Claudio; Hsia, Tain-Yen; Sermesant, Maxime; Pennec, Xavier; Taylor, Andrew M; Schievano, Silvia

2016-05-31

Medical image analysis in clinical practice is commonly carried out on 2D image data, without fully exploiting the detailed 3D anatomical information that is provided by modern non-invasive medical imaging techniques. In this paper, a statistical shape analysis method is presented, which enables the extraction of 3D anatomical shape features from cardiovascular magnetic resonance (CMR) image data, with no need for manual landmarking. The method was applied to repaired aortic coarctation arches that present complex shapes, with the aim of capturing shape features as biomarkers of potential functional relevance. The method is presented from the user-perspective and is evaluated by comparing results with traditional morphometric measurements. Steps required to set up the statistical shape modelling analyses, from pre-processing of the CMR images to parameter setting and strategies to account for size differences and outliers, are described in detail. The anatomical mean shape of 20 aortic arches post-aortic coarctation repair (CoA) was computed based on surface models reconstructed from CMR data. By analysing transformations that deform the mean shape towards each of the individual patient's anatomy, shape patterns related to differences in body surface area (BSA) and ejection fraction (EF) were extracted. The resulting shape vectors, describing shape features in 3D, were compared with traditionally measured 2D and 3D morphometric parameters. The computed 3D mean shape was close to population mean values of geometric shape descriptors and visually integrated characteristic shape features associated with our population of CoA shapes. After removing size effects due to differences in body surface area (BSA) between patients, distinct 3D shape features of the aortic arch correlated significantly with EF (r = 0.521, p = .022) and were well in agreement with trends as shown by traditional shape descriptors. The suggested method has the potential to discover previously unknown 3D shape biomarkers from medical imaging data. Thus, it could contribute to improving diagnosis and risk stratification in complex cardiac disease.

Three-Dimensional Grain Shape-Fabric from Unconsolidated Pyroclastic Density Current Deposits: Implications for Extracting Flow Direction and Insights on Rheology

NASA Astrophysics Data System (ADS)

Hawkins, T. T.; Brand, B. D.; Sarrochi, D.; Pollock, N.

2016-12-01

One of the greatest challenges volcanologists face is the ability to extrapolate information about eruption dynamics and emplacement conditions from deposits. Pyroclastic density current (PDC) deposits are particularly challenging given the wide range of initial current conditions, (e.g., granular, fluidized, concentrated, dilute), and rapid flow transformations due to interaction with evolving topography. Analysis of particle shape-fabric can be used to determine flow direction, and may help to understand the rheological characteristics of the flows. However, extracting shape-fabric information from outcrop (2D) apparent fabric is limited, especially when outcrop exposure is incomplete or lacks context. To better understand and quantify the complex flow dynamics reflected in PDC deposits, we study the complete shape-fabric data in 3D using oriented samples. In the field, the prospective sample is carved from the unconsolidated deposit in blocks, the dimensions of which depend on the average clast size in the sample. The sample is saturated in situ with a water-based sodium silicate solution, then wrapped in plaster-soaked gauze to form a protective cast. The orientation of the sample is recorded on the block faces. The samples dry for five days and are then extracted in intact blocks. In the lab, the sample is vacuum impregnated with sodium silicate and cured in an oven. The fully lithified sample is first cut along the plan view to identify orientations of the long axes of the grains (flow direction), and then cut in the two plains perpendicular to grain elongation. 3D fabric analysis is performed using high resolution images of the cut-faces using computer assisted image analysis software devoted to shape-fabric analysis. Here we present the results of samples taken from the 18 May 1980 PDC deposit facies, including massive, diffuse-stratified and cross-stratified lapilli tuff. We show a relationship between the strength of iso-orientation of the elongated particles and different facies architectures, which is used to interpret rheological conditions of the flow. We chose the 18 May PDC deposits because their well-exposed and well-studied outcrops provide context, which allow us to test the method and extract information useful for interpreting ancient deposits that lack context.

A novel 3D shape descriptor for automatic retrieval of anatomical structures from medical images

NASA Astrophysics Data System (ADS)

Nunes, Fátima L. S.; Bergamasco, Leila C. C.; Delmondes, Pedro H.; Valverde, Miguel A. G.; Jackowski, Marcel P.

2017-03-01

Content-based image retrieval (CBIR) aims at retrieving from a database objects that are similar to an object provided by a query, by taking into consideration a set of extracted features. While CBIR has been widely applied in the two-dimensional image domain, the retrieval of3D objects from medical image datasets using CBIR remains to be explored. In this context, the development of descriptors that can capture information specific to organs or structures is desirable. In this work, we focus on the retrieval of two anatomical structures commonly imaged by Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) techniques, the left ventricle of the heart and blood vessels. Towards this aim, we developed the Area-Distance Local Descriptor (ADLD), a novel 3D local shape descriptor that employs mesh geometry information, namely facet area and distance from centroid to surface, to identify shape changes. Because ADLD only considers surface meshes extracted from volumetric medical images, it substantially diminishes the amount of data to be analyzed. A 90% precision rate was obtained when retrieving both convex (left ventricle) and non-convex structures (blood vessels), allowing for detection of abnormalities associated with changes in shape. Thus, ADLD has the potential to aid in the diagnosis of a wide range of vascular and cardiac diseases.

3D local feature BKD to extract road information from mobile laser scanning point clouds

NASA Astrophysics Data System (ADS)

Yang, Bisheng; Liu, Yuan; Dong, Zhen; Liang, Fuxun; Li, Bijun; Peng, Xiangyang

2017-08-01

Extracting road information from point clouds obtained through mobile laser scanning (MLS) is essential for autonomous vehicle navigation, and has hence garnered a growing amount of research interest in recent years. However, the performance of such systems is seriously affected due to varying point density and noise. This paper proposes a novel three-dimensional (3D) local feature called the binary kernel descriptor (BKD) to extract road information from MLS point clouds. The BKD consists of Gaussian kernel density estimation and binarization components to encode the shape and intensity information of the 3D point clouds that are fed to a random forest classifier to extract curbs and markings on the road. These are then used to derive road information, such as the number of lanes, the lane width, and intersections. In experiments, the precision and recall of the proposed feature for the detection of curbs and road markings on an urban dataset and a highway dataset were as high as 90%, thus showing that the BKD is accurate and robust against varying point density and noise.

Two-dimensional shape recognition using sparse distributed memory

NASA Technical Reports Server (NTRS)

Kanerva, Pentti; Olshausen, Bruno

1990-01-01

Researchers propose a method for recognizing two-dimensional shapes (hand-drawn characters, for example) with an associative memory. The method consists of two stages: first, the image is preprocessed to extract tangents to the contour of the shape; second, the set of tangents is converted to a long bit string for recognition with sparse distributed memory (SDM). SDM provides a simple, massively parallel architecture for an associative memory. Long bit vectors (256 to 1000 bits, for example) serve as both data and addresses to the memory, and patterns are grouped or classified according to similarity in Hamming distance. At the moment, tangents are extracted in a simple manner by progressively blurring the image and then using a Canny-type edge detector (Canny, 1986) to find edges at each stage of blurring. This results in a grid of tangents. While the technique used for obtaining the tangents is at present rather ad hoc, researchers plan to adopt an existing framework for extracting edge orientation information over a variety of resolutions, such as suggested by Watson (1987, 1983), Marr and Hildreth (1980), or Canny (1986).

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.

Semi-automatic building extraction in informal settlements from high-resolution satellite imagery

NASA Astrophysics Data System (ADS)

Mayunga, Selassie David

The extraction of man-made features from digital remotely sensed images is considered as an important step underpinning management of human settlements in any country. Man-made features and buildings in particular are required for varieties of applications such as urban planning, creation of geographical information systems (GIS) databases and Urban City models. The traditional man-made feature extraction methods are very expensive in terms of equipment, labour intensive, need well-trained personnel and cannot cope with changing environments, particularly in dense urban settlement areas. This research presents an approach for extracting buildings in dense informal settlement areas using high-resolution satellite imagery. The proposed system uses a novel strategy of extracting building by measuring a single point at the approximate centre of the building. The fine measurement of the building outlines is then effected using a modified snake model. The original snake model on which this framework is based, incorporates an external constraint energy term which is tailored to preserving the convergence properties of the snake model; its use to unstructured objects will negatively affect their actual shapes. The external constrained energy term was removed from the original snake model formulation, thereby, giving ability to cope with high variability of building shapes in informal settlement areas. The proposed building extraction system was tested on two areas, which have different situations. The first area was Tungi in Dar Es Salaam, Tanzania where three sites were tested. This area is characterized by informal settlements, which are illegally formulated within the city boundaries. The second area was Oromocto in New Brunswick, Canada where two sites were tested. Oromocto area is mostly flat and the buildings are constructed using similar materials. Qualitative and quantitative measures were employed to evaluate the accuracy of the results as well as the performance of the system. The qualitative and quantitative measures were based on visual inspection and by comparing the measured coordinates to the reference data respectively. In the course of this process, a mean area coverage of 98% was achieved for Dar Es Salaam test sites, which globally indicated that the extracted building polygons were close to the ground truth data. Furthermore, the proposed system saved time to extract a single building by 32%. Although the extracted building polygons are within the perimeter of ground truth data, visually some of the extracted building polygons were somewhat distorted. This implies that interactive post-editing process is necessary for cartographic representation.

Sugarcane Crop Extraction Using Object-Oriented Method from ZY-3 High Resolution Satellite Tlc Image

NASA Astrophysics Data System (ADS)

Luo, H.; Ling, Z. Y.; Shao, G. Z.; Huang, Y.; He, Y. Q.; Ning, W. Y.; Zhong, Z.

2018-04-01

Sugarcane is one of the most important crops in Guangxi, China. As the development of satellite remote sensing technology, more remotely sensed images can be used for monitoring sugarcane crop. With the help of Three Line Camera (TLC) images, wide coverage and stereoscopic mapping ability, Chinese ZY-3 high resolution stereoscopic mapping satellite is useful in attaining more information for sugarcane crop monitoring, such as spectral, shape, texture difference between forward, nadir and backward images. Digital surface model (DSM) derived from ZY-3 TLC images are also able to provide height information for sugarcane crop. In this study, we make attempt to extract sugarcane crop from ZY-3 images, which are acquired in harvest period. Ortho-rectified TLC images, fused image, DSM are processed for our extraction. Then Object-oriented method is used in image segmentation, example collection, and feature extraction. The results of our study show that with the help of ZY-3 TLC image, the information of sugarcane crop in harvest time can be automatic extracted, with an overall accuracy of about 85.3 %.

Quantitative Understanding of SHAPE Mechanism from RNA Structure and Dynamics Analysis.

PubMed

Hurst, Travis; Xu, Xiaojun; Zhao, Peinan; Chen, Shi-Jie

2018-05-10

The selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) method probes RNA local structural and dynamic information at single nucleotide resolution. To gain quantitative insights into the relationship between nucleotide flexibility, RNA 3D structure, and SHAPE reactivity, we develop a 3D Structure-SHAPE Relationship model (3DSSR) to rebuild SHAPE profiles from 3D structures. The model starts from RNA structures and combines nucleotide interaction strength and conformational propensity, ligand (SHAPE reagent) accessibility, and base-pairing pattern through a composite function to quantify the correlation between SHAPE reactivity and nucleotide conformational stability. The 3DSSR model shows the relationship between SHAPE reactivity and RNA structure and energetics. Comparisons between the 3DSSR-predicted SHAPE profile and the experimental SHAPE data show correlation, suggesting that the extracted analytical function may have captured the key factors that determine the SHAPE reactivity profile. Furthermore, the theory offers an effective method to sieve RNA 3D models and exclude models that are incompatible with experimental SHAPE data.

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

Liu, Richen; Guo, Hanqi; Yuan, Xiaoru

Most of the existing approaches to visualize vector field ensembles are to reveal the uncertainty of individual variables, for example, statistics, variability, etc. However, a user-defined derived feature like vortex or air mass is also quite significant, since they make more sense to domain scientists. In this paper, we present a new framework to extract user-defined derived features from different simulation runs. Specially, we use a detail-to-overview searching scheme to help extract vortex with a user-defined shape. We further compute the geometry information including the size, the geo-spatial location of the extracted vortexes. We also design some linked views tomore » compare them between different runs. At last, the temporal information such as the occurrence time of the feature is further estimated and compared. Results show that our method is capable of extracting the features across different runs and comparing them spatially and temporally.« less

Breast MRI radiomics: comparison of computer- and human-extracted imaging phenotypes.

PubMed

Sutton, Elizabeth J; Huang, Erich P; Drukker, Karen; Burnside, Elizabeth S; Li, Hui; Net, Jose M; Rao, Arvind; Whitman, Gary J; Zuley, Margarita; Ganott, Marie; Bonaccio, Ermelinda; Giger, Maryellen L; Morris, Elizabeth A

2017-01-01

In this study, we sought to investigate if computer-extracted magnetic resonance imaging (MRI) phenotypes of breast cancer could replicate human-extracted size and Breast Imaging-Reporting and Data System (BI-RADS) imaging phenotypes using MRI data from The Cancer Genome Atlas (TCGA) project of the National Cancer Institute. Our retrospective interpretation study involved analysis of Health Insurance Portability and Accountability Act-compliant breast MRI data from The Cancer Imaging Archive, an open-source database from the TCGA project. This study was exempt from institutional review board approval at Memorial Sloan Kettering Cancer Center and the need for informed consent was waived. Ninety-one pre-operative breast MRIs with verified invasive breast cancers were analysed. Three fellowship-trained breast radiologists evaluated the index cancer in each case according to size and the BI-RADS lexicon for shape, margin, and enhancement (human-extracted image phenotypes [HEIP]). Human inter-observer agreement was analysed by the intra-class correlation coefficient (ICC) for size and Krippendorff's α for other measurements. Quantitative MRI radiomics of computerised three-dimensional segmentations of each cancer generated computer-extracted image phenotypes (CEIP). Spearman's rank correlation coefficients were used to compare HEIP and CEIP. Inter-observer agreement for HEIP varied, with the highest agreement seen for size (ICC 0.679) and shape (ICC 0.527). The computer-extracted maximum linear size replicated the human measurement with p  < 10 -12 . CEIP of shape, specifically sphericity and irregularity, replicated HEIP with both p values < 0.001. CEIP did not demonstrate agreement with HEIP of tumour margin or internal enhancement. Quantitative radiomics of breast cancer may replicate human-extracted tumour size and BI-RADS imaging phenotypes, thus enabling precision medicine.

Research on improved edge extraction algorithm of rectangular piece

NASA Astrophysics Data System (ADS)

He, Yi-Bin; Zeng, Ya-Jun; Chen, Han-Xin; Xiao, San-Xia; Wang, Yan-Wei; Huang, Si-Yu

Traditional edge detection operators such as Prewitt operator, LOG operator and Canny operator, etc. cannot meet the requirements of the modern industrial measurement. This paper proposes a kind of image edge detection algorithm based on improved morphological gradient. It can be detect the image using structural elements, which deals with the characteristic information of the image directly. Choosing different shapes and sizes of structural elements to use together, the ideal image edge information can be detected. The experimental result shows that the algorithm can well extract image edge with noise, which is clearer, and has more detailed edges compared with the previous edge detection algorithm.

When navigating wood ants use the centre of mass of a shape to extract directional information from a panoramic skyline.

PubMed

Woodgate, Joseph L; Buehlmann, Cornelia; Collett, Thomas S

2016-06-01

Bees and ants can control their direction of travel within a familiar landscape using the information available in the surrounding visual scene. To learn more about the visual cues that contribute to this directional control, we have examined how wood ants obtain direction from a single shape that is presented in an otherwise uniform panorama. Earlier experiments revealed that when an ant's goal is aligned with a point within a prominent shape, the ant is guided by a global property of the shape: it learns the relative areas of the shape that lie to its left and right when facing the goal and sets its path by keeping the proportions at the memorised value. This strategy cannot be applied when the direction of the goal lies outside the shape. To see whether a different global feature of the shape might guide ants under these conditions, we trained ants to follow a direction to a point outside a single shape and then analysed their direction of travel when they were presented with different shapes. The tests indicate that ants learn the retinal position of the centre of mass of the training shape when facing the goal and can then guide themselves by placing the centre of mass of training and test shapes in this learnt position. © 2016. Published by The Company of Biologists Ltd.

Advanced transcatheter aortic valve implantation (TAVI) planning from CT with ShapeForest.

PubMed

Swee, Joshua K Y; Grbić, Saša

2014-01-01

Transcatheter aortic valve implantation (TAVI) is becoming a standard treatment for non-operable and high-risk patients with symptomatic severe aortic valve stenosis. As there is no direct view or access to the affected anatomy, comprehensive preoperative planning is crucial for a successful outcome, with the most important decisions made during planning being the selection of the proper implant size, and determining the correct C-arm angulations. While geometric models extracted from 3D images are often used to derive these measurements, the complex shape variation of the AV anatomy found in these patients causes many of the shape representations used to estimate such geometric models to fail in capturing morphological characteristics in sufficient detail. In addition, most current approaches only model the aortic valve (AV), omitting modeling the left ventricle outflow tract (LVOT) entirely despite its high correlation with severe complications such as annulus ruptures, paravalvular leaks and myocardial infarction. We propose a fully automated method to extract patient specific models of the AV and the LVOT, and derive comprehensive biomarkers for accurate TAVI planning. We utilize a novel shape representation--the ShapeForest--which is able to model complex shape variation, preserves local shape information, and incorporates prior knowledge during shape space inference. Extensive quantitative and qualitative experiments performed on 630 volumetric data sets demonstrate an accuracy of 0.69 mm for the AV and 0.83 mm for the LVOT, an improvement of over 16% and 18% respectively when compared against state of the art methods.

Automated endoscopic navigation and advisory system from medical image

NASA Astrophysics Data System (ADS)

Kwoh, Chee K.; Khan, Gul N.; Gillies, Duncan F.

1999-05-01

In this paper, we present a review of the research conducted by our group to design an automatic endoscope navigation and advisory system. The whole system can be viewed as a two-layer system. The first layer is at the signal level, which consists of the processing that will be performed on a series of images to extract all the identifiable features. The information is purely dependent on what can be extracted from the 'raw' images. At the signal level, the first task is performed by detecting a single dominant feature, lumen. Few methods of identifying the lumen are proposed. The first method used contour extraction. Contours are extracted by edge detection, thresholding and linking. This method required images to be divided into overlapping squares (8 by 8 or 4 by 4) where line segments are extracted by using a Hough transform. Perceptual criteria such as proximity, connectivity, similarity in orientation, contrast and edge pixel intensity, are used to group edges both strong and weak. This approach is called perceptual grouping. The second method is based on a region extraction using split and merge approach using spatial domain data. An n-level (for a 2' by 2' image) quadtree based pyramid structure is constructed to find the most homogenous large dark region, which in most cases corresponds to the lumen. The algorithm constructs the quadtree from the bottom (pixel) level upward, recursively and computes the mean and variance of image regions corresponding to quadtree nodes. On reaching the root, the largest uniform seed region, whose mean corresponds to a lumen is selected that is grown by merging with its neighboring regions. In addition to the use of two- dimensional information in the form of regions and contours, three-dimensional shape can provide additional information that will enhance the system capabilities. Shape or depth information from an image is estimated by various methods. A particular technique suitable for endoscopy is the shape from shading, which is developed to obtain the relative depth of the colon surface in the image by assuming a point light source very close to the camera. If we assume the colon has a shape similar to a tube, then a reasonable approximation of the position of the center of the colon (lumen) will be a function of the direction in which the majority of the normal vectors of shape are pointing. The second layer is the control layer and at this level, a decision model must be built for endoscope navigation and advisory system. The system that we built is the models of probabilistic networks that create a basic, artificial intelligence system for navigation in the colon. We have constructed the probabilistic networks from correlated objective data using the maximum weighted spanning tree algorithm. In the construction of a probabilistic network, it is always assumed that the variables starting from the same parent are conditionally independent. However, this may not hold and will give rise to incorrect inferences. In these cases, we proposed the creation of a hidden node to modify the network topology, which in effect models the dependency of correlated variables, to solve the problem. The conditional probability matrices linking the hidden node to its neighbors are determined using a gradient descent method which minimizing the objective cost function. The error gradients can be treated as updating messages and ca be propagated in any direction throughout any singly connected network to adjust the network parameters. With the above two- level approach, we have been able to build an automated endoscope navigation and advisory system successfully.

Research of building information extraction and evaluation based on high-resolution remote-sensing imagery

NASA Astrophysics Data System (ADS)

Cao, Qiong; Gu, Lingjia; Ren, Ruizhi; Wang, Lang

2016-09-01

Building extraction currently is important in the application of high-resolution remote sensing imagery. At present, quite a few algorithms are available for detecting building information, however, most of them still have some obvious disadvantages, such as the ignorance of spectral information, the contradiction between extraction rate and extraction accuracy. The purpose of this research is to develop an effective method to detect building information for Chinese GF-1 data. Firstly, the image preprocessing technique is used to normalize the image and image enhancement is used to highlight the useful information in the image. Secondly, multi-spectral information is analyzed. Subsequently, an improved morphological building index (IMBI) based on remote sensing imagery is proposed to get the candidate building objects. Furthermore, in order to refine building objects and further remove false objects, the post-processing (e.g., the shape features, the vegetation index and the water index) is employed. To validate the effectiveness of the proposed algorithm, the omission errors (OE), commission errors (CE), the overall accuracy (OA) and Kappa are used at final. The proposed method can not only effectively use spectral information and other basic features, but also avoid extracting excessive interference details from high-resolution remote sensing images. Compared to the original MBI algorithm, the proposed method reduces the OE by 33.14% .At the same time, the Kappa increase by 16.09%. In experiments, IMBI achieved satisfactory results and outperformed other algorithms in terms of both accuracies and visual inspection

Extraction of liver volumetry based on blood vessel from the portal phase CT dataset

NASA Astrophysics Data System (ADS)

Maklad, Ahmed S.; Matsuhiro, Mikio; Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Utsunomiya, Tohru; Shimada, Mitsuo

2012-02-01

At liver surgery planning stage, the liver volumetry would be essential for surgeons. Main problem at liver extraction is the wide variability of livers in shapes and sizes. Since, hepatic blood vessels structure varies from a person to another and covers liver region, the present method uses that information for extraction of liver in two stages. The first stage is to extract abdominal blood vessels in the form of hepatic and nonhepatic blood vessels. At the second stage, extracted vessels are used to control extraction of liver region automatically. Contrast enhanced CT datasets at only the portal phase of 50 cases is used. Those data include 30 abnormal livers. A reference for all cases is done through a comparison of two experts labeling results and correction of their inter-reader variability. Results of the proposed method agree with the reference at an average rate of 97.8%. Through application of different metrics mentioned at MICCAI workshop for liver segmentation, it is found that: volume overlap error is 4.4%, volume difference is 0.3%, average symmetric distance is 0.7 mm, Root mean square symmetric distance is 0.8 mm, and maximum distance is 15.8 mm. These results represent the average of overall data and show an improved accuracy compared to current liver segmentation methods. It seems to be a promising method for extraction of liver volumetry of various shapes and sizes.

Point Cloud Classification of Tesserae from Terrestrial Laser Data Combined with Dense Image Matching for Archaeological Information Extraction

NASA Astrophysics Data System (ADS)

Poux, F.; Neuville, R.; Billen, R.

2017-08-01

Reasoning from information extraction given by point cloud data mining allows contextual adaptation and fast decision making. However, to achieve this perceptive level, a point cloud must be semantically rich, retaining relevant information for the end user. This paper presents an automatic knowledge-based method for pre-processing multi-sensory data and classifying a hybrid point cloud from both terrestrial laser scanning and dense image matching. Using 18 features including sensor's biased data, each tessera in the high-density point cloud from the 3D captured complex mosaics of Germigny-des-prés (France) is segmented via a colour multi-scale abstraction-based featuring extracting connectivity. A 2D surface and outline polygon of each tessera is generated by a RANSAC plane extraction and convex hull fitting. Knowledge is then used to classify every tesserae based on their size, surface, shape, material properties and their neighbour's class. The detection and semantic enrichment method shows promising results of 94% correct semantization, a first step toward the creation of an archaeological smart point cloud.

Three-dimensional shape perception from chromatic orientation flows

PubMed Central

Zaidi, Qasim; Li, Andrea

2010-01-01

The role of chromatic information in 3-D shape perception is controversial. We resolve this controversy by showing that chromatic orientation flows are sufficient for accurate perception of 3-D shape. Chromatic flows required less cone contrast to convey shape than did achromatic flows, thus ruling out luminance artifacts as a problem. Luminance artifacts were also ruled out by a protanope’s inability to see 3-D shape from chromatic flows. Since chromatic orientation flows can only be extracted from retinal images by neurons that are responsive to color modulations and selective for orientation, the psychophysical results also resolve the controversy over the existence of such neurons. In addition, we show that identification of 3-D shapes from chromatic flows can be masked by luminance modulations, indicating that it is subserved by orientation-tuned neurons sensitive to both chromatic and luminance modulations. PMID:16961963

Spectral identification of minerals using imaging spectrometry data: Evaluating the effects of signal to noise and spectral resolution using the tricorder algorithm

NASA Technical Reports Server (NTRS)

Swayze, Gregg A.; Clark, Roger N.

1995-01-01

The rapid development of sophisticated imaging spectrometers and resulting flood of imaging spectrometry data has prompted a rapid parallel development of spectral-information extraction technology. Even though these extraction techniques have evolved along different lines (band-shape fitting, endmember unmixing, near-infrared analysis, neural-network fitting, and expert systems to name a few), all are limited by the spectrometer's signal to noise (S/N) and spectral resolution in producing useful information. This study grew from a need to quantitatively determine what effects these parameters have on our ability to differentiate between mineral absorption features using a band-shape fitting algorithm. We chose to evaluate the AVIRIS, HYDICE, MIVIS, GERIS, VIMS, NIMS, and ASTER instruments because they collect data over wide S/N and spectral-resolution ranges. The study evaluates the performance of the Tricorder algorithm, in differentiating between mineral spectra in the 0.4-2.5 micrometer spectral region. The strength of the Tricorder algorithm is in its ability to produce an easily understood comparison of band shape that can concentrate on small relevant portions of the spectra, giving it an advantage over most unmixing schemes, and in that it need not spend large amounts of time reoptimizing each time a new mineral component is added to its reference library, as is the case with neural-network schemes. We believe the flexibility of the Tricorder algorithm is unparalleled among spectral-extraction techniques and that the results from this study, although dealing with minerals, will have direct applications to spectral identification in other disciplines.

SEGMENTATION OF MITOCHONDRIA IN ELECTRON MICROSCOPY IMAGES USING ALGEBRAIC CURVES.

PubMed

Seyedhosseini, Mojtaba; Ellisman, Mark H; Tasdizen, Tolga

2013-01-01

High-resolution microscopy techniques have been used to generate large volumes of data with enough details for understanding the complex structure of the nervous system. However, automatic techniques are required to segment cells and intracellular structures in these multi-terabyte datasets and make anatomical analysis possible on a large scale. We propose a fully automated method that exploits both shape information and regional statistics to segment irregularly shaped intracellular structures such as mitochondria in electron microscopy (EM) images. The main idea is to use algebraic curves to extract shape features together with texture features from image patches. Then, these powerful features are used to learn a random forest classifier, which can predict mitochondria locations precisely. Finally, the algebraic curves together with regional information are used to segment the mitochondria at the predicted locations. We demonstrate that our method outperforms the state-of-the-art algorithms in segmentation of mitochondria in EM images.

Estimation of 3D shape from image orientations.

PubMed

Fleming, Roland W; Holtmann-Rice, Daniel; Bülthoff, Heinrich H

2011-12-20

One of the main functions of vision is to estimate the 3D shape of objects in our environment. Many different visual cues, such as stereopsis, motion parallax, and shading, are thought to be involved. One important cue that remains poorly understood comes from surface texture markings. When a textured surface is slanted in 3D relative to the observer, the surface patterns appear compressed in the retinal image, providing potentially important information about 3D shape. What is not known, however, is how the brain actually measures this information from the retinal image. Here, we explain how the key information could be extracted by populations of cells tuned to different orientations and spatial frequencies, like those found in the primary visual cortex. To test this theory, we created stimuli that selectively stimulate such cell populations, by "smearing" (filtering) images of 2D random noise into specific oriented patterns. We find that the resulting patterns appear vividly 3D, and that increasing the strength of the orientation signals progressively increases the sense of 3D shape, even though the filtering we apply is physically inconsistent with what would occur with a real object. This finding suggests we have isolated key mechanisms used by the brain to estimate shape from texture. Crucially, we also find that adapting the visual system's orientation detectors to orthogonal patterns causes unoriented random noise to look like a specific 3D shape. Together these findings demonstrate a crucial role of orientation detectors in the perception of 3D shape.

How extractive industries affect health: Political economy underpinnings and pathways.

PubMed

Schrecker, Ted; Birn, Anne-Emanuelle; Aguilera, Mariajosé

2018-06-07

A systematic and theoretically informed analysis of how extractive industries affect health outcomes and health inequities is overdue. Informed by the work of Saskia Sassen on "logics of extraction," we adopt an expansive definition of extractive industries to include (for example) large-scale foreign acquisitions of agricultural land for export production. To ground our analysis in concrete place-based evidence, we begin with a brief review of four case examples of major extractive activities. We then analyze the political economy of extractivism, focusing on the societal structures, processes, and relationships of power that drive and enable extraction. Next, we examine how this global order shapes and interacts with politics, institutions, and policies at the state/national level contextualizing extractive activity. Having provided necessary context, we posit a set of pathways that link the global political economy and national politics and institutional practices surrounding extraction to health outcomes and their distribution. These pathways involve both direct health effects, such as toxic work and environmental exposures and assassination of activists, and indirect effects, including sustained impoverishment, water insecurity, and stress-related ailments. We conclude with some reflections on the need for future research on the health and health equity implications of the global extractive order. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Automatic Detection and Recognition of Craters Based on the Spectral Features of Lunar Rocks and Minerals

NASA Astrophysics Data System (ADS)

Ye, L.; Xu, X.; Luan, D.; Jiang, W.; Kang, Z.

2017-07-01

Crater-detection approaches can be divided into four categories: manual recognition, shape-profile fitting algorithms, machine-learning methods and geological information-based analysis using terrain and spectral data. The mainstream method is Shape-profile fitting algorithms. Many scholars throughout the world use the illumination gradient information to fit standard circles by least square method. Although this method has achieved good results, it is difficult to identify the craters with poor "visibility", complex structure and composition. Moreover, the accuracy of recognition is difficult to be improved due to the multiple solutions and noise interference. Aiming at the problem, we propose a method for the automatic extraction of impact craters based on spectral characteristics of the moon rocks and minerals: 1) Under the condition of sunlight, the impact craters are extracted from MI by condition matching and the positions as well as diameters of the craters are obtained. 2) Regolith is spilled while lunar is impacted and one of the elements of lunar regolith is iron. Therefore, incorrectly extracted impact craters can be removed by judging whether the crater contains "non iron" element. 3) Craters which are extracted correctly, are divided into two types: simple type and complex type according to their diameters. 4) Get the information of titanium and match the titanium distribution of the complex craters with normal distribution curve, then calculate the goodness of fit and set the threshold. The complex craters can be divided into two types: normal distribution curve type of titanium and non normal distribution curve type of titanium. We validated our proposed method with MI acquired by SELENE. Experimental results demonstrate that the proposed method has good performance in the test area.

Object-based Encoding in Visual Working Memory: Evidence from Memory-driven Attentional Capture.

PubMed

Gao, Zaifeng; Yu, Shixian; Zhu, Chengfeng; Shui, Rende; Weng, Xuchu; Li, Peng; Shen, Mowei

2016-03-09

Visual working memory (VWM) adopts a specific manner of object-based encoding (OBE) to extract perceptual information: Whenever one feature-dimension is selected for entry into VWM, the others are also extracted. Currently most studies revealing OBE probed an 'irrelevant-change distracting effect', where changes of irrelevant-features dramatically affected the performance of the target feature. However, the existence of irrelevant-feature change may affect participants' processing manner, leading to a false-positive result. The current study conducted a strict examination of OBE in VWM, by probing whether irrelevant-features guided the deployment of attention in visual search. The participants memorized an object's colour yet ignored shape and concurrently performed a visual-search task. They searched for a target line among distractor lines, each embedded within a different object. One object in the search display could match the shape, colour, or both dimensions of the memory item, but this object never contained the target line. Relative to a neutral baseline, where there was no match between the memory and search displays, search time was significantly prolonged in all match conditions, regardless of whether the memory item was displayed for 100 or 1000 ms. These results suggest that task-irrelevant shape was extracted into VWM, supporting OBE in VWM.

Instantaneous Coastline Extraction from LIDAR Point Cloud and High Resolution Remote Sensing Imagery

NASA Astrophysics Data System (ADS)

Li, Y.; Zhoing, L.; Lai, Z.; Gan, Z.

2018-04-01

A new method was proposed for instantaneous waterline extraction in this paper, which combines point cloud geometry features and image spectral characteristics of the coastal zone. The proposed method consists of follow steps: Mean Shift algorithm is used to segment the coastal zone of high resolution remote sensing images into small regions containing semantic information;Region features are extracted by integrating LiDAR data and the surface area of the image; initial waterlines are extracted by α-shape algorithm; a region growing algorithm with is taking into coastline refinement, with a growth rule integrating the intensity and topography of LiDAR data; moothing the coastline. Experiments are conducted to demonstrate the efficiency of the proposed method.

CFD Analysis of Flexible Thermal Protection System Shear Configuration Testing in the LCAT Facility

NASA Technical Reports Server (NTRS)

Ferlemann, Paul G.

2014-01-01

This paper documents results of computational analysis performed after flexible thermal protection system shear configuration testing in the LCAT facility. The primary objectives were to predict the shear force on the sample and the sensitivity of all surface properties to the shape of the sample. Bumps of 0.05, 0.10,and 0.15 inches were created to approximate the shape of some fabric samples during testing. A large amount of information was extracted from the CFD solutions for comparison between runs and also current or future flight simulations.

Automated egg grading system using computer vision: Investigation on weight measure versus shape parameters

NASA Astrophysics Data System (ADS)

Nasir, Ahmad Fakhri Ab; Suhaila Sabarudin, Siti; Majeed, Anwar P. P. Abdul; Ghani, Ahmad Shahrizan Abdul

2018-04-01

Chicken egg is a source of food of high demand by humans. Human operators cannot work perfectly and continuously when conducting egg grading. Instead of an egg grading system using weight measure, an automatic system for egg grading using computer vision (using egg shape parameter) can be used to improve the productivity of egg grading. However, early hypothesis has indicated that more number of egg classes will change when using egg shape parameter compared with using weight measure. This paper presents the comparison of egg classification by the two above-mentioned methods. Firstly, 120 images of chicken eggs of various grades (A–D) produced in Malaysia are captured. Then, the egg images are processed using image pre-processing techniques, such as image cropping, smoothing and segmentation. Thereafter, eight egg shape features, including area, major axis length, minor axis length, volume, diameter and perimeter, are extracted. Lastly, feature selection (information gain ratio) and feature extraction (principal component analysis) are performed using k-nearest neighbour classifier in the classification process. Two methods, namely, supervised learning (using weight measure as graded by egg supplier) and unsupervised learning (using egg shape parameters as graded by ourselves), are conducted to execute the experiment. Clustering results reveal many changes in egg classes after performing shape-based grading. On average, the best recognition results using shape-based grading label is 94.16% while using weight-based label is 44.17%. As conclusion, automated egg grading system using computer vision is better by implementing shape-based features since it uses image meanwhile the weight parameter is more suitable by using weight grading system.

Audio feature extraction using probability distribution function

NASA Astrophysics Data System (ADS)

Suhaib, A.; Wan, Khairunizam; Aziz, Azri A.; Hazry, D.; Razlan, Zuradzman M.; Shahriman A., B.

2015-05-01

Voice recognition has been one of the popular applications in robotic field. It is also known to be recently used for biometric and multimedia information retrieval system. This technology is attained from successive research on audio feature extraction analysis. Probability Distribution Function (PDF) is a statistical method which is usually used as one of the processes in complex feature extraction methods such as GMM and PCA. In this paper, a new method for audio feature extraction is proposed which is by using only PDF as a feature extraction method itself for speech analysis purpose. Certain pre-processing techniques are performed in prior to the proposed feature extraction method. Subsequently, the PDF result values for each frame of sampled voice signals obtained from certain numbers of individuals are plotted. From the experimental results obtained, it can be seen visually from the plotted data that each individuals' voice has comparable PDF values and shapes.

Human action recognition based on point context tensor shape descriptor

NASA Astrophysics Data System (ADS)

Li, Jianjun; Mao, Xia; Chen, Lijiang; Wang, Lan

2017-07-01

Motion trajectory recognition is one of the most important means to determine the identity of a moving object. A compact and discriminative feature representation method can improve the trajectory recognition accuracy. This paper presents an efficient framework for action recognition using a three-dimensional skeleton kinematic joint model. First, we put forward a rotation-scale-translation-invariant shape descriptor based on point context (PC) and the normal vector of hypersurface to jointly characterize local motion and shape information. Meanwhile, an algorithm for extracting the key trajectory based on the confidence coefficient is proposed to reduce the randomness and computational complexity. Second, to decrease the eigenvalue decomposition time complexity, a tensor shape descriptor (TSD) based on PC that can globally capture the spatial layout and temporal order to preserve the spatial information of each frame is proposed. Then, a multilinear projection process is achieved by tensor dynamic time warping to map the TSD to a low-dimensional tensor subspace of the same size. Experimental results show that the proposed shape descriptor is effective and feasible, and the proposed approach obtains considerable performance improvement over the state-of-the-art approaches with respect to accuracy on a public action dataset.

Atypical Balance between Occipital and Fronto-Parietal Activation for Visual Shape Extraction in Dyslexia

PubMed Central

Zhang, Ying; Whitfield-Gabrieli, Susan; Christodoulou, Joanna A.; Gabrieli, John D. E.

2013-01-01

Reading requires the extraction of letter shapes from a complex background of text, and an impairment in visual shape extraction would cause difficulty in reading. To investigate the neural mechanisms of visual shape extraction in dyslexia, we used functional magnetic resonance imaging (fMRI) to examine brain activation while adults with or without dyslexia responded to the change of an arrow’s direction in a complex, relative to a simple, visual background. In comparison to adults with typical reading ability, adults with dyslexia exhibited opposite patterns of atypical activation: decreased activation in occipital visual areas associated with visual perception, and increased activation in frontal and parietal regions associated with visual attention. These findings indicate that dyslexia involves atypical brain organization for fundamental processes of visual shape extraction even when reading is not involved. Overengagement in higher-order association cortices, required to compensate for underengagment in lower-order visual cortices, may result in competition for top-down attentional resources helpful for fluent reading. PMID:23825653

Extracted facial feature of racial closely related faces

NASA Astrophysics Data System (ADS)

Liewchavalit, Chalothorn; Akiba, Masakazu; Kanno, Tsuneo; Nagao, Tomoharu

2010-02-01

Human faces contain a lot of demographic information such as identity, gender, age, race and emotion. Human being can perceive these pieces of information and use it as an important clue in social interaction with other people. Race perception is considered the most delicacy and sensitive parts of face perception. There are many research concerning image-base race recognition, but most of them are focus on major race group such as Caucasoid, Negroid and Mongoloid. This paper focuses on how people classify race of the racial closely related group. As a sample of racial closely related group, we choose Japanese and Thai face to represents difference between Northern and Southern Mongoloid. Three psychological experiment was performed to study the strategies of face perception on race classification. As a result of psychological experiment, it can be suggested that race perception is an ability that can be learn. Eyes and eyebrows are the most attention point and eyes is a significant factor in race perception. The Principal Component Analysis (PCA) was performed to extract facial features of sample race group. Extracted race features of texture and shape were used to synthesize faces. As the result, it can be suggested that racial feature is rely on detailed texture rather than shape feature. This research is a indispensable important fundamental research on the race perception which are essential in the establishment of human-like race recognition system.

Automatic extraction of building boundaries using aerial LiDAR data

NASA Astrophysics Data System (ADS)

Wang, Ruisheng; Hu, Yong; Wu, Huayi; Wang, Jian

2016-01-01

Building extraction is one of the main research topics of the photogrammetry community. This paper presents automatic algorithms for building boundary extractions from aerial LiDAR data. First, segmenting height information generated from LiDAR data, the outer boundaries of aboveground objects are expressed as closed chains of oriented edge pixels. Then, building boundaries are distinguished from nonbuilding ones by evaluating their shapes. The candidate building boundaries are reconstructed as rectangles or regular polygons by applying new algorithms, following the hypothesis verification paradigm. These algorithms include constrained searching in Hough space, enhanced Hough transformation, and the sequential linking technique. The experimental results show that the proposed algorithms successfully extract building boundaries at rates of 97%, 85%, and 92% for three LiDAR datasets with varying scene complexities.

Dendritic cell recognition using template matching based on one-dimensional (1D) Fourier descriptors (FD)

NASA Astrophysics Data System (ADS)

Muhd Suberi, Anis Azwani; Wan Zakaria, Wan Nurshazwani; Tomari, Razali; Lau, Mei Xia

2016-07-01

Identification of Dendritic Cell (DC) particularly in the cancer microenvironment is a unique disclosure since fighting tumor from the harnessing immune system has been a novel treatment under investigation. Nowadays, the staining procedure in sorting DC can affect their viability. In this paper, a computer aided system is proposed for automatic classification of DC in peripheral blood mononuclear cell (PBMC) images. Initially, the images undergo a few steps in preprocessing to remove uneven illumination and artifacts around the cells. In segmentation, morphological operators and Canny edge are implemented to isolate the cell shapes and extract the contours. Following that, information from the contours are extracted based on Fourier descriptors, derived from one dimensional (1D) shape signatures. Eventually, cells are classified as DC by comparing template matching (TM) of established template and target images. The results show that the proposed scheme is reliable and effective to recognize DC.

Personal authentication using hand vein triangulation and knuckle shape.

PubMed

Kumar, Ajay; Prathyusha, K Venkata

2009-09-01

This paper presents a new approach to authenticate individuals using triangulation of hand vein images and simultaneous extraction of knuckle shape information. The proposed method is fully automated and employs palm dorsal hand vein images acquired from the low-cost, near infrared, contactless imaging. The knuckle tips are used as key points for the image normalization and extraction of region of interest. The matching scores are generated in two parallel stages: (i) hierarchical matching score from the four topologies of triangulation in the binarized vein structures and (ii) from the geometrical features consisting of knuckle point perimeter distances in the acquired images. The weighted score level combination from these two matching scores are used to authenticate the individuals. The achieved experimental results from the proposed system using contactless palm dorsal-hand vein images are promising (equal error rate of 1.14%) and suggest more user friendly alternative for user identification.

a Tool for Crowdsourced Building Information Modeling Through Low-Cost Range Camera: Preliminary Demonstration and Potential

NASA Astrophysics Data System (ADS)

Capocchiano, F.; Ravanelli, R.; Crespi, M.

2017-11-01

Within the construction sector, Building Information Models (BIMs) are more and more used thanks to the several benefits that they offer in the design of new buildings and the management of the existing ones. Frequently, however, BIMs are not available for already built constructions, but, at the same time, the range camera technology provides nowadays a cheap, intuitive and effective tool for automatically collecting the 3D geometry of indoor environments. It is thus essential to find new strategies, able to perform the first step of the scan to BIM process, by extracting the geometrical information contained in the 3D models that are so easily collected through the range cameras. In this work, a new algorithm to extract planimetries from the 3D models of rooms acquired by means of a range camera is therefore presented. The algorithm was tested on two rooms, characterized by different shapes and dimensions, whose 3D models were captured with the Occipital Structure SensorTM. The preliminary results are promising: the developed algorithm is able to model effectively the 2D shape of the investigated rooms, with an accuracy level comprised in the range of 5 - 10 cm. It can be potentially used by non-expert users in the first step of the BIM generation, when the building geometry is reconstructed, for collecting crowdsourced indoor information in the frame of BIMs Volunteered Geographic Information (VGI) generation.

Morphological decomposition of 2-D binary shapes into convex polygons: a heuristic algorithm.

PubMed

Xu, J

2001-01-01

In many morphological shape decomposition algorithms, either a shape can only be decomposed into shape components of extremely simple forms or a time consuming search process is employed to determine a decomposition. In this paper, we present a morphological shape decomposition algorithm that decomposes a two-dimensional (2-D) binary shape into a collection of convex polygonal components. A single convex polygonal approximation for a given image is first identified. This first component is determined incrementally by selecting a sequence of basic shape primitives. These shape primitives are chosen based on shape information extracted from the given shape at different scale levels. Additional shape components are identified recursively from the difference image between the given image and the first component. Simple operations are used to repair certain concavities caused by the set difference operation. The resulting hierarchical structure provides descriptions for the given shape at different detail levels. The experiments show that the decomposition results produced by the algorithm seem to be in good agreement with the natural structures of the given shapes. The computational cost of the algorithm is significantly lower than that of an earlier search-based convex decomposition algorithm. Compared to nonconvex decomposition algorithms, our algorithm allows accurate approximations for the given shapes at low coding costs.

Defect images by planar ECT probe of meander-mesh coils

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

Yamada, Sotoshi; Katou, Masaki; Iwahara, Masayoshi

1996-09-01

This paper presents results pertaining to image data obtained from a planar meander-mesh coupled coil type ECT probe. The image data makes it possible to detect not only the existence of a defect but also to extract detailed information regarding the nature of the defect, such as its position, shape, length, and direction. In order to recognize a defect distinctly, the authors have fabricated the high sensitive planar coil which can be used to image a 2-D representation of the ECT signal. The relationships between the image pattern and defect shape are discussed.

Diagnosing Breast Cancer with Microwave Technology: remaining challenges and potential solutions with machine learning.

PubMed

Oliveira, Bárbara L; Godinho, Daniela; O'Halloran, Martin; Glavin, Martin; Jones, Edward; Conceição, Raquel C

2018-05-19

Currently, breast cancer often requires invasive biopsies for diagnosis, motivating researchers to design and develop non-invasive and automated diagnosis systems. Recent microwave breast imaging studies have shown how backscattered signals carry relevant information about the shape of a tumour, and tumour shape is often used with current imaging modalities to assess malignancy. This paper presents a comprehensive analysis of microwave breast diagnosis systems which use machine learning to learn characteristics of benign and malignant tumours. The state-of-the-art, the main challenges still to overcome and potential solutions are outlined. Specifically, this work investigates the benefit of signal pre-processing on diagnostic performance, and proposes a new set of extracted features that capture the tumour shape information embedded in a signal. This work also investigates if a relationship exists between the antenna topology in a microwave system and diagnostic performance. Finally, a careful machine learning validation methodology is implemented to guarantee the robustness of the results and the accuracy of performance evaluation.

Effect of power shape on energy extraction from microbial fuel cell

NASA Astrophysics Data System (ADS)

Alaraj, Muhannad; Feng, Shuo; Roane, Timberley M.; Park, Jae-Do

2017-10-01

Microbial fuel cells (MFCs) generate renewable energy in the form of direct current (DC) power. Harvesting energy from MFCs started with passive components such as resistors and capacitors, then charge pumps were introduced with some more advantages. Power electronics converters were later preferred due to their higher efficiency and controllability; however, they introduce high frequency current ripple due to their high frequency switching. In this paper, the effect of shape of power extraction on MFC performance was investigated using three types of current shapes: continuous, square-wave, and triangular-wave. Simultaneously, chemical parameters, such as pH, dissolved oxygen, electrical conductivity, and redox potential, in the anode chamber were monitored to see how these parameters change with the shape of the electrical power extraction. Results showed that the shape of the extracted current did not have a substantial effect on the MFC life span, output power, and energy extraction, nor on the chemical parameters. The outcome of this study provided insight for the electrical impact by power electronics converters on some microbial and chemical aspects of an MFC system.

The skeletal maturation status estimated by statistical shape analysis: axial images of Japanese cervical vertebra.

PubMed

Shin, S M; Kim, Y-I; Choi, Y-S; Yamaguchi, T; Maki, K; Cho, B-H; Park, S-B

2015-01-01

To evaluate axial cervical vertebral (ACV) shape quantitatively and to build a prediction model for skeletal maturation level using statistical shape analysis for Japanese individuals. The sample included 24 female and 19 male patients with hand-wrist radiographs and CBCT images. Through generalized Procrustes analysis and principal components (PCs) analysis, the meaningful PCs were extracted from each ACV shape and analysed for the estimation regression model. Each ACV shape had meaningful PCs, except for the second axial cervical vertebra. Based on these models, the smallest prediction intervals (PIs) were from the combination of the shape space PCs, age and gender. Overall, the PIs of the male group were smaller than those of the female group. There was no significant correlation between centroid size as a size factor and skeletal maturation level. Our findings suggest that the ACV maturation method, which was applied by statistical shape analysis, could confirm information about skeletal maturation in Japanese individuals as an available quantifier of skeletal maturation and could be as useful a quantitative method as the skeletal maturation index.

The skeletal maturation status estimated by statistical shape analysis: axial images of Japanese cervical vertebra

PubMed Central

Shin, S M; Choi, Y-S; Yamaguchi, T; Maki, K; Cho, B-H; Park, S-B

2015-01-01

Objectives: To evaluate axial cervical vertebral (ACV) shape quantitatively and to build a prediction model for skeletal maturation level using statistical shape analysis for Japanese individuals. Methods: The sample included 24 female and 19 male patients with hand–wrist radiographs and CBCT images. Through generalized Procrustes analysis and principal components (PCs) analysis, the meaningful PCs were extracted from each ACV shape and analysed for the estimation regression model. Results: Each ACV shape had meaningful PCs, except for the second axial cervical vertebra. Based on these models, the smallest prediction intervals (PIs) were from the combination of the shape space PCs, age and gender. Overall, the PIs of the male group were smaller than those of the female group. There was no significant correlation between centroid size as a size factor and skeletal maturation level. Conclusions: Our findings suggest that the ACV maturation method, which was applied by statistical shape analysis, could confirm information about skeletal maturation in Japanese individuals as an available quantifier of skeletal maturation and could be as useful a quantitative method as the skeletal maturation index. PMID:25411713

Thermal feature extraction of servers in a datacenter using thermal image registration

NASA Astrophysics Data System (ADS)

Liu, Hang; Ran, Jian; Xie, Ting; Gao, Shan

2017-09-01

Thermal cameras provide fine-grained thermal information that enhances monitoring and enables automatic thermal management in large datacenters. Recent approaches employing mobile robots or thermal camera networks can already identify the physical locations of hot spots. Other distribution information used to optimize datacenter management can also be obtained automatically using pattern recognition technology. However, most of the features extracted from thermal images, such as shape and gradient, may be affected by changes in the position and direction of the thermal camera. This paper presents a method for extracting the thermal features of a hot spot or a server in a container datacenter. First, thermal and visual images are registered based on textural characteristics extracted from images acquired in datacenters. Then, the thermal distribution of each server is standardized. The features of a hot spot or server extracted from the standard distribution can reduce the impact of camera position and direction. The results of experiments show that image registration is efficient for aligning the corresponding visual and thermal images in the datacenter, and the standardization procedure reduces the impacts of camera position and direction on hot spot or server features.

Human listening studies reveal insights into object features extracted by echolocating dolphins

NASA Astrophysics Data System (ADS)

Delong, Caroline M.; Au, Whitlow W. L.; Roitblat, Herbert L.

2004-05-01

Echolocating dolphins extract object feature information from the acoustic parameters of object echoes. However, little is known about which object features are salient to dolphins or how they extract those features. To gain insight into how dolphins might be extracting feature information, human listeners were presented with echoes from objects used in a dolphin echoic-visual cross-modal matching task. Human participants performed a task similar to the one the dolphin had performed; however, echoic samples consisting of 23-echo trains were presented via headphones. The participants listened to the echoic sample and then visually selected the correct object from among three alternatives. The participants performed as well as or better than the dolphin (M=88.0% correct), and reported using a combination of acoustic cues to extract object features (e.g., loudness, pitch, timbre). Participants frequently reported using the pattern of aural changes in the echoes across the echo train to identify the shape and structure of the objects (e.g., peaks in loudness or pitch). It is likely that dolphins also attend to the pattern of changes across echoes as objects are echolocated from different angles.

Mapping morphological shape as a high-dimensional functional curve

PubMed Central

Fu, Guifang; Huang, Mian; Bo, Wenhao; Hao, Han; Wu, Rongling

2018-01-01

Abstract Detecting how genes regulate biological shape has become a multidisciplinary research interest because of its wide application in many disciplines. Despite its fundamental importance, the challenges of accurately extracting information from an image, statistically modeling the high-dimensional shape and meticulously locating shape quantitative trait loci (QTL) affect the progress of this research. In this article, we propose a novel integrated framework that incorporates shape analysis, statistical curve modeling and genetic mapping to detect significant QTLs regulating variation of biological shape traits. After quantifying morphological shape via a radius centroid contour approach, each shape, as a phenotype, was characterized as a high-dimensional curve, varying as angle θ runs clockwise with the first point starting from angle zero. We then modeled the dynamic trajectories of three mean curves and variation patterns as functions of θ. Our framework led to the detection of a few significant QTLs regulating the variation of leaf shape collected from a natural population of poplar, Populus szechuanica var tibetica. This population, distributed at altitudes 2000–4500 m above sea level, is an evolutionarily important plant species. This is the first work in the quantitative genetic shape mapping area that emphasizes a sense of ‘function’ instead of decomposing the shape into a few discrete principal components, as the majority of shape studies do. PMID:28062411

Mammographic mass classification based on possibility theory

NASA Astrophysics Data System (ADS)

Hmida, Marwa; Hamrouni, Kamel; Solaiman, Basel; Boussetta, Sana

2017-03-01

Shape and margin features are very important for differentiating between benign and malignant masses in mammographic images. In fact, benign masses are usually round and oval and have smooth contours. However, malignant tumors have generally irregular shape and appear lobulated or speculated in margins. This knowledge suffers from imprecision and ambiguity. Therefore, this paper deals with the problem of mass classification by using shape and margin features while taking into account the uncertainty linked to the degree of truth of the available information and the imprecision related to its content. Thus, in this work, we proposed a novel mass classification approach which provides a possibility based representation of the extracted shape features and builds a possibility knowledge basis in order to evaluate the possibility degree of malignancy and benignity for each mass. For experimentation, the MIAS database was used and the classification results show the great performance of our approach in spite of using simple features.

Human action classification using procrustes shape theory

NASA Astrophysics Data System (ADS)

Cho, Wanhyun; Kim, Sangkyoon; Park, Soonyoung; Lee, Myungeun

2015-02-01

In this paper, we propose new method that can classify a human action using Procrustes shape theory. First, we extract a pre-shape configuration vector of landmarks from each frame of an image sequence representing an arbitrary human action, and then we have derived the Procrustes fit vector for pre-shape configuration vector. Second, we extract a set of pre-shape vectors from tanning sample stored at database, and we compute a Procrustes mean shape vector for these preshape vectors. Third, we extract a sequence of the pre-shape vectors from input video, and we project this sequence of pre-shape vectors on the tangent space with respect to the pole taking as a sequence of mean shape vectors corresponding with a target video. And we calculate the Procrustes distance between two sequences of the projection pre-shape vectors on the tangent space and the mean shape vectors. Finally, we classify the input video into the human action class with minimum Procrustes distance. We assess a performance of the proposed method using one public dataset, namely Weizmann human action dataset. Experimental results reveal that the proposed method performs very good on this dataset.

Biologically Inspired Model for Inference of 3D Shape from Texture

PubMed Central

Gomez, Olman; Neumann, Heiko

2016-01-01

A biologically inspired model architecture for inferring 3D shape from texture is proposed. The model is hierarchically organized into modules roughly corresponding to visual cortical areas in the ventral stream. Initial orientation selective filtering decomposes the input into low-level orientation and spatial frequency representations. Grouping of spatially anisotropic orientation responses builds sketch-like representations of surface shape. Gradients in orientation fields and subsequent integration infers local surface geometry and globally consistent 3D depth. From the distributions in orientation responses summed in frequency, an estimate of the tilt and slant of the local surface can be obtained. The model suggests how 3D shape can be inferred from texture patterns and their image appearance in a hierarchically organized processing cascade along the cortical ventral stream. The proposed model integrates oriented texture gradient information that is encoded in distributed maps of orientation-frequency representations. The texture energy gradient information is defined by changes in the grouped summed normalized orientation-frequency response activity extracted from the textured object image. This activity is integrated by directed fields to generate a 3D shape representation of a complex object with depth ordering proportional to the fields output, with higher activity denoting larger distance in relative depth away from the viewer. PMID:27649387

Hierarchical human action recognition around sleeping using obscured posture information

NASA Astrophysics Data System (ADS)

Kudo, Yuta; Sashida, Takehiko; Aoki, Yoshimitsu

2015-04-01

This paper presents a new approach for human action recognition around sleeping with the human body parts locations and the positional relationship between human and sleeping environment. Body parts are estimated from the depth image obtained by a time-of-flight (TOF) sensor using oriented 3D normal vector. Issues in action recognition of sleeping situation are the demand of availability in darkness, and hiding of the human body by duvets. Therefore, the extraction of image features is difficult since color and edge features are obscured by covers. Thus, first in our method, positions of four parts of the body (head, torso, thigh, and lower leg) are estimated by using the shape model of bodily surface constructed by oriented 3D normal vector. This shape model can represent the surface shape of rough body, and is effective in robust posture estimation of the body hidden with duvets. Then, action descriptor is extracted from the position of each body part. The descriptor includes temporal variation of each part of the body and spatial vector of position of the parts and the bed. Furthermore, this paper proposes hierarchical action classes and classifiers to improve the indistinct action classification. Classifiers are composed of two layers, and recognize human action by using the action descriptor. First layer focuses on spatial descriptor and classifies action roughly. Second layer focuses on temporal descriptor and classifies action finely. This approach achieves a robust recognition of obscured human by using the posture information and the hierarchical action recognition.

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

Zare, Bijan; Faramarzi, Mohammad Ali; Sepehrizadeh, Zargham

Highlights: ► Biosynthesis of rod shape tellurium nanoparticles with a hexagonal crystal structure. ► Extraction procedure for isolation of tellurium nanoparticles from Bacillus sp. BZ. ► Extracted tellurium nanoparticles have good bactericidal activity against some bacteria. -- Abstract: In this study, a tellurium-transforming Bacillus sp. BZ was isolated from the Caspian Sea in northern Iran. The isolate was identified by various tests and 16S rDNA analysis, and then used to prepare elemental tellurium nanoparticles. The isolate was subsequently used for the intracellular biosynthesis of elemental tellurium nanoparticles. The biogenic nanoparticles were released by liquid nitrogen and purified by an n-octylmore » alcohol water extraction system. The shape, size, and composition of the extracted nanoparticles were characterized. The transmission electron micrograph showed rod-shaped nanoparticles with dimensions of about 20 nm × 180 nm. The energy dispersive X-ray and X-ray diffraction spectra respectively demonstrated that the extracted nanoparticles consisted of only tellurium and have a hexagonal crystal structure. This is the first study to demonstrate a biological method for synthesizing rod-shaped elemental tellurium by a Bacillus sp., its extraction and its antibacterial activity against different clinical isolates.« less

Regional shape-based feature space for segmenting biomedical images using neural networks

NASA Astrophysics Data System (ADS)

Sundaramoorthy, Gopal; Hoford, John D.; Hoffman, Eric A.

1993-07-01

In biomedical images, structure of interest, particularly the soft tissue structures, such as the heart, airways, bronchial and arterial trees often have grey-scale and textural characteristics similar to other structures in the image, making it difficult to segment them using only gray- scale and texture information. However, these objects can be visually recognized by their unique shapes and sizes. In this paper we discuss, what we believe to be, a novel, simple scheme for extracting features based on regional shapes. To test the effectiveness of these features for image segmentation (classification), we use an artificial neural network and a statistical cluster analysis technique. The proposed shape-based feature extraction algorithm computes regional shape vectors (RSVs) for all pixels that meet a certain threshold criteria. The distance from each such pixel to a boundary is computed in 8 directions (or in 26 directions for a 3-D image). Together, these 8 (or 26) values represent the pixel's (or voxel's) RSV. All RSVs from an image are used to train a multi-layered perceptron neural network which uses these features to 'learn' a suitable classification strategy. To clearly distinguish the desired object from other objects within an image, several examples from inside and outside the desired object are used for training. Several examples are presented to illustrate the strengths and weaknesses of our algorithm. Both synthetic and actual biomedical images are considered. Future extensions to this algorithm are also discussed.

Experience improves feature extraction in Drosophila.

PubMed

Peng, Yueqing; Xi, Wang; Zhang, Wei; Zhang, Ke; Guo, Aike

2007-05-09

Previous exposure to a pattern in the visual scene can enhance subsequent recognition of that pattern in many species from honeybees to humans. However, whether previous experience with a visual feature of an object, such as color or shape, can also facilitate later recognition of that particular feature from multiple visual features is largely unknown. Visual feature extraction is the ability to select the key component from multiple visual features. Using a visual flight simulator, we designed a novel protocol for visual feature extraction to investigate the effects of previous experience on visual reinforcement learning in Drosophila. We found that, after conditioning with a visual feature of objects among combinatorial shape-color features, wild-type flies exhibited poor ability to extract the correct visual feature. However, the ability for visual feature extraction was greatly enhanced in flies trained previously with that visual feature alone. Moreover, we demonstrated that flies might possess the ability to extract the abstract category of "shape" but not a particular shape. Finally, this experience-dependent feature extraction is absent in flies with defective MBs, one of the central brain structures in Drosophila. Our results indicate that previous experience can enhance visual feature extraction in Drosophila and that MBs are required for this experience-dependent visual cognition.

WE-AB-207B-07: Dose Cloud: Generating “Big Data” for Radiation Therapy Treatment Plan Optimization Research

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

Folkerts, MM; University of California San Diego, La Jolla, California; Long, T

Purpose: To provide a tool to generate large sets of realistic virtual patient geometries and beamlet doses for treatment optimization research. This tool enables countless studies exploring the fundamental interplay between patient geometry, objective functions, weight selections, and achievable dose distributions for various algorithms and modalities. Methods: Generating realistic virtual patient geometries requires a small set of real patient data. We developed a normalized patient shape model (PSM) which captures organ and target contours in a correspondence-preserving manner. Using PSM-processed data, we perform principal component analysis (PCA) to extract major modes of variation from the population. These PCA modes canmore » be shared without exposing patient information. The modes are re-combined with different weights to produce sets of realistic virtual patient contours. Because virtual patients lack imaging information, we developed a shape-based dose calculation (SBD) relying on the assumption that the region inside the body contour is water. SBD utilizes a 2D fluence-convolved scatter kernel, derived from Monte Carlo simulations, and can compute both full dose for a given set of fluence maps, or produce a dose matrix (dose per fluence pixel) for many modalities. Combining the shape model with SBD provides the data needed for treatment plan optimization research. Results: We used PSM to capture organ and target contours for 96 prostate cases, extracted the first 20 PCA modes, and generated 2048 virtual patient shapes by randomly sampling mode scores. Nearly half of the shapes were thrown out for failing anatomical checks, the remaining 1124 were used in computing dose matrices via SBD and a standard 7-beam protocol. As a proof of concept, and to generate data for later study, we performed fluence map optimization emphasizing PTV coverage. Conclusions: We successfully developed and tested a tool for creating customizable sets of virtual patients suitable for large-scale radiation therapy optimization research.« less

Radiomics: a new application from established techniques

PubMed Central

Parekh, Vishwa; Jacobs, Michael A.

2016-01-01

The increasing use of biomarkers in cancer have led to the concept of personalized medicine for patients. Personalized medicine provides better diagnosis and treatment options available to clinicians. Radiological imaging techniques provide an opportunity to deliver unique data on different types of tissue. However, obtaining useful information from all radiological data is challenging in the era of “big data”. Recent advances in computational power and the use of genomics have generated a new area of research termed Radiomics. Radiomics is defined as the high throughput extraction of quantitative imaging features or texture (radiomics) from imaging to decode tissue pathology and creating a high dimensional data set for feature extraction. Radiomic features provide information about the gray-scale patterns, inter-pixel relationships. In addition, shape and spectral properties can be extracted within the same regions of interest on radiological images. Moreover, these features can be further used to develop computational models using advanced machine learning algorithms that may serve as a tool for personalized diagnosis and treatment guidance. PMID:28042608

Method for wafer edge profile extraction using optical images obtained in edge defect inspection process

NASA Astrophysics Data System (ADS)

Okamoto, Hiroaki; Sakaguchi, Naoshi; Hayano, Fuminori

2010-03-01

It is becoming increasingly important to monitor wafer edge profiles in the immersion lithography era. A Nikon edge defect inspection tool acquires the circumferential optical images of the wafer edge during its inspection process. Nikon's unique illumination system and optics make it possible to then convert the brightness data of the captured images to quantifiable edge profile information. During this process the wafer's outer shape is also calculated. Test results show that even newly shipped bare wafers may not have a constant shape over 360 degree. In some cases repeated deformations with 90 degree pitch are observed.

Eyeglasses Lens Contour Extraction from Facial Images Using an Efficient Shape Description

PubMed Central

Borza, Diana; Darabant, Adrian Sergiu; Danescu, Radu

2013-01-01

This paper presents a system that automatically extracts the position of the eyeglasses and the accurate shape and size of the frame lenses in facial images. The novelty brought by this paper consists in three key contributions. The first one is an original model for representing the shape of the eyeglasses lens, using Fourier descriptors. The second one is a method for generating the search space starting from a finite, relatively small number of representative lens shapes based on Fourier morphing. Finally, we propose an accurate lens contour extraction algorithm using a multi-stage Monte Carlo sampling technique. Multiple experiments demonstrate the effectiveness of our approach. PMID:24152926

Three-dimensional tracking for efficient fire fighting in complex situations

NASA Astrophysics Data System (ADS)

Akhloufi, Moulay; Rossi, Lucile

2009-05-01

Each year, hundred millions hectares of forests burn causing human and economic losses. For efficient fire fighting, the personnel in the ground need tools permitting the prediction of fire front propagation. In this work, we present a new technique for automatically tracking fire spread in three-dimensional space. The proposed approach uses a stereo system to extract a 3D shape from fire images. A new segmentation technique is proposed and permits the extraction of fire regions in complex unstructured scenes. It works in the visible spectrum and combines information extracted from YUV and RGB color spaces. Unlike other techniques, our algorithm does not require previous knowledge about the scene. The resulting fire regions are classified into different homogenous zones using clustering techniques. Contours are then extracted and a feature detection algorithm is used to detect interest points like local maxima and corners. Extracted points from stereo images are then used to compute the 3D shape of the fire front. The resulting data permits to build the fire volume. The final model is used to compute important spatial and temporal fire characteristics like: spread dynamics, local orientation, heading direction, etc. Tests conducted on the ground show the efficiency of the proposed scheme. This scheme is being integrated with a fire spread mathematical model in order to predict and anticipate the fire behaviour during fire fighting. Also of interest to fire-fighters, is the proposed automatic segmentation technique that can be used in early detection of fire in complex scenes.

Proceedings of the Meeting of the Coordinating Group on Modern Control Theory (4th) Held at Rochester, Michigan on 27-28 October 1982. Part 1

DTIC Science & Technology

1982-10-01

and time-to-go (T60) are provided from the Estimation Algorithm. The gimbal angle commands used in the first two phases are applied to the gimbal...lighting techniques are also used to simplify image understanding or to extract additional information about position, range, or shape of objects in the...motion or firing dis- turbances. Since useful muzzle position and rate information is difficult to obtain, conventional feedback techniques 447 cannot

Detection of exudates in fundus images using a Markovian segmentation model.

PubMed

Harangi, Balazs; Hajdu, Andras

2014-01-01

Diabetic retinopathy (DR) is one of the most common causing of vision loss in developed countries. In early stage of DR, some signs like exudates appear in the retinal images. An automatic screening system must be capable to detect these signs properly so that the treatment of the patients may begin in time. The appearance of exudates shows a rich variety regarding their shape and size making automatic detection more challenging. We propose a way for the automatic segmentation of exudates consisting of a candidate extraction step followed by exact contour detection and region-wise classification. More specifically, we extract possible exudate candidates using grayscale morphology and their proper shape is determined by a Markovian segmentation model considering edge information. Finally, we label the candidates as true or false ones by an optimally adjusted SVM classifier. For testing purposes, we considered the publicly available database DiaretDB1, where the proposed method outperformed several state-of-the-art exudate detectors.

Extraction and textural characterization of above-ground areas from aerial stereo pairs: a quality assessment

NASA Astrophysics Data System (ADS)

Baillard, C.; Dissard, O.; Jamet, O.; Maître, H.

Above-ground analysis is a key point to the reconstruction of urban scenes, but it is a difficult task because of the diversity of the involved objects. We propose a new method to above-ground extraction from an aerial stereo pair, which does not require any assumption about object shape or nature. A Digital Surface Model is first produced by a stereoscopic matching stage preserving discontinuities, and then processed by a region-based Markovian classification algorithm. The produced above-ground areas are finally characterized as man-made or natural according to the grey level information. The quality of the results is assessed and discussed.

Novel face-detection method under various environments

NASA Astrophysics Data System (ADS)

Jing, Min-Quan; Chen, Ling-Hwei

2009-06-01

We propose a method to detect a face with different poses under various environments. On the basis of skin color information, skin regions are first extracted from an input image. Next, the shoulder part is cut out by using shape information and the head part is then identified as a face candidate. For a face candidate, a set of geometric features is applied to determine if it is a profile face. If not, then a set of eyelike rectangles extracted from the face candidate and the lighting distribution are used to determine if the face candidate is a nonprofile face. Experimental results show that the proposed method is robust under a wide range of lighting conditions, different poses, and races. The detection rate for the HHI face database is 93.68%. For the Champion face database, the detection rate is 95.15%.

Automatic Rooftop Extraction in Stereo Imagery Using Distance and Building Shape Regularized Level Set Evolution

NASA Astrophysics Data System (ADS)

Tian, J.; Krauß, T.; d'Angelo, P.

2017-05-01

Automatic rooftop extraction is one of the most challenging problems in remote sensing image analysis. Classical 2D image processing techniques are expensive due to the high amount of features required to locate buildings. This problem can be avoided when 3D information is available. In this paper, we show how to fuse the spectral and height information of stereo imagery to achieve an efficient and robust rooftop extraction. In the first step, the digital terrain model (DTM) and in turn the normalized digital surface model (nDSM) is generated by using a newly step-edge approach. In the second step, the initial building locations and rooftop boundaries are derived by removing the low-level pixels and high-level pixels with higher probability to be trees and shadows. This boundary is then served as the initial level set function, which is further refined to fit the best possible boundaries through distance regularized level-set curve evolution. During the fitting procedure, the edge-based active contour model is adopted and implemented by using the edges indicators extracted from panchromatic image. The performance of the proposed approach is tested by using the WorldView-2 satellite data captured over Munich.

Automatic segmentation of the liver using multi-planar anatomy and deformable surface model in abdominal contrast-enhanced CT images

NASA Astrophysics Data System (ADS)

Jang, Yujin; Hong, Helen; Chung, Jin Wook; Yoon, Young Ho

2012-02-01

We propose an effective technique for the extraction of liver boundary based on multi-planar anatomy and deformable surface model in abdominal contrast-enhanced CT images. Our method is composed of four main steps. First, for extracting an optimal volume circumscribing a liver, lower and side boundaries are defined by positional information of pelvis and rib. An upper boundary is defined by separating the lungs and heart from CT images. Second, for extracting an initial liver volume, optimal liver volume is smoothed by anisotropic diffusion filtering and is segmented using adaptively selected threshold value. Third, for removing neighbor organs from initial liver volume, morphological opening and connected component labeling are applied to multiple planes. Finally, for refining the liver boundaries, deformable surface model is applied to a posterior liver surface and missing left robe in previous step. Then, probability summation map is generated by calculating regional information of the segmented liver in coronal plane, which is used for restoring the inaccurate liver boundaries. Experimental results show that our segmentation method can accurately extract liver boundaries without leakage to neighbor organs in spite of various liver shape and ambiguous boundary.

Hierarchical structures of amorphous solids characterized by persistent homology

PubMed Central

Hiraoka, Yasuaki; Nakamura, Takenobu; Hirata, Akihiko; Escolar, Emerson G.; Matsue, Kaname; Nishiura, Yasumasa

2016-01-01

This article proposes a topological method that extracts hierarchical structures of various amorphous solids. The method is based on the persistence diagram (PD), a mathematical tool for capturing shapes of multiscale data. The input to the PDs is given by an atomic configuration and the output is expressed as 2D histograms. Then, specific distributions such as curves and islands in the PDs identify meaningful shape characteristics of the atomic configuration. Although the method can be applied to a wide variety of disordered systems, it is applied here to silica glass, the Lennard-Jones system, and Cu-Zr metallic glass as standard examples of continuous random network and random packing structures. In silica glass, the method classified the atomic rings as short-range and medium-range orders and unveiled hierarchical ring structures among them. These detailed geometric characterizations clarified a real space origin of the first sharp diffraction peak and also indicated that PDs contain information on elastic response. Even in the Lennard-Jones system and Cu-Zr metallic glass, the hierarchical structures in the atomic configurations were derived in a similar way using PDs, although the glass structures and properties substantially differ from silica glass. These results suggest that the PDs provide a unified method that extracts greater depth of geometric information in amorphous solids than conventional methods. PMID:27298351

Superordinate Shape Classification Using Natural Shape Statistics

ERIC Educational Resources Information Center

Wilder, John; Feldman, Jacob; Singh, Manish

2011-01-01

This paper investigates the classification of shapes into broad natural categories such as "animal" or "leaf". We asked whether such coarse classifications can be achieved by a simple statistical classification of the shape skeleton. We surveyed databases of natural shapes, extracting shape skeletons and tabulating their…

SU-E-I-87: Automated Liver Segmentation Method for CBCT Dataset by Combining Sparse Shape Composition and Probabilistic Atlas Construction

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

Li, Dengwang; Liu, Li; Chen, Jinhu

2014-06-01

Purpose: The aiming of this study was to extract liver structures for daily Cone beam CT (CBCT) images automatically. Methods: Datasets were collected from 50 intravenous contrast planning CT images, which were regarded as training dataset for probabilistic atlas and shape prior model construction. Firstly, probabilistic atlas and shape prior model based on sparse shape composition (SSC) were constructed by iterative deformable registration. Secondly, the artifacts and noise were removed from the daily CBCT image by an edge-preserving filtering using total variation with L1 norm (TV-L1). Furthermore, the initial liver region was obtained by registering the incoming CBCT image withmore » the atlas utilizing edge-preserving deformable registration with multi-scale strategy, and then the initial liver region was converted to surface meshing which was registered with the shape model where the major variation of specific patient was modeled by sparse vectors. At the last stage, the shape and intensity information were incorporated into joint probabilistic model, and finally the liver structure was extracted by maximum a posteriori segmentation.Regarding the construction process, firstly the manually segmented contours were converted into meshes, and then arbitrary patient data was chosen as reference image to register with the rest of training datasets by deformable registration algorithm for constructing probabilistic atlas and prior shape model. To improve the efficiency of proposed method, the initial probabilistic atlas was used as reference image to register with other patient data for iterative construction for removing bias caused by arbitrary selection. Results: The experiment validated the accuracy of the segmentation results quantitatively by comparing with the manually ones. The volumetric overlap percentage between the automatically generated liver contours and the ground truth were on an average 88%–95% for CBCT images. Conclusion: The experiment demonstrated that liver structures of CBCT with artifacts can be extracted accurately for following adaptive radiation therapy. This work is supported by National Natural Science Foundation of China (No. 61201441), Research Fund for Excellent Young and Middle-aged Scientists of Shandong Province (No. BS2012DX038), Project of Shandong Province Higher Educational Science and Technology Program (No. J12LN23), Jinan youth science and technology star (No.20120109)« less

Modeling of efficient light extraction in light-pipes through specular surfaces with elliptical and lineal front shapes

NASA Astrophysics Data System (ADS)

Sánchez-Guerrero, Guillermo E.; Viera-González, Perla M.; Ceballos-Herrera, Daniel E.; Martínez-Guerra, Edgar

2016-09-01

Extraction light in light-pipes with different specular surfaces was analyzed. In the analysis, the impact of the surface shape in all properties of the extracted light in order to obtain an efficient extraction and a uniform illumination using a LED as light source. Also, several parameters of the specular surface to obtain spatial uniformity inside the light-pipe are considered. In this case, the simulation was made for a rectangular light­pipe. One objective of this work is to compare how the front face shape of the specular surface can affect the extraction of light in the lateral face of the light-pipe, only straight and elliptical front faces were used in this work and the comparison between them at different tilts and lengths were made. The main purpose of the front face was extract the light uniformly at the lateral face and this was done by studying simulations on OpticStudio Zemax. The results show how the extraction length is lower in the elliptical front but its total power performs better than the line front.

Extraction of membrane structure in eyeball from MR volumes

NASA Astrophysics Data System (ADS)

Oda, Masahiro; Kin, Taichi; Mori, Kensaku

2017-03-01

This paper presents an accurate extraction method of spherical shaped membrane structures in the eyeball from MR volumes. In ophthalmic surgery, operation field is limited to a small region. Patient specific surgical simulation is useful to reduce complications. Understanding of tissue structure in the eyeball of a patient is required to achieve patient specific surgical simulations. Previous extraction methods of tissue structure in the eyeball use optical coherence tomography (OCT) images. Although OCT images have high resolution, imaging regions are limited to very small. Global structure extraction of the eyeball is difficult from OCT images. We propose an extraction method of spherical shaped membrane structures including the sclerotic coat, choroid, and retina. This method is applied to a T2 weighted MR volume of the head region. MR volume can capture tissue structure of whole eyeball. Because we use MR volumes, out method extracts whole membrane structures in the eyeball. We roughly extract membrane structures by applying a sheet structure enhancement filter. The rough extraction result includes parts of the membrane structures. Then, we apply the Hough transform to extract a sphere structure from the voxels set of the rough extraction result. The Hough transform finds a sphere structure from the rough extraction result. An experimental result using a T2 weighted MR volume of the head region showed that the proposed method can extract spherical shaped membrane structures accurately.

Feature extraction for face recognition via Active Shape Model (ASM) and Active Appearance Model (AAM)

NASA Astrophysics Data System (ADS)

Iqtait, M.; Mohamad, F. S.; Mamat, M.

2018-03-01

Biometric is a pattern recognition system which is used for automatic recognition of persons based on characteristics and features of an individual. Face recognition with high recognition rate is still a challenging task and usually accomplished in three phases consisting of face detection, feature extraction, and expression classification. Precise and strong location of trait point is a complicated and difficult issue in face recognition. Cootes proposed a Multi Resolution Active Shape Models (ASM) algorithm, which could extract specified shape accurately and efficiently. Furthermore, as the improvement of ASM, Active Appearance Models algorithm (AAM) is proposed to extracts both shape and texture of specified object simultaneously. In this paper we give more details about the two algorithms and give the results of experiments, testing their performance on one dataset of faces. We found that the ASM is faster and gains more accurate trait point location than the AAM, but the AAM gains a better match to the texture.

Toward Routine Automatic Pathway Discovery from On-line Scientific Text Abstracts.

PubMed

Ng; Wong

1999-01-01

We are entering a new era of research where the latest scientific discoveries are often first reported online and are readily accessible by scientists worldwide. This rapid electronic dissemination of research breakthroughs has greatly accelerated the current pace in genomics and proteomics research. The race to the discovery of a gene or a drug has now become increasingly dependent on how quickly a scientist can scan through voluminous amount of information available online to construct the relevant picture (such as protein-protein interaction pathways) as it takes shape amongst the rapidly expanding pool of globally accessible biological data (e.g. GENBANK) and scientific literature (e.g. MEDLINE). We describe a prototype system for automatic pathway discovery from on-line text abstracts, combining technologies that (1) retrieve research abstracts from online sources, (2) extract relevant information from the free texts, and (3) present the extracted information graphically and intuitively. Our work demonstrates that this framework allows us to routinely scan online scientific literature for automatic discovery of knowledge, giving modern scientists the necessary competitive edge in managing the information explosion in this electronic age.

Liver segmentation from CT images using a sparse priori statistical shape model (SP-SSM).

PubMed

Wang, Xuehu; Zheng, Yongchang; Gan, Lan; Wang, Xuan; Sang, Xinting; Kong, Xiangfeng; Zhao, Jie

2017-01-01

This study proposes a new liver segmentation method based on a sparse a priori statistical shape model (SP-SSM). First, mark points are selected in the liver a priori model and the original image. Then, the a priori shape and its mark points are used to obtain a dictionary for the liver boundary information. Second, the sparse coefficient is calculated based on the correspondence between mark points in the original image and those in the a priori model, and then the sparse statistical model is established by combining the sparse coefficients and the dictionary. Finally, the intensity energy and boundary energy models are built based on the intensity information and the specific boundary information of the original image. Then, the sparse matching constraint model is established based on the sparse coding theory. These models jointly drive the iterative deformation of the sparse statistical model to approximate and accurately extract the liver boundaries. This method can solve the problems of deformation model initialization and a priori method accuracy using the sparse dictionary. The SP-SSM can achieve a mean overlap error of 4.8% and a mean volume difference of 1.8%, whereas the average symmetric surface distance and the root mean square symmetric surface distance can reach 0.8 mm and 1.4 mm, respectively.

Buildings Change Detection Based on Shape Matching for Multi-Resolution Remote Sensing Imagery

NASA Astrophysics Data System (ADS)

Abdessetar, M.; Zhong, Y.

2017-09-01

Buildings change detection has the ability to quantify the temporal effect, on urban area, for urban evolution study or damage assessment in disaster cases. In this context, changes analysis might involve the utilization of the available satellite images with different resolutions for quick responses. In this paper, to avoid using traditional method with image resampling outcomes and salt-pepper effect, building change detection based on shape matching is proposed for multi-resolution remote sensing images. Since the object's shape can be extracted from remote sensing imagery and the shapes of corresponding objects in multi-scale images are similar, it is practical for detecting buildings changes in multi-scale imagery using shape analysis. Therefore, the proposed methodology can deal with different pixel size for identifying new and demolished buildings in urban area using geometric properties of objects of interest. After rectifying the desired multi-dates and multi-resolutions images, by image to image registration with optimal RMS value, objects based image classification is performed to extract buildings shape from the images. Next, Centroid-Coincident Matching is conducted, on the extracted building shapes, based on the Euclidean distance measurement between shapes centroid (from shape T0 to shape T1 and vice versa), in order to define corresponding building objects. Then, New and Demolished buildings are identified based on the obtained distances those are greater than RMS value (No match in the same location).

Using Simplistic Shape/Surface Models to Predict Brightness in Estimation Filters

NASA Astrophysics Data System (ADS)

Wetterer, C.; Sheppard, D.; Hunt, B.

The prerequisite for using brightness (radiometric flux intensity) measurements in an estimation filter is to have a measurement function that accurately predicts a space objects brightness for variations in the parameters of interest. These parameters include changes in attitude and articulations of particular components (e.g. solar panel east-west offsets to direct sun-tracking). Typically, shape models and bidirectional reflectance distribution functions are combined to provide this forward light curve modeling capability. To achieve precise orbit predictions with the inclusion of shape/surface dependent forces such as radiation pressure, relatively complex and sophisticated modeling is required. Unfortunately, increasing the complexity of the models makes it difficult to estimate all those parameters simultaneously because changes in light curve features can now be explained by variations in a number of different properties. The classic example of this is the connection between the albedo and the area of a surface. If, however, the desire is to extract information about a single and specific parameter or feature from the light curve, a simple shape/surface model could be used. This paper details an example of this where a complex model is used to create simulated light curves, and then a simple model is used in an estimation filter to extract out a particular feature of interest. In order for this to be successful, however, the simple model must be first constructed using training data where the feature of interest is known or at least known to be constant.

Sparse intervertebral fence composition for 3D cervical vertebra segmentation

NASA Astrophysics Data System (ADS)

Liu, Xinxin; Yang, Jian; Song, Shuang; Cong, Weijian; Jiao, Peifeng; Song, Hong; Ai, Danni; Jiang, Yurong; Wang, Yongtian

2018-06-01

Statistical shape models are capable of extracting shape prior information, and are usually utilized to assist the task of segmentation of medical images. However, such models require large training datasets in the case of multi-object structures, and it also is difficult to achieve satisfactory results for complex shapes. This study proposed a novel statistical model for cervical vertebra segmentation, called sparse intervertebral fence composition (SiFC), which can reconstruct the boundary between adjacent vertebrae by modeling intervertebral fences. The complex shape of the cervical spine is replaced by a simple intervertebral fence, which considerably reduces the difficulty of cervical segmentation. The final segmentation results are obtained by using a 3D active contour deformation model without shape constraint, which substantially enhances the recognition capability of the proposed method for objects with complex shapes. The proposed segmentation framework is tested on a dataset with CT images from 20 patients. A quantitative comparison against corresponding reference vertebral segmentation yields an overall mean absolute surface distance of 0.70 mm and a dice similarity index of 95.47% for cervical vertebral segmentation. The experimental results show that the SiFC method achieves competitive cervical vertebral segmentation performances, and completely eliminates inter-process overlap.

Python and computer vision

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

Doak, J. E.; Prasad, Lakshman

2002-01-01

This paper discusses the use of Python in a computer vision (CV) project. We begin by providing background information on the specific approach to CV employed by the project. This includes a brief discussion of Constrained Delaunay Triangulation (CDT), the Chordal Axis Transform (CAT), shape feature extraction and syntactic characterization, and normalization of strings representing objects. (The terms 'object' and 'blob' are used interchangeably, both referring to an entity extracted from an image.) The rest of the paper focuses on the use of Python in three critical areas: (1) interactions with a MySQL database, (2) rapid prototyping of algorithms, andmore » (3) gluing together all components of the project including existing C and C++ modules. For (l), we provide a schema definition and discuss how the various tables interact to represent objects in the database as tree structures. (2) focuses on an algorithm to create a hierarchical representation of an object, given its string representation, and an algorithm to match unknown objects against objects in a database. And finally, (3) discusses the use of Boost Python to interact with the pre-existing C and C++ code that creates the CDTs and CATS, performs shape feature extraction and syntactic characterization, and normalizes object strings. The paper concludes with a vision of the future use of Python for the CV project.« less

Trans-Membrane Area Asymmetry Controls the Shape of Cellular Organelles

PubMed Central

Beznoussenko, Galina V.; Pilyugin, Sergei S.; Geerts, Willie J. C.; Kozlov, Michael M.; Burger, Koert N. J.; Luini, Alberto; Derganc, Jure; Mironov, Alexander A.

2015-01-01

Membrane organelles often have complicated shapes and differ in their volume, surface area and membrane curvature. The ratio between the surface area of the cytosolic and luminal leaflets (trans-membrane area asymmetry (TAA)) determines the membrane curvature within different sites of the organelle. Thus, the shape of the organelle could be critically dependent on TAA. Here, using mathematical modeling and stereological measurements of TAA during fast transformation of organelle shapes, we present evidence that suggests that when organelle volume and surface area are constant, TAA can regulate transformation of the shape of the Golgi apparatus, endosomal multivesicular bodies, and microvilli of brush borders of kidney epithelial cells. Extraction of membrane curvature by small spheres, such as COPI-dependent vesicles within the Golgi (extraction of positive curvature), or by intraluminal vesicles within endosomes (extraction of negative curvature) controls the shape of these organelles. For instance, Golgi tubulation is critically dependent on the fusion of COPI vesicles with Golgi cisternae, and vice versa, for the extraction of membrane curvature into 50–60 nm vesicles, to induce transformation of Golgi tubules into cisternae. Also, formation of intraluminal ultra-small vesicles after fusion of endosomes allows equilibration of their TAA, volume and surface area. Finally, when microvilli of the brush border are broken into vesicles and microvilli fragments, TAA of these membranes remains the same as TAA of the microvilli. Thus, TAA has a significant role in transformation of organelle shape when other factors remain constant. PMID:25761238

Reconstructing the transport history of pebbles on Mars

PubMed Central

Szabó, Tímea; Domokos, Gábor; Grotzinger, John P.; Jerolmack, Douglas J.

2015-01-01

The discovery of remarkably rounded pebbles by the rover Curiosity, within an exhumed alluvial fan complex in Gale Crater, presents some of the most compelling evidence yet for sustained fluvial activity on Mars. While rounding is known to result from abrasion by inter-particle collisions, geologic interpretations of sediment shape have been qualitative. Here we show how quantitative information on the transport distance of river pebbles can be extracted from their shape alone, using a combination of theory, laboratory experiments and terrestrial field data. We determine that the Martian basalt pebbles have been carried tens of kilometres from their source, by bed-load transport on an alluvial fan. In contrast, angular clasts strewn about the surface of the Curiosity traverse are indicative of later emplacement by rock fragmentation processes. The proposed method for decoding transport history from particle shape provides a new tool for terrestrial and planetary sedimentology. PMID:26460507

Microlensing as a possible probe of event-horizon structure in quasars

NASA Astrophysics Data System (ADS)

Tomozeiu, Mihai; Mohammed, Irshad; Rabold, Manuel; Saha, Prasenjit; Wambsganss, Joachim

2018-04-01

In quasars which are lensed by galaxies, the point-like images sometimes show sharp and uncorrelated brightness variations (microlensing). These brightness changes are associated with the innermost region of the quasar passing through a complicated pattern of caustics produced by the stars in the lensing galaxy. In this paper, we study whether the universal properties of optical caustics could enable extraction of shape information about the central engine of quasars. We present a toy model with a crescent-shaped source crossing a fold caustic. The silhouette of a black hole over an accretion disc tends to produce roughly crescent sources. When a crescent-shaped source crosses a fold caustic, the resulting light curve is noticeably different from the case of a circular luminosity profile or Gaussian source. With good enough monitoring data, the crescent parameters, apart from one degeneracy, can be recovered.

Microlensing as a Possible Probe of Event-Horizon Structure in Quasars

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

Tomozeiu, Mihai; Mohammed, Irshad; Rabold, Manuel

In quasars which are lensed by galaxies, the point-like images sometimes show sharp and uncorrelated brightness variations (microlensing). These brightness changes are associated with the innermost region of the quasar passing through a complicated pattern of caustics produced by the stars in the lensing galaxy. In this paper, we study whether the universal properties of optical caustics could enable extraction of shape information about the central engine of quasars. We present a toy model with a crescent-shaped source crossing a fold caustic. The silhouette of a black hole over an accretion disk tends to produce roughly crescent sources. When amore » crescent-shaped source crosses a fold caustic, the resulting light curve is noticeably different from the case of a circular luminosity profile or Gaussian source. With good enough monitoring data, the crescent parameters, apart from one degeneracy, can be recovered.« less

Microlensing as a Possible Probe of Event-Horizon Structure in Quasars

DOE PAGES

Tomozeiu, Mihai; Mohammed, Irshad; Rabold, Manuel; ...

2017-12-08

In quasars which are lensed by galaxies, the point-like images sometimes show sharp and uncorrelated brightness variations (microlensing). These brightness changes are associated with the innermost region of the quasar passing through a complicated pattern of caustics produced by the stars in the lensing galaxy. In this paper, we study whether the universal properties of optical caustics could enable extraction of shape information about the central engine of quasars. We present a toy model with a crescent-shaped source crossing a fold caustic. The silhouette of a black hole over an accretion disk tends to produce roughly crescent sources. When amore » crescent-shaped source crosses a fold caustic, the resulting light curve is noticeably different from the case of a circular luminosity profile or Gaussian source. With good enough monitoring data, the crescent parameters, apart from one degeneracy, can be recovered.« less

An Ecometric Study of Recent Microfossils using High-throughput Imaging

NASA Astrophysics Data System (ADS)

Elder, L. E.; Hull, P. M.; Hsiang, A. Y.; Kahanamoku, S.

2016-02-01

The era of Big Data has ushered in the potential to collect population level information in a manageable time frame. Taxon-free morphological trait analysis, referred to as ecometrics, can be used to examine and compare ecological dynamics between communities with entirely different species compositions. Until recently population level studies of morphology were difficult because of the time intensive task of collecting measurements. To overcome this, we implemented advances in imaging technology and created software to automate measurements. This high-throughput set of methods collects assemblage-scale data, with methods tuned to foraminiferal samples (e.g., light objects on a dark background). Methods include serial focused dark-field microscopy, custom software (Automorph) to batch process images, extract 2D and 3D shape parameters and frames, and implement landmark-free geometric morphometric analyses. Informatics pipelines were created to store, catalog and share images through the Yale Peabody Museum(YPM; peabody.yale.edu). We openly share software and images to enhance future data discovery. In less than a year we have generated over 25TB of high resolution semi 3D images for this initial study. Here, we take the first step towards developing ecometric approaches for open ocean microfossil communities with a calibration study of community shape in recent sediments. We will present an overview of the `shape' of modern planktonic foraminiferal communities from 25 Atlantic core top samples (23 sites in the North and Equatorial Atlantic; 2 sites in the South Atlantic). In total, more than 100,000 microfossils and fragments were imaged from these sites' sediment cores, an unprecedented morphometric sample set. Correlates of community shape, including diversity, temperature, and latitude, will be discussed. These methods have also been applied to images of limpets and fish teeth to date, and have the potential to be used on modern taxa to extract meaningful information on community responses to changing climate.

Infrared and visible images registration with adaptable local-global feature integration for rail inspection

NASA Astrophysics Data System (ADS)

Tang, Chaoqing; Tian, Gui Yun; Chen, Xiaotian; Wu, Jianbo; Li, Kongjing; Meng, Hongying

2017-12-01

Active thermography provides infrared images that contain sub-surface defect information, while visible images only reveal surface information. Mapping infrared information to visible images offers more comprehensive visualization for decision-making in rail inspection. However, the common information for registration is limited due to different modalities in both local and global level. For example, rail track which has low temperature contrast reveals rich details in visible images, but turns blurry in the infrared counterparts. This paper proposes a registration algorithm called Edge-Guided Speeded-Up-Robust-Features (EG-SURF) to address this issue. Rather than sequentially integrating local and global information in matching stage which suffered from buckets effect, this algorithm adaptively integrates local and global information into a descriptor to gather more common information before matching. This adaptability consists of two facets, an adaptable weighting factor between local and global information, and an adaptable main direction accuracy. The local information is extracted using SURF while the global information is represented by shape context from edges. Meanwhile, in shape context generation process, edges are weighted according to local scale and decomposed into bins using a vector decomposition manner to provide more accurate descriptor. The proposed algorithm is qualitatively and quantitatively validated using eddy current pulsed thermography scene in the experiments. In comparison with other algorithms, better performance has been achieved.

How effective are geometric morphometric techniques for assessing functional shape variation? An example from the great ape temporomandibular joint.

PubMed

Terhune, Claire E

2013-08-01

Functional shape analyses have long relied on the use of shape ratios to test biomechanical hypotheses. This method is powerful because of the ease with which results are interpreted, but these techniques fall short in quantifying complex morphologies that may not have a strong biomechanical foundation but may still be functionally informative. In contrast, geometric morphometric methods are continually being adopted for quantifying complex shapes, but they tend to prove inadequate in functional analyses because they have little foundation in an explicit biomechanical framework. The goal of this study was to evaluate the intersection of these two methods using the great ape temporomandibular joint as a case study. Three-dimensional coordinates of glenoid fossa and mandibular condyle shape were collected using a Microscribe digitizer. Linear distances extracted from these landmarks were analyzed using a series of one-way ANOVAs; further, the landmark configurations were analyzed using geometric morphometric techniques. Results suggest that the two methods are broadly similar, although the geometric morphometric data allow for the identification of shape differences among taxa that were not immediately apparent in the univariate analyses. Furthermore, this study suggests several new approaches for translating these shape data into a biomechanical context by adjusting the data using a biomechanically relevant variable. Copyright © 2013 Wiley Periodicals, Inc.

Geologic information from satellite images

NASA Technical Reports Server (NTRS)

Lee, K.; Knepper, D. H.; Sawatzky, D. L.

1974-01-01

Extracting geologic information from ERTS and Skylab/EREP images is best done by a geologist trained in photo-interpretation. The information is at a regional scale, and three basic types are available: rock and soil, geologic structures, and landforms. Discrimination between alluvium and sedimentary or crystalline bedrock, and between units in thick sedimentary sequences is best, primarily because of topographic expression and vegetation differences. Discrimination between crystalline rock types is poor. Folds and fractures are the best displayed geologic features. They are recognizable by topographic expression, drainage patterns, and rock or vegetation tonal patterns. Landforms are easily discriminated by their familiar shapes and patterns. Several examples demonstrate the applicability of satellite images to tectonic analysis and petroleum and mineral exploration.

Population Estimation in Singapore Based on Remote Sensing and Open Data

NASA Astrophysics Data System (ADS)

Guo, H.; Cao, K.; Wang, P.

2017-09-01

Population estimation statistics are widely used in government, commercial and educational sectors for a variety of purposes. With growing emphases on real-time and detailed population information, data users nowadays have switched from traditional census data to more technology-based data source such as LiDAR point cloud and High-Resolution Satellite Imagery. Nevertheless, such data are costly and periodically unavailable. In this paper, the authors use West Coast District, Singapore as a case study to investigate the applicability and effectiveness of using satellite image from Google Earth for extraction of building footprint and population estimation. At the same time, volunteered geographic information (VGI) is also utilized as ancillary data for building footprint extraction. Open data such as Open Street Map OSM could be employed to enhance the extraction process. In view of challenges in building shadow extraction, this paper discusses several methods including buffer, mask and shape index to improve accuracy. It also illustrates population estimation methods based on building height and number of floor estimates. The results show that the accuracy level of housing unit method on population estimation can reach 92.5 %, which is remarkably accurate. This paper thus provides insights into techniques for building extraction and fine-scale population estimation, which will benefit users such as urban planners in terms of policymaking and urban planning of Singapore.

Characterization of green zero-valent iron nanoparticles produced with tree leaf extracts.

PubMed

Machado, S; Pacheco, J G; Nouws, H P A; Albergaria, J T; Delerue-Matos, C

2015-11-15

In the last decades nanotechnology has become increasingly important because it offers indisputable advantages to almost every area of expertise, including environmental remediation. In this area the synthesis of highly reactive nanomaterials (e.g. zero-valent iron nanoparticles, nZVI) is gaining the attention of the scientific community, service providers and other stakeholders. The synthesis of nZVI by the recently developed green bottom-up method is extremely promising. However, the lack of information about the characteristics of the synthetized particles hinders a wider and more extensive application. This work aims to evaluate the characteristics of nZVI synthesized through the green method using leaves from different trees. Considering the requirements of a product for environmental remediation the following characteristics were studied: size, shape, reactivity and agglomeration tendency. The mulberry and pomegranate leaf extracts produced the smallest nZVIs (5-10 nm), the peach, pear and vine leaf extracts produced the most reactive nZVIs while the ones produced with passion fruit, medlar and cherry extracts did not settle at high nZVI concentrations (931 and 266 ppm). Considering all tests, the nZVIs obtained from medlar and vine leaf extracts are the ones that could present better performances in the environmental remediation. The information gathered in this paper will be useful to choose the most appropriate leaf extracts and operational conditions for the application of the green nZVIs in environmental remediation. Copyright © 2015 Elsevier B.V. All rights reserved.

[Lithology feature extraction of CASI hyperspectral data based on fractal signal algorithm].

PubMed

Tang, Chao; Chen, Jian-Ping; Cui, Jing; Wen, Bo-Tao

2014-05-01

Hyperspectral data is characterized by combination of image and spectrum and large data volume dimension reduction is the main research direction. Band selection and feature extraction is the primary method used for this objective. In the present article, the authors tested methods applied for the lithology feature extraction from hyperspectral data. Based on the self-similarity of hyperspectral data, the authors explored the application of fractal algorithm to lithology feature extraction from CASI hyperspectral data. The "carpet method" was corrected and then applied to calculate the fractal value of every pixel in the hyperspectral data. The results show that fractal information highlights the exposed bedrock lithology better than the original hyperspectral data The fractal signal and characterized scale are influenced by the spectral curve shape, the initial scale selection and iteration step. At present, research on the fractal signal of spectral curve is rare, implying the necessity of further quantitative analysis and investigation of its physical implications.

A semi-automatic method for extracting thin line structures in images as rooted tree network

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

Brazzini, Jacopo; Dillard, Scott; Soille, Pierre

2010-01-01

This paper addresses the problem of semi-automatic extraction of line networks in digital images - e.g., road or hydrographic networks in satellite images, blood vessels in medical images, robust. For that purpose, we improve a generic method derived from morphological and hydrological concepts and consisting in minimum cost path estimation and flow simulation. While this approach fully exploits the local contrast and shape of the network, as well as its arborescent nature, we further incorporate local directional information about the structures in the image. Namely, an appropriate anisotropic metric is designed by using both the characteristic features of the targetmore » network and the eigen-decomposition of the gradient structure tensor of the image. Following, the geodesic propagation from a given seed with this metric is combined with hydrological operators for overland flow simulation to extract the line network. The algorithm is demonstrated for the extraction of blood vessels in a retina image and of a river network in a satellite image.« less

A Complete System for Automatic Extraction of Left Ventricular Myocardium From CT Images Using Shape Segmentation and Contour Evolution

PubMed Central

Zhu, Liangjia; Gao, Yi; Appia, Vikram; Yezzi, Anthony; Arepalli, Chesnal; Faber, Tracy; Stillman, Arthur; Tannenbaum, Allen

2014-01-01

The left ventricular myocardium plays a key role in the entire circulation system and an automatic delineation of the myocardium is a prerequisite for most of the subsequent functional analysis. In this paper, we present a complete system for an automatic segmentation of the left ventricular myocardium from cardiac computed tomography (CT) images using the shape information from images to be segmented. The system follows a coarse-to-fine strategy by first localizing the left ventricle and then deforming the myocardial surfaces of the left ventricle to refine the segmentation. In particular, the blood pool of a CT image is extracted and represented as a triangulated surface. Then, the left ventricle is localized as a salient component on this surface using geometric and anatomical characteristics. After that, the myocardial surfaces are initialized from the localization result and evolved by applying forces from the image intensities with a constraint based on the initial myocardial surface locations. The proposed framework has been validated on 34-human and 12-pig CT images, and the robustness and accuracy are demonstrated. PMID:24723531

Segmentation of human face using gradient-based approach

NASA Astrophysics Data System (ADS)

Baskan, Selin; Bulut, M. Mete; Atalay, Volkan

2001-04-01

This paper describes a method for automatic segmentation of facial features such as eyebrows, eyes, nose, mouth and ears in color images. This work is an initial step for wide range of applications based on feature-based approaches, such as face recognition, lip-reading, gender estimation, facial expression analysis, etc. Human face can be characterized by its skin color and nearly elliptical shape. For this purpose, face detection is performed using color and shape information. Uniform illumination is assumed. No restrictions on glasses, make-up, beard, etc. are imposed. Facial features are extracted using the vertically and horizontally oriented gradient projections. The gradient of a minimum with respect to its neighbor maxima gives the boundaries of a facial feature. Each facial feature has a different horizontal characteristic. These characteristics are derived by extensive experimentation with many face images. Using fuzzy set theory, the similarity between the candidate and the feature characteristic under consideration is calculated. Gradient-based method is accompanied by the anthropometrical information, for robustness. Ear detection is performed using contour-based shape descriptors. This method detects the facial features and circumscribes each facial feature with the smallest rectangle possible. AR database is used for testing. The developed method is also suitable for real-time systems.

A new method to extract modal parameters using output-only responses

NASA Astrophysics Data System (ADS)

Kim, Byeong Hwa; Stubbs, Norris; Park, Taehyo

2005-04-01

This work proposes a new output-only modal analysis method to extract mode shapes and natural frequencies of a structure. The proposed method is based on an approach with a single-degree-of-freedom in the time domain. For a set of given mode-isolated signals, the un-damped mode shapes are extracted utilizing the singular value decomposition of the output energy correlation matrix with respect to sensor locations. The natural frequencies are extracted from a noise-free signal that is projected on the estimated modal basis. The proposed method is particularly efficient when a high resolution of mode shape is essential. The accuracy of the method is numerically verified using a set of time histories that are simulated using a finite-element method. The feasibility and practicality of the method are verified using experimental data collected at the newly constructed King Storm Water Bridge in California, United States.

Extraction of object skeletons in multispectral imagery by the orthogonal regression fitting

NASA Astrophysics Data System (ADS)

Palenichka, Roman M.; Zaremba, Marek B.

2003-03-01

Accurate and automatic extraction of skeletal shape of objects of interest from satellite images provides an efficient solution to such image analysis tasks as object detection, object identification, and shape description. The problem of skeletal shape extraction can be effectively solved in three basic steps: intensity clustering (i.e. segmentation) of objects, extraction of a structural graph of the object shape, and refinement of structural graph by the orthogonal regression fitting. The objects of interest are segmented from the background by a clustering transformation of primary features (spectral components) with respect to each pixel. The structural graph is composed of connected skeleton vertices and represents the topology of the skeleton. In the general case, it is a quite rough piecewise-linear representation of object skeletons. The positions of skeleton vertices on the image plane are adjusted by means of the orthogonal regression fitting. It consists of changing positions of existing vertices according to the minimum of the mean orthogonal distances and, eventually, adding new vertices in-between if a given accuracy if not yet satisfied. Vertices of initial piecewise-linear skeletons are extracted by using a multi-scale image relevance function. The relevance function is an image local operator that has local maximums at the centers of the objects of interest.

Shape Adaptive, Robust Iris Feature Extraction from Noisy Iris Images

PubMed Central

Ghodrati, Hamed; Dehghani, Mohammad Javad; Danyali, Habibolah

2013-01-01

In the current iris recognition systems, noise removing step is only used to detect noisy parts of the iris region and features extracted from there will be excluded in matching step. Whereas depending on the filter structure used in feature extraction, the noisy parts may influence relevant features. To the best of our knowledge, the effect of noise factors on feature extraction has not been considered in the previous works. This paper investigates the effect of shape adaptive wavelet transform and shape adaptive Gabor-wavelet for feature extraction on the iris recognition performance. In addition, an effective noise-removing approach is proposed in this paper. The contribution is to detect eyelashes and reflections by calculating appropriate thresholds by a procedure called statistical decision making. The eyelids are segmented by parabolic Hough transform in normalized iris image to decrease computational burden through omitting rotation term. The iris is localized by an accurate and fast algorithm based on coarse-to-fine strategy. The principle of mask code generation is to assign the noisy bits in an iris code in order to exclude them in matching step is presented in details. An experimental result shows that by using the shape adaptive Gabor-wavelet technique there is an improvement on the accuracy of recognition rate. PMID:24696801

Shape adaptive, robust iris feature extraction from noisy iris images.

PubMed

Ghodrati, Hamed; Dehghani, Mohammad Javad; Danyali, Habibolah

2013-10-01

In the current iris recognition systems, noise removing step is only used to detect noisy parts of the iris region and features extracted from there will be excluded in matching step. Whereas depending on the filter structure used in feature extraction, the noisy parts may influence relevant features. To the best of our knowledge, the effect of noise factors on feature extraction has not been considered in the previous works. This paper investigates the effect of shape adaptive wavelet transform and shape adaptive Gabor-wavelet for feature extraction on the iris recognition performance. In addition, an effective noise-removing approach is proposed in this paper. The contribution is to detect eyelashes and reflections by calculating appropriate thresholds by a procedure called statistical decision making. The eyelids are segmented by parabolic Hough transform in normalized iris image to decrease computational burden through omitting rotation term. The iris is localized by an accurate and fast algorithm based on coarse-to-fine strategy. The principle of mask code generation is to assign the noisy bits in an iris code in order to exclude them in matching step is presented in details. An experimental result shows that by using the shape adaptive Gabor-wavelet technique there is an improvement on the accuracy of recognition rate.

VIPAR, a quantitative approach to 3D histopathology applied to lymphatic malformations

PubMed Central

Hägerling, René; Drees, Dominik; Scherzinger, Aaron; Dierkes, Cathrin; Martin-Almedina, Silvia; Butz, Stefan; Gordon, Kristiana; Schäfers, Michael; Hinrichs, Klaus; Vestweber, Dietmar; Goerge, Tobias; Mansour, Sahar; Mortimer, Peter S.

2017-01-01

BACKGROUND. Lack of investigatory and diagnostic tools has been a major contributing factor to the failure to mechanistically understand lymphedema and other lymphatic disorders in order to develop effective drug and surgical therapies. One difficulty has been understanding the true changes in lymph vessel pathology from standard 2D tissue sections. METHODS. VIPAR (volume information-based histopathological analysis by 3D reconstruction and data extraction), a light-sheet microscopy–based approach for the analysis of tissue biopsies, is based on digital reconstruction and visualization of microscopic image stacks. VIPAR allows semiautomated segmentation of the vasculature and subsequent nonbiased extraction of characteristic vessel shape and connectivity parameters. We applied VIPAR to analyze biopsies from healthy lymphedematous and lymphangiomatous skin. RESULTS. Digital 3D reconstruction provided a directly visually interpretable, comprehensive representation of the lymphatic and blood vessels in the analyzed tissue volumes. The most conspicuous features were disrupted lymphatic vessels in lymphedematous skin and a hyperplasia (4.36-fold lymphatic vessel volume increase) in the lymphangiomatous skin. Both abnormalities were detected by the connectivity analysis based on extracted vessel shape and structure data. The quantitative evaluation of extracted data revealed a significant reduction of lymphatic segment length (51.3% and 54.2%) and straightness (89.2% and 83.7%) for lymphedematous and lymphangiomatous skin, respectively. Blood vessel length was significantly increased in the lymphangiomatous sample (239.3%). CONCLUSION. VIPAR is a volume-based tissue reconstruction data extraction and analysis approach that successfully distinguished healthy from lymphedematous and lymphangiomatous skin. Its application is not limited to the vascular systems or skin. FUNDING. Max Planck Society, DFG (SFB 656), and Cells-in-Motion Cluster of Excellence EXC 1003. PMID:28814672

VIPAR, a quantitative approach to 3D histopathology applied to lymphatic malformations.

PubMed

Hägerling, René; Drees, Dominik; Scherzinger, Aaron; Dierkes, Cathrin; Martin-Almedina, Silvia; Butz, Stefan; Gordon, Kristiana; Schäfers, Michael; Hinrichs, Klaus; Ostergaard, Pia; Vestweber, Dietmar; Goerge, Tobias; Mansour, Sahar; Jiang, Xiaoyi; Mortimer, Peter S; Kiefer, Friedemann

2017-08-17

Lack of investigatory and diagnostic tools has been a major contributing factor to the failure to mechanistically understand lymphedema and other lymphatic disorders in order to develop effective drug and surgical therapies. One difficulty has been understanding the true changes in lymph vessel pathology from standard 2D tissue sections. VIPAR (volume information-based histopathological analysis by 3D reconstruction and data extraction), a light-sheet microscopy-based approach for the analysis of tissue biopsies, is based on digital reconstruction and visualization of microscopic image stacks. VIPAR allows semiautomated segmentation of the vasculature and subsequent nonbiased extraction of characteristic vessel shape and connectivity parameters. We applied VIPAR to analyze biopsies from healthy lymphedematous and lymphangiomatous skin. Digital 3D reconstruction provided a directly visually interpretable, comprehensive representation of the lymphatic and blood vessels in the analyzed tissue volumes. The most conspicuous features were disrupted lymphatic vessels in lymphedematous skin and a hyperplasia (4.36-fold lymphatic vessel volume increase) in the lymphangiomatous skin. Both abnormalities were detected by the connectivity analysis based on extracted vessel shape and structure data. The quantitative evaluation of extracted data revealed a significant reduction of lymphatic segment length (51.3% and 54.2%) and straightness (89.2% and 83.7%) for lymphedematous and lymphangiomatous skin, respectively. Blood vessel length was significantly increased in the lymphangiomatous sample (239.3%). VIPAR is a volume-based tissue reconstruction data extraction and analysis approach that successfully distinguished healthy from lymphedematous and lymphangiomatous skin. Its application is not limited to the vascular systems or skin. Max Planck Society, DFG (SFB 656), and Cells-in-Motion Cluster of Excellence EXC 1003.

Hierarchical graph-based segmentation for extracting road networks from high-resolution satellite images

NASA Astrophysics Data System (ADS)

Alshehhi, Rasha; Marpu, Prashanth Reddy

2017-04-01

Extraction of road networks in urban areas from remotely sensed imagery plays an important role in many urban applications (e.g. road navigation, geometric correction of urban remote sensing images, updating geographic information systems, etc.). It is normally difficult to accurately differentiate road from its background due to the complex geometry of the buildings and the acquisition geometry of the sensor. In this paper, we present a new method for extracting roads from high-resolution imagery based on hierarchical graph-based image segmentation. The proposed method consists of: 1. Extracting features (e.g., using Gabor and morphological filtering) to enhance the contrast between road and non-road pixels, 2. Graph-based segmentation consisting of (i) Constructing a graph representation of the image based on initial segmentation and (ii) Hierarchical merging and splitting of image segments based on color and shape features, and 3. Post-processing to remove irregularities in the extracted road segments. Experiments are conducted on three challenging datasets of high-resolution images to demonstrate the proposed method and compare with other similar approaches. The results demonstrate the validity and superior performance of the proposed method for road extraction in urban areas.

Reconstructing the Curve-Skeletons of 3D Shapes Using the Visual Hull.

PubMed

Livesu, Marco; Guggeri, Fabio; Scateni, Riccardo

2012-11-01

Curve-skeletons are the most important descriptors for shapes, capable of capturing in a synthetic manner the most relevant features. They are useful for many different applications: from shape matching and retrieval, to medical imaging, to animation. This has led, over the years, to the development of several different techniques for extraction, each trying to comply with specific goals. We propose a novel technique which stems from the intuition of reproducing what a human being does to deduce the shape of an object holding it in his or her hand and rotating. To accomplish this, we use the formal definitions of epipolar geometry and visual hull. We show how it is possible to infer the curve-skeleton of a broad class of 3D shapes, along with an estimation of the radii of the maximal inscribed balls, by gathering information about the medial axes of their projections on the image planes of the stereographic vision. It is definitely worth to point out that our method works indifferently on (even unoriented) polygonal meshes, voxel models, and point clouds. Moreover, it is insensitive to noise, pose-invariant, resolution-invariant, and robust when applied to incomplete data sets.

Arbitrarily shaped high-coherence electron bunches from cold atoms

NASA Astrophysics Data System (ADS)

McCulloch, A. J.; Sheludko, D. V.; Saliba, S. D.; Bell, S. C.; Junker, M.; Nugent, K. A.; Scholten, R. E.

2011-10-01

Ultrafast electron diffractive imaging of nanoscale objects such as biological molecules and defects in solid-state devices provides crucial information on structure and dynamic processes: for example, determination of the form and function of membrane proteins, vital for many key goals in modern biological science, including rational drug design. High brightness and high coherence are required to achieve the necessary spatial and temporal resolution, but have been limited by the thermal nature of conventional electron sources and by divergence due to repulsive interactions between the electrons, known as the Coulomb explosion. It has been shown that, if the electrons are shaped into ellipsoidal bunches with uniform density, the Coulomb explosion can be reversed using conventional optics, to deliver the maximum possible brightness at the target. Here we demonstrate arbitrary and real-time control of the shape of cold electron bunches extracted from laser-cooled atoms. The ability to dynamically shape the electron source itself and to observe this shape in the propagated electron bunch provides a remarkable experimental demonstration of the intrinsically high spatial coherence of a cold-atom electron source, and the potential for alleviation of electron-source brightness limitations due to Coulomb explosion.

View subspaces for indexing and retrieval of 3D models

NASA Astrophysics Data System (ADS)

Dutagaci, Helin; Godil, Afzal; Sankur, Bülent; Yemez, Yücel

2010-02-01

View-based indexing schemes for 3D object retrieval are gaining popularity since they provide good retrieval results. These schemes are coherent with the theory that humans recognize objects based on their 2D appearances. The viewbased techniques also allow users to search with various queries such as binary images, range images and even 2D sketches. The previous view-based techniques use classical 2D shape descriptors such as Fourier invariants, Zernike moments, Scale Invariant Feature Transform-based local features and 2D Digital Fourier Transform coefficients. These methods describe each object independent of others. In this work, we explore data driven subspace models, such as Principal Component Analysis, Independent Component Analysis and Nonnegative Matrix Factorization to describe the shape information of the views. We treat the depth images obtained from various points of the view sphere as 2D intensity images and train a subspace to extract the inherent structure of the views within a database. We also show the benefit of categorizing shapes according to their eigenvalue spread. Both the shape categorization and data-driven feature set conjectures are tested on the PSB database and compared with the competitor view-based 3D shape retrieval algorithms.

3D face analysis by using Mesh-LBP feature

NASA Astrophysics Data System (ADS)

Wang, Haoyu; Yang, Fumeng; Zhang, Yuming; Wu, Congzhong

2017-11-01

Objective: Face Recognition is one of the widely application of image processing. Corresponding two-dimensional limitations, such as the pose and illumination changes, to a certain extent restricted its accurate rate and further development. How to overcome the pose and illumination changes and the effects of self-occlusion is the research hotspot and difficulty, also attracting more and more domestic and foreign experts and scholars to study it. 3D face recognition fusing shape and texture descriptors has become a very promising research direction. Method: Our paper presents a 3D point cloud based on mesh local binary pattern grid (Mesh-LBP), then feature extraction for 3D face recognition by fusing shape and texture descriptors. 3D Mesh-LBP not only retains the integrity of the 3D geometry, is also reduces the need for recognition process of normalization steps, because the triangle Mesh-LBP descriptor is calculated on 3D grid. On the other hand, in view of multi-modal consistency in face recognition advantage, construction of LBP can fusing shape and texture information on Triangular Mesh. In this paper, some of the operators used to extract Mesh-LBP, Such as the normal vectors of the triangle each face and vertex, the gaussian curvature, the mean curvature, laplace operator and so on. Conclusion: First, Kinect devices obtain 3D point cloud face, after the pretreatment and normalization, then transform it into triangular grid, grid local binary pattern feature extraction from face key significant parts of face. For each local face, calculate its Mesh-LBP feature with Gaussian curvature, mean curvature laplace operator and so on. Experiments on the our research database, change the method is robust and high recognition accuracy.

Layout pattern analysis using the Voronoi diagram of line segments

NASA Astrophysics Data System (ADS)

Dey, Sandeep Kumar; Cheilaris, Panagiotis; Gabrani, Maria; Papadopoulou, Evanthia

2016-01-01

Early identification of problematic patterns in very large scale integration (VLSI) designs is of great value as the lithographic simulation tools face significant timing challenges. To reduce the processing time, such a tool selects only a fraction of possible patterns which have a probable area of failure, with the risk of missing some problematic patterns. We introduce a fast method to automatically extract patterns based on their structure and context, using the Voronoi diagram of line-segments as derived from the edges of VLSI design shapes. Designers put line segments around the problematic locations in patterns called "gauges," along which the critical distance is measured. The gauge center is the midpoint of a gauge. We first use the Voronoi diagram of VLSI shapes to identify possible problematic locations, represented as gauge centers. Then we use the derived locations to extract windows containing the problematic patterns from the design layout. The problematic locations are prioritized by the shape and proximity information of the design polygons. We perform experiments for pattern selection in a portion of a 22-nm random logic design layout. The design layout had 38,584 design polygons (consisting of 199,946 line segments) on layer Mx, and 7079 markers generated by an optical rule checker (ORC) tool. The optical rules specify requirements for printing circuits with minimum dimension. Markers are the locations of some optical rule violations in the layout. We verify our approach by comparing the coverage of our extracted patterns to the ORC-generated markers. We further derive a similarity measure between patterns and between layouts. The similarity measure helps to identify a set of representative gauges that reduces the number of patterns for analysis.

An Effective 3D Shape Descriptor for Object Recognition with RGB-D Sensors

PubMed Central

Liu, Zhong; Zhao, Changchen; Wu, Xingming; Chen, Weihai

2017-01-01

RGB-D sensors have been widely used in various areas of computer vision and graphics. A good descriptor will effectively improve the performance of operation. This article further analyzes the recognition performance of shape features extracted from multi-modality source data using RGB-D sensors. A hybrid shape descriptor is proposed as a representation of objects for recognition. We first extracted five 2D shape features from contour-based images and five 3D shape features over point cloud data to capture the global and local shape characteristics of an object. The recognition performance was tested for category recognition and instance recognition. Experimental results show that the proposed shape descriptor outperforms several common global-to-global shape descriptors and is comparable to some partial-to-global shape descriptors that achieved the best accuracies in category and instance recognition. Contribution of partial features and computational complexity were also analyzed. The results indicate that the proposed shape features are strong cues for object recognition and can be combined with other features to boost accuracy. PMID:28245553

Quantitative, simultaneous, and collinear eye-tracked, high dynamic range optical coherence tomography at 850 and 1060 nm

NASA Astrophysics Data System (ADS)

Mooser, Matthias; Burri, Christian; Stoller, Markus; Luggen, David; Peyer, Michael; Arnold, Patrik; Meier, Christoph; Považay, Boris

2017-07-01

Ocular optical coherence tomography at the wavelengths ranges of 850 and 1060 nm have been integrated with a confocal scanning laser ophthalmoscope eye-tracker as a clinical commercial-class system. Collinear optics enables an exact overlap of the different channels to produce precisely overlapping depth-scans for evaluating the similarities and differences between the wavelengths to extract additional physiologic information. A reliable segmentation algorithm utilizing Graphcuts has been implemented and applied to automatically extract retinal and choroidal shape in cross-sections and volumes. The device has been tested in normals and pathologies including a cross-sectional and longitudinal study of myopia progress and control with a duplicate instrument in Asian children.

Information Extraction of Tourist Geological Resources Based on 3d Visualization Remote Sensing Image

NASA Astrophysics Data System (ADS)

Wang, X.

2018-04-01

Tourism geological resources are of high value in admiration, scientific research and universal education, which need to be protected and rationally utilized. In the past, most of the remote sensing investigations of tourism geological resources used two-dimensional remote sensing interpretation method, which made it difficult for some geological heritages to be interpreted and led to the omission of some information. This aim of this paper is to assess the value of a method using the three-dimensional visual remote sensing image to extract information of geological heritages. skyline software system is applied to fuse the 0.36 m aerial images and 5m interval DEM to establish the digital earth model. Based on the three-dimensional shape, color tone, shadow, texture and other image features, the distribution of tourism geological resources in Shandong Province and the location of geological heritage sites were obtained, such as geological structure, DaiGu landform, granite landform, Volcanic landform, sandy landform, Waterscapes, etc. The results show that using this method for remote sensing interpretation is highly recognizable, making the interpretation more accurate and comprehensive.

Disciplinary power and the process of training informal carers on stroke units.

PubMed

Sadler, Euan; Hawkins, Rebecca; Clarke, David J; Godfrey, Mary; Dickerson, Josie; McKevitt, Christopher

2018-01-01

This article examines the process of training informal carers on stroke units using the lens of power. Care is usually assumed as a kinship obligation but the state has long had an interest in framing the carer and caring work. Training carers in healthcare settings raises questions about the power of the state and healthcare professionals as its agents to shape expectations and practices related to the caring role. Drawing on Foucault's notion of disciplinary power, we show how disciplinary forms of power exercised in interactions between healthcare professionals and carers shape the engagement and resistance of carers in the process of training. Interview and observational field note extracts are drawn from a multi-sited study of a training programme on stroke units targeting family carers of people with stroke to consider the consequences of subjecting caring to this intervention. We found that the process of training informal carers on stroke units was not simply a matter of transferring skills from professional to lay person, but entailed disciplinary forms of power intended to shape the conduct of the carer. We interrogate the extent to which a specific kind of carer is produced through such an approach, and the wider implications for the participation of carers in training in healthcare settings and the empowerment of carers. © 2017 Foundation for the Sociology of Health & Illness.

Development of Γ-ray tracking detectors

DOE PAGES

Lieder, R. M.; Gast, W.; Jäger, H. M.; ...

2001-12-01

The next generation of 4π arrays for high-precision γ-ray spectroscopy AGATA will consist of γ-ray tracking detectors. They represent high-fold segmented Ge detectors and a front-end electronics, based on digital signal processing techniques, which allows to extract energy, timing and spatial information on the interactions of a γ-ray in the Ge detector by pulse shape analysis of its signals. Utilizing the information on the positions of the interaction points and the energies released at each point the tracks of the γ-rays in a Ge shell can be reconstructed in three dimensions on the basis of the Compton-scattering formula.

Drop shape visualization and contact angle measurement on curved surfaces.

PubMed

Guilizzoni, Manfredo

2011-12-01

The shape and contact angles of drops on curved surfaces is experimentally investigated. Image processing, spline fitting and numerical integration are used to extract the drop contour in a number of cross-sections. The three-dimensional surfaces which describe the surface-air and drop-air interfaces can be visualized and a simple procedure to determine the equilibrium contact angle starting from measurements on curved surfaces is proposed. Contact angles on flat surfaces serve as a reference term and a procedure to measure them is proposed. Such procedure is not as accurate as the axisymmetric drop shape analysis algorithms, but it has the advantage of requiring only a side view of the drop-surface couple and no further information. It can therefore be used also for fluids with unknown surface tension and there is no need to measure the drop volume. Examples of application of the proposed techniques for distilled water drops on gemstones confirm that they can be useful for drop shape analysis and contact angle measurement on three-dimensional sculptured surfaces. Copyright © 2011 Elsevier Inc. All rights reserved.

Case study of 3D fingerprints applications

PubMed Central

Liu, Feng; Liang, Jinrong; Shen, Linlin; Yang, Meng; Zhang, David; Lai, Zhihui

2017-01-01

Human fingers are 3D objects. More information will be provided if three dimensional (3D) fingerprints are available compared with two dimensional (2D) fingerprints. Thus, this paper firstly collected 3D finger point cloud data by Structured-light Illumination method. Additional features from 3D fingerprint images are then studied and extracted. The applications of these features are finally discussed. A series of experiments are conducted to demonstrate the helpfulness of 3D information to fingerprint recognition. Results show that a quick alignment can be easily implemented under the guidance of 3D finger shape feature even though this feature does not work for fingerprint recognition directly. The newly defined distinctive 3D shape ridge feature can be used for personal authentication with Equal Error Rate (EER) of ~8.3%. Also, it is helpful to remove false core point. Furthermore, a promising of EER ~1.3% is realized by combining this feature with 2D features for fingerprint recognition which indicates the prospect of 3D fingerprint recognition. PMID:28399141

Neuronize: a tool for building realistic neuronal cell morphologies

PubMed Central

Brito, Juan P.; Mata, Susana; Bayona, Sofia; Pastor, Luis; DeFelipe, Javier; Benavides-Piccione, Ruth

2013-01-01

This study presents a tool, Neuronize, for building realistic three-dimensional models of neuronal cells from the morphological information extracted through computer-aided tracing applications. Neuronize consists of a set of methods designed to build 3D neural meshes that approximate the cell membrane at different resolution levels, allowing a balance to be reached between the complexity and the quality of the final model. The main contribution of the present study is the proposal of a novel approach to build a realistic and accurate 3D shape of the soma from the incomplete information stored in the digitally traced neuron, which usually consists of a 2D cell body contour. This technique is based on the deformation of an initial shape driven by the position and thickness of the first order dendrites. The addition of a set of spines along the dendrites completes the model, building a final 3D neuronal cell suitable for its visualization in a wide range of 3D environments. PMID:23761740

Case study of 3D fingerprints applications.

PubMed

Liu, Feng; Liang, Jinrong; Shen, Linlin; Yang, Meng; Zhang, David; Lai, Zhihui

2017-01-01

Human fingers are 3D objects. More information will be provided if three dimensional (3D) fingerprints are available compared with two dimensional (2D) fingerprints. Thus, this paper firstly collected 3D finger point cloud data by Structured-light Illumination method. Additional features from 3D fingerprint images are then studied and extracted. The applications of these features are finally discussed. A series of experiments are conducted to demonstrate the helpfulness of 3D information to fingerprint recognition. Results show that a quick alignment can be easily implemented under the guidance of 3D finger shape feature even though this feature does not work for fingerprint recognition directly. The newly defined distinctive 3D shape ridge feature can be used for personal authentication with Equal Error Rate (EER) of ~8.3%. Also, it is helpful to remove false core point. Furthermore, a promising of EER ~1.3% is realized by combining this feature with 2D features for fingerprint recognition which indicates the prospect of 3D fingerprint recognition.

Neuronize: a tool for building realistic neuronal cell morphologies.

PubMed

Brito, Juan P; Mata, Susana; Bayona, Sofia; Pastor, Luis; Defelipe, Javier; Benavides-Piccione, Ruth

2013-01-01

This study presents a tool, Neuronize, for building realistic three-dimensional models of neuronal cells from the morphological information extracted through computer-aided tracing applications. Neuronize consists of a set of methods designed to build 3D neural meshes that approximate the cell membrane at different resolution levels, allowing a balance to be reached between the complexity and the quality of the final model. The main contribution of the present study is the proposal of a novel approach to build a realistic and accurate 3D shape of the soma from the incomplete information stored in the digitally traced neuron, which usually consists of a 2D cell body contour. This technique is based on the deformation of an initial shape driven by the position and thickness of the first order dendrites. The addition of a set of spines along the dendrites completes the model, building a final 3D neuronal cell suitable for its visualization in a wide range of 3D environments.

Extracting a shape function for a signal with intra-wave frequency modulation.

PubMed

Hou, Thomas Y; Shi, Zuoqiang

2016-04-13

In this paper, we develop an effective and robust adaptive time-frequency analysis method for signals with intra-wave frequency modulation. To handle this kind of signals effectively, we generalize our data-driven time-frequency analysis by using a shape function to describe the intra-wave frequency modulation. The idea of using a shape function in time-frequency analysis was first proposed by Wu (Wu 2013 Appl. Comput. Harmon. Anal. 35, 181-199. (doi:10.1016/j.acha.2012.08.008)). A shape function could be any smooth 2π-periodic function. Based on this model, we propose to solve an optimization problem to extract the shape function. By exploring the fact that the shape function is a periodic function with respect to its phase function, we can identify certain low-rank structure of the signal. This low-rank structure enables us to extract the shape function from the signal. Once the shape function is obtained, the instantaneous frequency with intra-wave modulation can be recovered from the shape function. We demonstrate the robustness and efficiency of our method by applying it to several synthetic and real signals. One important observation is that this approach is very stable to noise perturbation. By using the shape function approach, we can capture the intra-wave frequency modulation very well even for noise-polluted signals. In comparison, existing methods such as empirical mode decomposition/ensemble empirical mode decomposition seem to have difficulty in capturing the intra-wave modulation when the signal is polluted by noise. © 2016 The Author(s).

Microbial phenomics information extractor (MicroPIE): a natural language processing tool for the automated acquisition of prokaryotic phenotypic characters from text sources.

PubMed

Mao, Jin; Moore, Lisa R; Blank, Carrine E; Wu, Elvis Hsin-Hui; Ackerman, Marcia; Ranade, Sonali; Cui, Hong

2016-12-13

The large-scale analysis of phenomic data (i.e., full phenotypic traits of an organism, such as shape, metabolic substrates, and growth conditions) in microbial bioinformatics has been hampered by the lack of tools to rapidly and accurately extract phenotypic data from existing legacy text in the field of microbiology. To quickly obtain knowledge on the distribution and evolution of microbial traits, an information extraction system needed to be developed to extract phenotypic characters from large numbers of taxonomic descriptions so they can be used as input to existing phylogenetic analysis software packages. We report the development and evaluation of Microbial Phenomics Information Extractor (MicroPIE, version 0.1.0). MicroPIE is a natural language processing application that uses a robust supervised classification algorithm (Support Vector Machine) to identify characters from sentences in prokaryotic taxonomic descriptions, followed by a combination of algorithms applying linguistic rules with groups of known terms to extract characters as well as character states. The input to MicroPIE is a set of taxonomic descriptions (clean text). The output is a taxon-by-character matrix-with taxa in the rows and a set of 42 pre-defined characters (e.g., optimum growth temperature) in the columns. The performance of MicroPIE was evaluated against a gold standard matrix and another student-made matrix. Results show that, compared to the gold standard, MicroPIE extracted 21 characters (50%) with a Relaxed F1 score > 0.80 and 16 characters (38%) with Relaxed F1 scores ranging between 0.50 and 0.80. Inclusion of a character prediction component (SVM) improved the overall performance of MicroPIE, notably the precision. Evaluated against the same gold standard, MicroPIE performed significantly better than the undergraduate students. MicroPIE is a promising new tool for the rapid and efficient extraction of phenotypic character information from prokaryotic taxonomic descriptions. However, further development, including incorporation of ontologies, will be necessary to improve the performance of the extraction for some character types.

Extracting contours of oval-shaped objects by Hough transform and minimal path algorithms

NASA Astrophysics Data System (ADS)

Tleis, Mohamed; Verbeek, Fons J.

2014-04-01

Circular and oval-like objects are very common in cell and micro biology. These objects need to be analyzed, and to that end, digitized images from the microscope are used so as to come to an automated analysis pipeline. It is essential to detect all the objects in an image as well as to extract the exact contour of each individual object. In this manner it becomes possible to perform measurements on these objects, i.e. shape and texture features. Our measurement objective is achieved by probing contour detection through dynamic programming. In this paper we describe a method that uses Hough transform and two minimal path algorithms to detect contours of (ovoid-like) objects. These algorithms are based on an existing grey-weighted distance transform and a new algorithm to extract the circular shortest path in an image. The methods are tested on an artificial dataset of a 1000 images, with an F1-score of 0.972. In a case study with yeast cells, contours from our methods were compared with another solution using Pratt's figure of merit. Results indicate that our methods were more precise based on a comparison with a ground-truth dataset. As far as yeast cells are concerned, the segmentation and measurement results enable, in future work, to retrieve information from different developmental stages of the cell using complex features.

Dilated contour extraction and component labeling algorithm for object vector representation

NASA Astrophysics Data System (ADS)

Skourikhine, Alexei N.

2005-08-01

Object boundary extraction from binary images is important for many applications, e.g., image vectorization, automatic interpretation of images containing segmentation results, printed and handwritten documents and drawings, maps, and AutoCAD drawings. Efficient and reliable contour extraction is also important for pattern recognition due to its impact on shape-based object characterization and recognition. The presented contour tracing and component labeling algorithm produces dilated (sub-pixel) contours associated with corresponding regions. The algorithm has the following features: (1) it always produces non-intersecting, non-degenerate contours, including the case of one-pixel wide objects; (2) it associates the outer and inner (i.e., around hole) contours with the corresponding regions during the process of contour tracing in a single pass over the image; (3) it maintains desired connectivity of object regions as specified by 8-neighbor or 4-neighbor connectivity of adjacent pixels; (4) it avoids degenerate regions in both background and foreground; (5) it allows an easy augmentation that will provide information about the containment relations among regions; (6) it has a time complexity that is dominantly linear in the number of contour points. This early component labeling (contour-region association) enables subsequent efficient object-based processing of the image information.

Biometric verification in dynamic writing

NASA Astrophysics Data System (ADS)

George, Susan E.

2002-03-01

Pen-tablet devices capable of capturing the dynamics of writing record temporal and pressure information as well as the spatial pattern. This paper explores biometric verification based upon the dynamics of writing where writers are distinguished not on the basis of what they write (ie the signature), but how they write. We have collected samples of dynamic writing from 38 Chinese writers. Each writer was asked to provide 10 copies of a paragraph of text and the same number of signature samples. From the data we have extracted stroke-based primitives from the sentence data utilizing pen-up/down information and heuristic rules about the shape of the character. The x, y and pressure values of each primitive were interpolated into an even temporal range based upon a 20 msec sampling rate. We applied the Daubechies 1 wavelet transform to the x signal, y signal and pressure signal using the coefficients as inputs to a multi-layer perceptron trained with back-propagation on the sentence data. We found a sensitivity of 0.977 and specificity of 0.990 recognizing writers based on test primitives extracted from sentence data and measures of 0.916 and 0.961 respectively, from test primitives extracted from signature data.

Joint deep shape and appearance learning: application to optic pathway glioma segmentation

NASA Astrophysics Data System (ADS)

Mansoor, Awais; Li, Ien; Packer, Roger J.; Avery, Robert A.; Linguraru, Marius George

2017-03-01

Automated tissue characterization is one of the major applications of computer-aided diagnosis systems. Deep learning techniques have recently demonstrated impressive performance for the image patch-based tissue characterization. However, existing patch-based tissue classification techniques struggle to exploit the useful shape information. Local and global shape knowledge such as the regional boundary changes, diameter, and volumetrics can be useful in classifying the tissues especially in scenarios where the appearance signature does not provide significant classification information. In this work, we present a deep neural network-based method for the automated segmentation of the tumors referred to as optic pathway gliomas (OPG) located within the anterior visual pathway (AVP; optic nerve, chiasm or tracts) using joint shape and appearance learning. Voxel intensity values of commonly used MRI sequences are generally not indicative of OPG. To be considered an OPG, current clinical practice dictates that some portion of AVP must demonstrate shape enlargement. The method proposed in this work integrates multiple sequence magnetic resonance image (T1, T2, and FLAIR) along with local boundary changes to train a deep neural network. For training and evaluation purposes, we used a dataset of multiple sequence MRI obtained from 20 subjects (10 controls, 10 NF1+OPG). To our best knowledge, this is the first deep representation learning-based approach designed to merge shape and multi-channel appearance data for the glioma detection. In our experiments, mean misclassification errors of 2:39% and 0:48% were observed respectively for glioma and control patches extracted from the AVP. Moreover, an overall dice similarity coefficient of 0:87+/-0:13 (0:93+/-0:06 for healthy tissue, 0:78+/-0:18 for glioma tissue) demonstrates the potential of the proposed method in the accurate localization and early detection of OPG.

Extracting cardiac shapes and motion of the chick embryo heart outflow tract from four-dimensional optical coherence tomography images

NASA Astrophysics Data System (ADS)

Yin, Xin; Liu, Aiping; Thornburg, Kent L.; Wang, Ruikang K.; Rugonyi, Sandra

2012-09-01

Recent advances in optical coherence tomography (OCT), and the development of image reconstruction algorithms, enabled four-dimensional (4-D) (three-dimensional imaging over time) imaging of the embryonic heart. To further analyze and quantify the dynamics of cardiac beating, segmentation procedures that can extract the shape of the heart and its motion are needed. Most previous studies analyzed cardiac image sequences using manually extracted shapes and measurements. However, this is time consuming and subject to inter-operator variability. Automated or semi-automated analyses of 4-D cardiac OCT images, although very desirable, are also extremely challenging. This work proposes a robust algorithm to semi automatically detect and track cardiac tissue layers from 4-D OCT images of early (tubular) embryonic hearts. Our algorithm uses a two-dimensional (2-D) deformable double-line model (DLM) to detect target cardiac tissues. The detection algorithm uses a maximum-likelihood estimator and was successfully applied to 4-D in vivo OCT images of the heart outflow tract of day three chicken embryos. The extracted shapes captured the dynamics of the chick embryonic heart outflow tract wall, enabling further analysis of cardiac motion.

Gallbladder shape extraction from ultrasound images using active contour models.

PubMed

Ciecholewski, Marcin; Chochołowicz, Jakub

2013-12-01

Gallbladder function is routinely assessed using ultrasonographic (USG) examinations. In clinical practice, doctors very often analyse the gallbladder shape when diagnosing selected disorders, e.g. if there are turns or folds of the gallbladder, so extracting its shape from USG images using supporting software can simplify a diagnosis that is often difficult to make. The paper describes two active contour models: the edge-based model and the region-based model making use of a morphological approach, both designed for extracting the gallbladder shape from USG images. The active contour models were applied to USG images without lesions and to those showing specific disease units, namely, anatomical changes like folds and turns of the gallbladder as well as polyps and gallstones. This paper also presents modifications of the edge-based model, such as the method for removing self-crossings and loops or the method of dampening the inflation force which moves nodes if they approach the edge being determined. The user is also able to add a fragment of the approximated edge beyond which neither active contour model will move if this edge is incomplete in the USG image. The modifications of the edge-based model presented here allow more precise results to be obtained when extracting the shape of the gallbladder from USG images than if the morphological model is used. © 2013 Elsevier Ltd. Published by Elsevier Ltd. All rights reserved.

Comparing the role of shape and texture on staging hepatic fibrosis from medical imaging

NASA Astrophysics Data System (ADS)

Zhang, Xuejun; Louie, Ryan; Liu, Brent J.; Gao, Xin; Tan, Xiaomin; Qu, Xianghe; Long, Liling

2016-03-01

The purpose of this study is to investigate the role of shape and texture in the classification of hepatic fibrosis by selecting the optimal parameters for a better Computer-aided diagnosis (CAD) system. 10 surface shape features are extracted from a standardized profile of liver; while15 texture features calculated from gray level co-occurrence matrix (GLCM) are extracted within an ROI in liver. Each combination of these input subsets is checked by using support vector machine (SVM) with leave-one-case-out method to differentiate fibrosis into two groups: normal or abnormal. The accurate rate value of all 10/15 types number of features is 66.83% by texture, while 85.74% by shape features, respectively. The irregularity of liver shape can demonstrate fibrotic grade efficiently and texture feature of CT image is not recommended to use with shape feature for interpretation of cirrhosis.

Pattern recognition of satellite cloud imagery for improved weather prediction

NASA Technical Reports Server (NTRS)

Gautier, Catherine; Somerville, Richard C. J.; Volfson, Leonid B.

1986-01-01

The major accomplishment was the successful development of a method for extracting time derivative information from geostationary meteorological satellite imagery. This research is a proof-of-concept study which demonstrates the feasibility of using pattern recognition techniques and a statistical cloud classification method to estimate time rate of change of large-scale meteorological fields from remote sensing data. The cloud classification methodology is based on typical shape function analysis of parameter sets characterizing the cloud fields. The three specific technical objectives, all of which were successfully achieved, are as follows: develop and test a cloud classification technique based on pattern recognition methods, suitable for the analysis of visible and infrared geostationary satellite VISSR imagery; develop and test a methodology for intercomparing successive images using the cloud classification technique, so as to obtain estimates of the time rate of change of meteorological fields; and implement this technique in a testbed system incorporating an interactive graphics terminal to determine the feasibility of extracting time derivative information suitable for comparison with numerical weather prediction products.

Selective protein extraction from Chlorobium tepidum chlorosomes using detergents. Evidence that CsmA forms multimers and binds bacteriochlorophyll a.

PubMed

Bryant, Donald A; Vassilieva, Elena V; Frigaard, Niels-Ulrik; Li, Hui

2002-12-03

Chlorosomes of the photosynthetic green sulfur bacterium Chlorobium tepidum consist of bacteriochlorophyll (BChl) c aggregates that are surrounded by a lipid-protein monolayer envelope that contains ten different proteins. Chlorosomes also contain a small amount of BChl a, but the organization and location of this BChl a are not yet clearly understood. Chlorosomes were treated with sodium dodecyl sulfate (SDS), Lubrol PX, or Triton X-100, separately or in combination with 1-hexanol, and the extracted components were separated from the residual chlorosomes by ultrafiltration on centrifugal filters. When chlorosomes were treated with low concentrations of SDS, all proteins except CsmA were extracted. However, this treatment did not significantly alter the size and shape of the chlorosomes, did not extract the BChl a, and caused only minor changes in the absorption spectrum of the chlorosomes. Cross-linking studies with SDS-treated chlorosomes revealed the presence of multimers of the major chlorosome protein, CsmA, up to homooctamers. Extraction of chlorosomes with SDS and 1-hexanol solubilized all ten chlorosome envelope proteins as well as BChl a. Although the size and shape of these extracted chlorosomes did not initially differ significantly from untreated chlorosomes, the extracted chlorosomes gradually disintegrated, and rod-shaped BChl c aggregates were sometimes observed. These results strongly suggest that CsmA binds the BChl a in Chlorobium-type chlorosomes and further indicate that none of the nine other chlorosome envelope proteins are absolutely required for maintaining the shape and integrity of chlorosomes. Quantitative estimates suggest that chlorosomes contain approximately equimolar amounts of CsmA and BChl a and that roughly one-third of the surface of the chlorosome is covered by CsmA.

A framework for longitudinal data analysis via shape regression

NASA Astrophysics Data System (ADS)

Fishbaugh, James; Durrleman, Stanley; Piven, Joseph; Gerig, Guido

2012-02-01

Traditional longitudinal analysis begins by extracting desired clinical measurements, such as volume or head circumference, from discrete imaging data. Typically, the continuous evolution of a scalar measurement is estimated by choosing a 1D regression model, such as kernel regression or fitting a polynomial of fixed degree. This type of analysis not only leads to separate models for each measurement, but there is no clear anatomical or biological interpretation to aid in the selection of the appropriate paradigm. In this paper, we propose a consistent framework for the analysis of longitudinal data by estimating the continuous evolution of shape over time as twice differentiable flows of deformations. In contrast to 1D regression models, one model is chosen to realistically capture the growth of anatomical structures. From the continuous evolution of shape, we can simply extract any clinical measurements of interest. We demonstrate on real anatomical surfaces that volume extracted from a continuous shape evolution is consistent with a 1D regression performed on the discrete measurements. We further show how the visualization of shape progression can aid in the search for significant measurements. Finally, we present an example on a shape complex of the brain (left hemisphere, right hemisphere, cerebellum) that demonstrates a potential clinical application for our framework.

A supervised learning approach for Crohn's disease detection using higher-order image statistics and a novel shape asymmetry measure.

PubMed

Mahapatra, Dwarikanath; Schueffler, Peter; Tielbeek, Jeroen A W; Buhmann, Joachim M; Vos, Franciscus M

2013-10-01

Increasing incidence of Crohn's disease (CD) in the Western world has made its accurate diagnosis an important medical challenge. The current reference standard for diagnosis, colonoscopy, is time-consuming and invasive while magnetic resonance imaging (MRI) has emerged as the preferred noninvasive procedure over colonoscopy. Current MRI approaches assess rate of contrast enhancement and bowel wall thickness, and rely on extensive manual segmentation for accurate analysis. We propose a supervised learning method for the identification and localization of regions in abdominal magnetic resonance images that have been affected by CD. Low-level features like intensity and texture are used with shape asymmetry information to distinguish between diseased and normal regions. Particular emphasis is laid on a novel entropy-based shape asymmetry method and higher-order statistics like skewness and kurtosis. Multi-scale feature extraction renders the method robust. Experiments on real patient data show that our features achieve a high level of accuracy and perform better than two competing methods.

HYPOTrace: image analysis software for measuring hypocotyl growth and shape demonstrated on Arabidopsis seedlings undergoing photomorphogenesis.

PubMed

Wang, Liya; Uilecan, Ioan Vlad; Assadi, Amir H; Kozmik, Christine A; Spalding, Edgar P

2009-04-01

Analysis of time series of images can quantify plant growth and development, including the effects of genetic mutations (phenotypes) that give information about gene function. Here is demonstrated a software application named HYPOTrace that automatically extracts growth and shape information from electronic gray-scale images of Arabidopsis (Arabidopsis thaliana) seedlings. Key to the method is the iterative application of adaptive local principal components analysis to extract a set of ordered midline points (medial axis) from images of the seedling hypocotyl. Pixel intensity is weighted to avoid the medial axis being diverted by the cotyledons in areas where the two come in contact. An intensity feature useful for terminating the midline at the hypocotyl apex was isolated in each image by subtracting the baseline with a robust local regression algorithm. Applying the algorithm to time series of images of Arabidopsis seedlings responding to light resulted in automatic quantification of hypocotyl growth rate, apical hook opening, and phototropic bending with high spatiotemporal resolution. These functions are demonstrated here on wild-type, cryptochrome1, and phototropin1 seedlings for the purpose of showing that HYPOTrace generated expected results and to show how much richer the machine-vision description is compared to methods more typical in plant biology. HYPOTrace is expected to benefit seedling development research, particularly in the photomorphogenesis field, by replacing many tedious, error-prone manual measurements with a precise, largely automated computational tool.

Finger vein recognition based on the hyperinformation feature

NASA Astrophysics Data System (ADS)

Xi, Xiaoming; Yang, Gongping; Yin, Yilong; Yang, Lu

2014-01-01

The finger vein is a promising biometric pattern for personal identification due to its advantages over other existing biometrics. In finger vein recognition, feature extraction is a critical step, and many feature extraction methods have been proposed to extract the gray, texture, or shape of the finger vein. We treat them as low-level features and present a high-level feature extraction framework. Under this framework, base attribute is first defined to represent the characteristics of a certain subcategory of a subject. Then, for an image, the correlation coefficient is used for constructing the high-level feature, which reflects the correlation between this image and all base attributes. Since the high-level feature can reveal characteristics of more subcategories and contain more discriminative information, we call it hyperinformation feature (HIF). Compared with low-level features, which only represent the characteristics of one subcategory, HIF is more powerful and robust. In order to demonstrate the potential of the proposed framework, we provide a case study to extract HIF. We conduct comprehensive experiments to show the generality of the proposed framework and the efficiency of HIF on our databases, respectively. Experimental results show that HIF significantly outperforms the low-level features.

Computational segmentation of collagen fibers from second-harmonic generation images of breast cancer

NASA Astrophysics Data System (ADS)

Bredfeldt, Jeremy S.; Liu, Yuming; Pehlke, Carolyn A.; Conklin, Matthew W.; Szulczewski, Joseph M.; Inman, David R.; Keely, Patricia J.; Nowak, Robert D.; Mackie, Thomas R.; Eliceiri, Kevin W.

2014-01-01

Second-harmonic generation (SHG) imaging can help reveal interactions between collagen fibers and cancer cells. Quantitative analysis of SHG images of collagen fibers is challenged by the heterogeneity of collagen structures and low signal-to-noise ratio often found while imaging collagen in tissue. The role of collagen in breast cancer progression can be assessed post acquisition via enhanced computation. To facilitate this, we have implemented and evaluated four algorithms for extracting fiber information, such as number, length, and curvature, from a variety of SHG images of collagen in breast tissue. The image-processing algorithms included a Gaussian filter, SPIRAL-TV filter, Tubeness filter, and curvelet-denoising filter. Fibers are then extracted using an automated tracking algorithm called fiber extraction (FIRE). We evaluated the algorithm performance by comparing length, angle and position of the automatically extracted fibers with those of manually extracted fibers in twenty-five SHG images of breast cancer. We found that the curvelet-denoising filter followed by FIRE, a process we call CT-FIRE, outperforms the other algorithms under investigation. CT-FIRE was then successfully applied to track collagen fiber shape changes over time in an in vivo mouse model for breast cancer.

Eco-friendly approach for nanoparticles synthesis and mechanism behind antibacterial activity of silver and anticancer activity of gold nanoparticles.

PubMed

Patil, Maheshkumar Prakash; Kim, Gun-Do

2017-01-01

This review covers general information about the eco-friendly process for the synthesis of silver nanoparticles (AgNP) and gold nanoparticles (AuNP) and focuses on mechanism of the antibacterial activity of AgNPs and the anticancer activity of AuNPs. Biomolecules in the plant extract are involved in reduction of metal ions to nanoparticle in a one-step and eco-friendly synthesis process. Natural plant extracts contain wide range of metabolites including carbohydrates, alkaloids, terpenoids, phenolic compounds, and enzymes. A variety of plant species and plant parts have been successfully extracted and utilized for AgNP and AuNP syntheses. Green-synthesized nanoparticles eliminate the need for a stabilizing and capping agent and show shape and size-dependent biological activities. Here, we describe some of the plant extracts involved in nanoparticle synthesis, characterization methods, and biological applications. Nanoparticles are important in the field of pharmaceuticals for their strong antibacterial and anticancer activity. Considering the importance and uniqueness of this concept, the synthesis, characterization, and application of AgNPs and AuNPs are discussed in this review.

River Devices to Recover Energy with Advanced Materials (River DREAM)

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

McMahon, Daniel P.

2013-07-03

The purpose of this project is to develop a generator called a Galloping Hydroelectric Energy Extraction Device (GHEED). It uses a galloping prism to convert water flow into linear motion. This motion is converted into electricity via a dielectric elastomer generator (DEG). The galloping mechanism and the DEG are combined to create a system to effectively generate electricity. This project has three research objectives: 1. Oscillator development and design a. Characterize galloping behavior, evaluate control surface shape change on oscillator performance and demonstrate shape change with water flow change. 2. Dielectric Energy Generator (DEG) characterization and modeling a. Characterize andmore » model the performance of the DEG based on oscillator design 3. Galloping Hydroelectric Energy Extraction Device (GHEED) system modeling and integration a. Create numerical models for construction of a system performance model and define operating capabilities for this approach Accomplishing these three objectives will result in the creation of a model that can be used to fully define the operating parameters and performance capabilities of a generator based on the GHEED design. This information will be used in the next phase of product development, the creation of an integrated laboratory scale generator to confirm model predictions.« less

Automatic age and gender classification using supervised appearance model

NASA Astrophysics Data System (ADS)

Bukar, Ali Maina; Ugail, Hassan; Connah, David

2016-11-01

Age and gender classification are two important problems that recently gained popularity in the research community, due to their wide range of applications. Research has shown that both age and gender information are encoded in the face shape and texture, hence the active appearance model (AAM), a statistical model that captures shape and texture variations, has been one of the most widely used feature extraction techniques for the aforementioned problems. However, AAM suffers from some drawbacks, especially when used for classification. This is primarily because principal component analysis (PCA), which is at the core of the model, works in an unsupervised manner, i.e., PCA dimensionality reduction does not take into account how the predictor variables relate to the response (class labels). Rather, it explores only the underlying structure of the predictor variables, thus, it is no surprise if PCA discards valuable parts of the data that represent discriminatory features. Toward this end, we propose a supervised appearance model (sAM) that improves on AAM by replacing PCA with partial least-squares regression. This feature extraction technique is then used for the problems of age and gender classification. Our experiments show that sAM has better predictive power than the conventional AAM.

Single-molecule dynamics in nanofabricated traps

NASA Astrophysics Data System (ADS)

Cohen, Adam

2009-03-01

The Anti-Brownian Electrokinetic trap (ABEL trap) provides a means to immobilize a single fluorescent molecule in solution, without surface attachment chemistry. The ABEL trap works by tracking the Brownian motion of a single molecule, and applying feedback electric fields to induce an electrokinetic motion that approximately cancels the Brownian motion. We present a new design for the ABEL trap that allows smaller molecules to be trapped and more information to be extracted from the dynamics of a single molecule than was previously possible. In particular, we present strategies for extracting dynamically fluctuating mobilities and diffusion coefficients, as a means to probe dynamic changes in molecular charge and shape. If one trapped molecule is good, many trapped molecules are better. An array of single molecules in solution, each immobilized without surface attachment chemistry, provides an ideal test-bed for single-molecule analyses of intramolecular dynamics and intermolecular interactions. We present a technology for creating such an array, using a fused silica plate with nanofabricated dimples and a removable cover for sealing single molecules within the dimples. With this device one can watch the shape fluctuations of single molecules of DNA or study cooperative interactions in weakly associating protein complexes.

Geometrical modeling of complete dental shapes by using panoramic X-ray, digital mouth data and anatomical templates.

PubMed

Barone, Sandro; Paoli, Alessandro; Razionale, Armando Viviano

2015-07-01

In the field of orthodontic planning, the creation of a complete digital dental model to simulate and predict treatments is of utmost importance. Nowadays, orthodontists use panoramic radiographs (PAN) and dental crown representations obtained by optical scanning. However, these data do not contain any 3D information regarding tooth root geometries. A reliable orthodontic treatment should instead take into account entire geometrical models of dental shapes in order to better predict tooth movements. This paper presents a methodology to create complete 3D patient dental anatomies by combining digital mouth models and panoramic radiographs. The modeling process is based on using crown surfaces, reconstructed by optical scanning, and root geometries, obtained by adapting anatomical CAD templates over patient specific information extracted from radiographic data. The radiographic process is virtually replicated on crown digital geometries through the Discrete Radon Transform (DRT). The resulting virtual PAN image is used to integrate the actual radiographic data and the digital mouth model. This procedure provides the root references on the 3D digital crown models, which guide a shape adjustment of the dental CAD templates. The entire geometrical models are finally created by merging dental crowns, captured by optical scanning, and root geometries, obtained from the CAD templates. Copyright © 2015 Elsevier Ltd. All rights reserved.

Roi Detection and Vessel Segmentation in Retinal Image

NASA Astrophysics Data System (ADS)

Sabaz, F.; Atila, U.

2017-11-01

Diabetes disrupts work by affecting the structure of the eye and afterwards leads to loss of vision. Depending on the stage of disease that called diabetic retinopathy, there are sudden loss of vision and blurred vision problems. Automated detection of vessels in retinal images is a useful study to diagnose eye diseases, disease classification and other clinical trials. The shape and structure of the vessels give information about the severity of the disease and the stage of the disease. Automatic and fast detection of vessels allows for a quick diagnosis of the disease and the treatment process to start shortly. ROI detection and vessel extraction methods for retinal image are mentioned in this study. It is shown that the Frangi filter used in image processing can be successfully used in detection and extraction of vessels.

Investigation of FPGA-Based Real-Time Adaptive Digital Pulse Shaping for High-Count-Rate Applications

NASA Astrophysics Data System (ADS)

Saxena, Shefali; Hawari, Ayman I.

2017-07-01

Digital signal processing techniques have been widely used in radiation spectrometry to provide improved stability and performance with compact physical size over the traditional analog signal processing. In this paper, field-programmable gate array (FPGA)-based adaptive digital pulse shaping techniques are investigated for real-time signal processing. National Instruments (NI) NI 5761 14-bit, 250-MS/s adaptor module is used for digitizing high-purity germanium (HPGe) detector's preamplifier pulses. Digital pulse processing algorithms are implemented on the NI PXIe-7975R reconfigurable FPGA (Kintex-7) using the LabVIEW FPGA module. Based on the time separation between successive input pulses, the adaptive shaping algorithm selects the optimum shaping parameters (rise time and flattop time of trapezoid-shaping filter) for each incoming signal. A digital Sallen-Key low-pass filter is implemented to enhance signal-to-noise ratio and reduce baseline drifting in trapezoid shaping. A recursive trapezoid-shaping filter algorithm is employed for pole-zero compensation of exponentially decayed (with two-decay constants) preamplifier pulses of an HPGe detector. It allows extraction of pulse height information at the beginning of each pulse, thereby reducing the pulse pileup and increasing throughput. The algorithms for RC-CR2 timing filter, baseline restoration, pile-up rejection, and pulse height determination are digitally implemented for radiation spectroscopy. Traditionally, at high-count-rate conditions, a shorter shaping time is preferred to achieve high throughput, which deteriorates energy resolution. In this paper, experimental results are presented for varying count-rate and pulse shaping conditions. Using adaptive shaping, increased throughput is accepted while preserving the energy resolution observed using the longer shaping times.

Object Recognition in Flight: How Do Bees Distinguish between 3D Shapes?

PubMed Central

Werner, Annette; Stürzl, Wolfgang; Zanker, Johannes

2016-01-01

Honeybees (Apis mellifera) discriminate multiple object features such as colour, pattern and 2D shape, but it remains unknown whether and how bees recover three-dimensional shape. Here we show that bees can recognize objects by their three-dimensional form, whereby they employ an active strategy to uncover the depth profiles. We trained individual, free flying honeybees to collect sugar water from small three-dimensional objects made of styrofoam (sphere, cylinder, cuboids) or folded paper (convex, concave, planar) and found that bees can easily discriminate between these stimuli. We also tested possible strategies employed by the bees to uncover the depth profiles. For the card stimuli, we excluded overall shape and pictorial features (shading, texture gradients) as cues for discrimination. Lacking sufficient stereo vision, bees are known to use speed gradients in optic flow to detect edges; could the bees apply this strategy also to recover the fine details of a surface depth profile? Analysing the bees’ flight tracks in front of the stimuli revealed specific combinations of flight maneuvers (lateral translations in combination with yaw rotations), which are particularly suitable to extract depth cues from motion parallax. We modelled the generated optic flow and found characteristic patterns of angular displacement corresponding to the depth profiles of our stimuli: optic flow patterns from pure translations successfully recovered depth relations from the magnitude of angular displacements, additional rotation provided robust depth information based on the direction of the displacements; thus, the bees flight maneuvers may reflect an optimized visuo-motor strategy to extract depth structure from motion signals. The robustness and simplicity of this strategy offers an efficient solution for 3D-object-recognition without stereo vision, and could be employed by other flying insects, or mobile robots. PMID:26886006

Object Recognition in Flight: How Do Bees Distinguish between 3D Shapes?

PubMed

Werner, Annette; Stürzl, Wolfgang; Zanker, Johannes

2016-01-01

Honeybees (Apis mellifera) discriminate multiple object features such as colour, pattern and 2D shape, but it remains unknown whether and how bees recover three-dimensional shape. Here we show that bees can recognize objects by their three-dimensional form, whereby they employ an active strategy to uncover the depth profiles. We trained individual, free flying honeybees to collect sugar water from small three-dimensional objects made of styrofoam (sphere, cylinder, cuboids) or folded paper (convex, concave, planar) and found that bees can easily discriminate between these stimuli. We also tested possible strategies employed by the bees to uncover the depth profiles. For the card stimuli, we excluded overall shape and pictorial features (shading, texture gradients) as cues for discrimination. Lacking sufficient stereo vision, bees are known to use speed gradients in optic flow to detect edges; could the bees apply this strategy also to recover the fine details of a surface depth profile? Analysing the bees' flight tracks in front of the stimuli revealed specific combinations of flight maneuvers (lateral translations in combination with yaw rotations), which are particularly suitable to extract depth cues from motion parallax. We modelled the generated optic flow and found characteristic patterns of angular displacement corresponding to the depth profiles of our stimuli: optic flow patterns from pure translations successfully recovered depth relations from the magnitude of angular displacements, additional rotation provided robust depth information based on the direction of the displacements; thus, the bees flight maneuvers may reflect an optimized visuo-motor strategy to extract depth structure from motion signals. The robustness and simplicity of this strategy offers an efficient solution for 3D-object-recognition without stereo vision, and could be employed by other flying insects, or mobile robots.

Synthesis of image sequences for Korean sign language using 3D shape model

NASA Astrophysics Data System (ADS)

Hong, Mun-Ho; Choi, Chang-Seok; Kim, Chang-Seok; Jeon, Joon-Hyeon

1995-05-01

This paper proposes a method for offering information and realizing communication to the deaf-mute. The deaf-mute communicates with another person by means of sign language, but most people are unfamiliar with it. This method enables to convert text data into the corresponding image sequences for Korean sign language (KSL). Using a general 3D shape model of the upper body leads to generating the 3D motions of KSL. It is necessary to construct the general 3D shape model considering the anatomical structure of the human body. To obtain a personal 3D shape model, this general model is to adjust to the personal base images. Image synthesis for KSL consists of deforming a personal 3D shape model and texture-mapping the personal images onto the deformed model. The 3D motions for KSL have the facial expressions and the 3D movements of the head, trunk, arms and hands and are parameterized for easily deforming the model. These motion parameters of the upper body are extracted from a skilled signer's motion for each KSL and are stored to the database. Editing the parameters according to the inputs of text data yields to generate the image sequences of 3D motions.

A Finger-Shaped Tactile Sensor for Fabric Surfaces Evaluation by 2-Dimensional Active Sliding Touch

PubMed Central

Hu, Haihua; Han, Yezhen; Song, Aiguo; Chen, Shanguang; Wang, Chunhui; Wang, Zheng

2014-01-01

Sliding tactile perception is a basic function for human beings to determine the mechanical properties of object surfaces and recognize materials. Imitating this process, this paper proposes a novel finger-shaped tactile sensor based on a thin piezoelectric polyvinylidene fluoride (PVDF) film for surface texture measurement. A parallelogram mechanism is designed to ensure that the sensor applies a constant contact force perpendicular to the object surface, and a 2-dimensional movable mechanical structure is utilized to generate the relative motion at a certain speed between the sensor and the object surface. By controlling the 2-dimensional motion of the finger-shaped sensor along the object surface, small height/depth variation of surface texture changes the output charge of PVDF film then surface texture can be measured. In this paper, the finger-shaped tactile sensor is used to evaluate and classify five different kinds of linen. Fast Fourier Transformation (FFT) is utilized to get original attribute data of surface in the frequency domain, and principal component analysis (PCA) is used to compress the attribute data and extract feature information. Finally, low dimensional features are classified by Support Vector Machine (SVM). The experimental results show that this finger-shaped tactile sensor is effective and high accurate for discriminating the five textures. PMID:24618775

A finger-shaped tactile sensor for fabric surfaces evaluation by 2-dimensional active sliding touch.

PubMed

Hu, Haihua; Han, Yezhen; Song, Aiguo; Chen, Shanguang; Wang, Chunhui; Wang, Zheng

2014-03-11

Sliding tactile perception is a basic function for human beings to determine the mechanical properties of object surfaces and recognize materials. Imitating this process, this paper proposes a novel finger-shaped tactile sensor based on a thin piezoelectric polyvinylidene fluoride (PVDF) film for surface texture measurement. A parallelogram mechanism is designed to ensure that the sensor applies a constant contact force perpendicular to the object surface, and a 2-dimensional movable mechanical structure is utilized to generate the relative motion at a certain speed between the sensor and the object surface. By controlling the 2-dimensional motion of the finger-shaped sensor along the object surface, small height/depth variation of surface texture changes the output charge of PVDF film then surface texture can be measured. In this paper, the finger-shaped tactile sensor is used to evaluate and classify five different kinds of linen. Fast Fourier Transformation (FFT) is utilized to get original attribute data of surface in the frequency domain, and principal component analysis (PCA) is used to compress the attribute data and extract feature information. Finally, low dimensional features are classified by Support Vector Machine (SVM). The experimental results show that this finger-shaped tactile sensor is effective and high accurate for discriminating the five textures.

Volume estimation using food specific shape templates in mobile image-based dietary assessment

NASA Astrophysics Data System (ADS)

Chae, Junghoon; Woo, Insoo; Kim, SungYe; Maciejewski, Ross; Zhu, Fengqing; Delp, Edward J.; Boushey, Carol J.; Ebert, David S.

2011-03-01

As obesity concerns mount, dietary assessment methods for prevention and intervention are being developed. These methods include recording, cataloging and analyzing daily dietary records to monitor energy and nutrient intakes. Given the ubiquity of mobile devices with built-in cameras, one possible means of improving dietary assessment is through photographing foods and inputting these images into a system that can determine the nutrient content of foods in the images. One of the critical issues in such the image-based dietary assessment tool is the accurate and consistent estimation of food portion sizes. The objective of our study is to automatically estimate food volumes through the use of food specific shape templates. In our system, users capture food images using a mobile phone camera. Based on information (i.e., food name and code) determined through food segmentation and classification of the food images, our system choose a particular food template shape corresponding to each segmented food. Finally, our system reconstructs the three-dimensional properties of the food shape from a single image by extracting feature points in order to size the food shape template. By employing this template-based approach, our system automatically estimates food portion size, providing a consistent method for estimation food volume.

Optimized method for atmospheric signal reduction in irregular sampled InSAR time series assisted by external atmospheric information

NASA Astrophysics Data System (ADS)

Gong, W.; Meyer, F. J.

2013-12-01

It is well known that spatio-temporal the tropospheric phase signatures complicate the interpretation and detection of smaller magnitude deformation signals or unstudied motion fields. Several advanced time-series InSAR techniques were developed in the last decade that make assumptions about the stochastic properties of the signal components in interferometric phases to reduce atmospheric delay effects on surface deformation estimates. However, their need for large datasets to successfully separate the different phase contributions limits their performance if data is scarce and irregularly sampled. Limited SAR data coverage is true for many areas affected by geophysical deformation. This is either due to their low priority in mission programming, unfavorable ground coverage condition, or turbulent seasonal weather effects. In this paper, we present new adaptive atmospheric phase filtering algorithms that are specifically designed to reconstruct surface deformation signals from atmosphere-affected and irregularly sampled InSAR time series. The filters take advantage of auxiliary atmospheric delay information that is extracted from various sources, e.g. atmospheric weather models. They are embedded into a model-free Persistent Scatterer Interferometry (PSI) approach that was selected to accommodate non-linear deformation patterns that are often observed near volcanoes and earthquake zones. Two types of adaptive phase filters were developed that operate in the time dimension and separate atmosphere from deformation based on their different temporal correlation properties. Both filter types use the fact that atmospheric models can reliably predict the spatial statistics and signal power of atmospheric phase delay fields in order to automatically optimize the filter's shape parameters. In essence, both filter types will attempt to maximize the linear correlation between a-priori and the extracted atmospheric phase information. Topography-related phase components, orbit errors and the master atmospheric delays are first removed in a pre-processing step before the atmospheric filters are applied. The first adaptive filter type is using a filter kernel of Gaussian shape and is adaptively adjusting the width (defined in days) of this filter until the correlation of extracted and modeled atmospheric signal power is maximized. If atmospheric properties vary along the time series, this approach will lead to filter setting that are adapted to best reproduce atmospheric conditions at a certain observation epoch. Despite the superior performance of this first filter design, its Gaussian shape imposes non-physical relative weights onto acquisitions that ignore the known atmospheric noise in the data. Hence, in our second approach we are using atmospheric a-priori information to adaptively define the full shape of the atmospheric filter. For this process, we use a so-called normalized convolution (NC) approach that is often used in image reconstruction. Several NC designs will be presented in this paper and studied for relative performance. A cross-validation of all developed algorithms was done using both synthetic and real data. This validation showed designed filters are outperforming conventional filter methods that particularly useful for regions with limited data coverage or lack of a deformation field prior.

Arena geometry and path shape: when rats travel in straight or in circuitous paths?

PubMed

Yaski, Osnat; Portugali, Juval; Eilam, David

2011-12-01

We show here that the global geometry of the environment affects the shape of the paths of travel in rats. To examine this, individual rats were introduced into an unfamiliar arena. One group of rats (n=8) was tested in a square arena (2 m × 2 m), and the other group (n=8) in a round arena (2 m diameter). Testing was in a total darkness, since in the absence of visual information the geometry is not perceived immediately and the extraction of environment shape is slower. We found that while the level of the rats' activity did not seem to differ between both arenas, path shape differed significantly. When traveling along the perimeter, path shape basically followed the arena walls, with perimeter paths curving along the walls of the round arena, while being straight along the walls of the square arena. A similar impact of arena geometry was observed for travel away from the arena walls. Indeed, when the rats abandoned the arena walls to crosscut through the center of the arena, their center paths were circuitous in the round arena and relatively straight in the square arena. We suggest that the shapes of these paths are exploited for the same spatial task: returning back to a familiar location in the unsighted environment. Copyright © 2011 Elsevier B.V. All rights reserved.

An effective hand vein feature extraction method.

PubMed

Li, Haigang; Zhang, Qian; Li, Chengdong

2015-01-01

As a new authentication method developed years ago, vein recognition technology features the unique advantage of bioassay. This paper studies the specific procedure for the extraction of hand back vein characteristics. There are different positions used in the collecting process, so that a suitable intravenous regional orientation method is put forward, allowing the positioning area to be the same for all hand positions. In addition, to eliminate the pseudo vein area, the valley regional shape extraction operator can be improved and combined with multiple segmentation algorithms. The images should be segmented step by step, making the vein texture to appear clear and accurate. Lastly, the segmented images should be filtered, eroded, and refined. This process helps to filter the most of the pseudo vein information. Finally, a clear vein skeleton diagram is obtained, demonstrating the effectiveness of the algorithm. This paper presents a hand back vein region location method. This makes it possible to rotate and correct the image by working out the inclination degree of contour at the side of hand back.

Extended Multiscale Image Segmentation for Castellated Wall Management

NASA Astrophysics Data System (ADS)

Sakamoto, M.; Tsuguchi, M.; Chhatkuli, S.; Satoh, T.

2018-05-01

Castellated walls are positioned as tangible cultural heritage, which require regular maintenance to preserve their original state. For the demolition and repair work of the castellated wall, it is necessary to identify the individual stones constituting the wall. However, conventional approaches using laser scanning or integrated circuits (IC) tags were very time-consuming and cumbersome. Therefore, we herein propose an efficient approach for castellated wall management based on an extended multiscale image segmentation technique. In this approach, individual stone polygons are extracted from the castellated wall image and are associated with a stone management database. First, to improve the performance of the extraction of individual stone polygons having a convex shape, we developed a new shape criterion named convex hull fitness in the image segmentation process and confirmed its effectiveness. Next, we discussed the stone management database and its beneficial utilization in the repair work of castellated walls. Subsequently, we proposed irregular-shape indexes that are helpful for evaluating the stone shape and the stability of the stone arrangement state in castellated walls. Finally, we demonstrated an application of the proposed method for a typical castellated wall in Japan. Consequently, we confirmed that the stone polygons can be extracted with an acceptable level. Further, the condition of the shapes and the layout of the stones could be visually judged with the proposed irregular-shape indexes.

Segmentation of deformable organs from medical images using particle swarm optimization and nonlinear shape priors

NASA Astrophysics Data System (ADS)

Afifi, Ahmed; Nakaguchi, Toshiya; Tsumura, Norimichi

2010-03-01

In many medical applications, the automatic segmentation of deformable organs from medical images is indispensable and its accuracy is of a special interest. However, the automatic segmentation of these organs is a challenging task according to its complex shape. Moreover, the medical images usually have noise, clutter, or occlusion and considering the image information only often leads to meager image segmentation. In this paper, we propose a fully automated technique for the segmentation of deformable organs from medical images. In this technique, the segmentation is performed by fitting a nonlinear shape model with pre-segmented images. The kernel principle component analysis (KPCA) is utilized to capture the complex organs deformation and to construct the nonlinear shape model. The presegmentation is carried out by labeling each pixel according to its high level texture features extracted using the overcomplete wavelet packet decomposition. Furthermore, to guarantee an accurate fitting between the nonlinear model and the pre-segmented images, the particle swarm optimization (PSO) algorithm is employed to adapt the model parameters for the novel images. In this paper, we demonstrate the competence of proposed technique by implementing it to the liver segmentation from computed tomography (CT) scans of different patients.

Contrasting accounts of direction and shape perception in short-range motion: Counterchange compared with motion energy detection.

PubMed

Norman, Joseph; Hock, Howard; Schöner, Gregor

2014-07-01

It has long been thought (e.g., Cavanagh & Mather, 1989) that first-order motion-energy extraction via space-time comparator-type models (e.g., the elaborated Reichardt detector) is sufficient to account for human performance in the short-range motion paradigm (Braddick, 1974), including the perception of reverse-phi motion when the luminance polarity of the visual elements is inverted during successive frames. Human observers' ability to discriminate motion direction and use coherent motion information to segregate a region of a random cinematogram and determine its shape was tested; they performed better in the same-, as compared with the inverted-, polarity condition. Computational analyses of short-range motion perception based on the elaborated Reichardt motion energy detector (van Santen & Sperling, 1985) predict, incorrectly, that symmetrical results will be obtained for the same- and inverted-polarity conditions. In contrast, the counterchange detector (Hock, Schöner, & Gilroy, 2009) predicts an asymmetry quite similar to that of human observers in both motion direction and shape discrimination. The further advantage of counterchange, as compared with motion energy, detection for the perception of spatial shape- and depth-from-motion is discussed.

Joint source based analysis of multiple brain structures in studying major depressive disorder

NASA Astrophysics Data System (ADS)

Ramezani, Mahdi; Rasoulian, Abtin; Hollenstein, Tom; Harkness, Kate; Johnsrude, Ingrid; Abolmaesumi, Purang

2014-03-01

We propose a joint Source-Based Analysis (jSBA) framework to identify brain structural variations in patients with Major Depressive Disorder (MDD). In this framework, features representing position, orientation and size (i.e. pose), shape, and local tissue composition are extracted. Subsequently, simultaneous analysis of these features within a joint analysis method is performed to generate the basis sources that show signi cant di erences between subjects with MDD and those in healthy control. Moreover, in a cross-validation leave- one-out experiment, we use a Fisher Linear Discriminant (FLD) classi er to identify individuals within the MDD group. Results show that we can classify the MDD subjects with an accuracy of 76% solely based on the information gathered from the joint analysis of pose, shape, and tissue composition in multiple brain structures.

3D-shape of objects with straight line-motion by simultaneous projection of color coded patterns

NASA Astrophysics Data System (ADS)

Flores, Jorge L.; Ayubi, Gaston A.; Di Martino, J. Matías; Castillo, Oscar E.; Ferrari, Jose A.

2018-05-01

In this work, we propose a novel technique to retrieve the 3D shape of dynamic objects by the simultaneous projection of a fringe pattern and a homogeneous light pattern which are both coded in two of the color channels of a RGB image. The fringe pattern, red channel, is used to retrieve the phase by phase-shift algorithms with arbitrary phase-step, while the homogeneous pattern, blue channel, is used to match pixels from the test object in consecutive images, which are acquired at different positions, and thus, to determine the speed of the object. The proposed method successfully overcomes the standard requirement of projecting fringes of two different frequencies; one frequency to extract object information and the other one to retrieve the phase. Validation experiments are presented.

Template-based automatic extraction of the joint space of foot bones from CT scan

NASA Astrophysics Data System (ADS)

Park, Eunbi; Kim, Taeho; Park, Jinah

2016-03-01

Clean bone segmentation is critical in studying the joint anatomy for measuring the spacing between the bones. However, separation of the coupled bones in CT images is sometimes difficult due to ambiguous gray values coming from the noise and the heterogeneity of bone materials as well as narrowing of the joint space. For fine reconstruction of the individual local boundaries, manual operation is a common practice where the segmentation remains to be a bottleneck. In this paper, we present an automatic method for extracting the joint space by applying graph cut on Markov random field model to the region of interest (ROI) which is identified by a template of 3D bone structures. The template includes encoded articular surface which identifies the tight region of the high-intensity bone boundaries together with the fuzzy joint area of interest. The localized shape information from the template model within the ROI effectively separates the bones nearby. By narrowing the ROI down to the region including two types of tissue, the object extraction problem was reduced to binary segmentation and solved via graph cut. Based on the shape of a joint space marked by the template, the hard constraint was set by the initial seeds which were automatically generated from thresholding and morphological operations. The performance and the robustness of the proposed method are evaluated on 12 volumes of ankle CT data, where each volume includes a set of 4 tarsal bones (calcaneus, talus, navicular and cuboid).

Informational primacy of visual dimensions: specialized roles for luminance and chromaticity in figure-ground perception.

PubMed

Yamagishi, N; Melara, R D

2001-07-01

Three experiments were conducted to examine the distinct contributions of two visual dimensions to figure-ground segregation. In each experiment, pattern identification was assessed by asking observers to judge whether a near-threshold test pattern was the same or different in shape to a high-contrast comparison pattern. A test pattern could differ from its background along one dimension, either luminance (luminance tasks) or chromaticity (chromaticity tasks). In each task, performance in a baseline condition, in which the test pattern was intact, was compared with performance in each of several degradation conditions, in which either the contour or the surface of the figure was degraded, using either partial occlusion (Experiment 1) or ramping (Experiments 2 and 3) of figure-ground differences. In each experiment, performance in luminance tasks was worst when the contour was degraded, whereas performance in chromaticity tasks was worst when the surface was degraded. This interaction was found even when spatial frequencies were fixed across test patterns by low-pass filtering. The results are consistent with a late (postfiltering) dual-mechanism system that processes luminance information to extract boundary representations and chromaticity information to extract surface representations.

Honeybees can discriminate between Monet and Picasso paintings.

PubMed

Wu, Wen; Moreno, Antonio M; Tangen, Jason M; Reinhard, Judith

2013-01-01

Honeybees (Apis mellifera) have remarkable visual learning and discrimination abilities that extend beyond learning simple colours, shapes or patterns. They can discriminate landscape scenes, types of flowers, and even human faces. This suggests that in spite of their small brain, honeybees have a highly developed capacity for processing complex visual information, comparable in many respects to vertebrates. Here, we investigated whether this capacity extends to complex images that humans distinguish on the basis of artistic style: Impressionist paintings by Monet and Cubist paintings by Picasso. We show that honeybees learned to simultaneously discriminate between five different Monet and Picasso paintings, and that they do not rely on luminance, colour, or spatial frequency information for discrimination. When presented with novel paintings of the same style, the bees even demonstrated some ability to generalize. This suggests that honeybees are able to discriminate Monet paintings from Picasso ones by extracting and learning the characteristic visual information inherent in each painting style. Our study further suggests that discrimination of artistic styles is not a higher cognitive function that is unique to humans, but simply due to the capacity of animals-from insects to humans-to extract and categorize the visual characteristics of complex images.

Automatic design of conformal cooling channels in injection molding tooling

NASA Astrophysics Data System (ADS)

Zhang, Yingming; Hou, Binkui; Wang, Qian; Li, Yang; Huang, Zhigao

2018-02-01

The generation of cooling system plays an important role in injection molding design. A conformal cooling system can effectively improve molding efficiency and product quality. This paper provides a generic approach for building conformal cooling channels. The centrelines of these channels are generated in two steps. First, we extract conformal loops based on geometric information of product. Second, centrelines in spiral shape are built by blending these loops. We devise algorithms to implement the entire design process. A case study verifies the feasibility of this approach.

Ribosomal RNA: a key to phylogeny

NASA Technical Reports Server (NTRS)

Olsen, G. J.; Woese, C. R.

1993-01-01

As molecular phylogeny increasingly shapes our understanding of organismal relationships, no molecule has been applied to more questions than have ribosomal RNAs. We review this role of the rRNAs and some of the insights that have been gained from them. We also offer some of the practical considerations in extracting the phylogenetic information from the sequences. Finally, we stress the importance of comparing results from multiple molecules, both as a method for testing the overall reliability of the organismal phylogeny and as a method for more broadly exploring the history of the genome.

Chinese wine classification system based on micrograph using combination of shape and structure features

NASA Astrophysics Data System (ADS)

Wan, Yi

2011-06-01

Chinese wines can be classification or graded by the micrographs. Micrographs of Chinese wines show floccules, stick and granule of variant shape and size. Different wines have variant microstructure and micrographs, we study the classification of Chinese wines based on the micrographs. Shape and structure of wines' particles in microstructure is the most important feature for recognition and classification of wines. So we introduce a feature extraction method which can describe the structure and region shape of micrograph efficiently. First, the micrographs are enhanced using total variation denoising, and segmented using a modified Otsu's method based on the Rayleigh Distribution. Then features are extracted using proposed method in the paper based on area, perimeter and traditional shape feature. Eight kinds total 26 features are selected. Finally, Chinese wine classification system based on micrograph using combination of shape and structure features and BP neural network have been presented. We compare the recognition results for different choices of features (traditional shape features or proposed features). The experimental results show that the better classification rate have been achieved using the combinational features proposed in this paper.

Asymmetric dumbbell-shaped silver nanoparticles and spherical gold nanoparticles green-synthesized by mangosteen (Garcinia mangostana) pericarp waste extracts

PubMed Central

Park, Ji Su; Ahn, Eun-Young; Park, Youmie

2017-01-01

Mangosteen (Garcinia mangostana) pericarp waste extract was used to synthesize gold and silver nanoparticles by a green strategy. The extract was both a reducing and stabilizing agent during synthesis. Phytochemical screening of the extract was conducted to obtain information regarding the presence/absence of primary and secondary metabolites in the extract. The in vitro antioxidant activity results demonstrated that the extract had excellent antioxidant activity, which was comparable to a standard (butylated hydroxy toluene). Spherical gold nanoparticles (gold nanoparticles green synthesized by mangosteen pericarp extract [GM-AuNPs]) with an average size of 15.37±3.99 to 44.20±16.99 nm were observed in high-resolution transmission electron microscopy (HR-TEM) images. Most interestingly, the silver nanoparticles (silver nanoparticles green synthesized by mangosteen pericarp extract [GM-AgNPs]) had asymmetric nanodumbbell shapes where one tail grew from a spherical head. The average head size was measured to be 13.65±5.07 to 31.08±3.99 nm from HR-TEM images. The hydrodynamic size of both nanoparticles tended to increase with increasing extract concentration. Large negative zeta potentials (−18.92 to −34.77 mV) suggested that each nanoparticle solution possessed excellent colloidal stability. The reaction yields were 99.7% for GM-AuNPs and 82.8% for GM-AgNPs, which were assessed by inductively coupled plasma optical emission spectroscopy. A high-resolution X-ray diffraction pattern confirmed the face-centered cubic structure of both nanoparticles. Based on phytochemical screening and Fourier transform infrared spectra, the hydroxyl functional groups of carbohydrates, flavonoids, glycosides, and phenolic compounds were most likely involved in a reduction reaction of gold or silver salts to their corresponding nanoparticles. The in vitro cytotoxicity (based on a water-soluble tetrazolium assay) demonstrated that GM-AgNPs were toxic to both A549 (a human lung cancer cell) and NIH3T3 (a mouse fibroblast cell). The cytotoxicity of GM-AgNPs on A549 cells was related to apoptotic cell death. However, GM-AuNPs did not show any significant cytotoxicity to either cell. These results suggest that GM-AuNPs have the potential to be drug delivery vehicles or carriers for pharmaceutical and biomedical applications. PMID:29066885

Asymmetric dumbbell-shaped silver nanoparticles and spherical gold nanoparticles green-synthesized by mangosteen (Garcinia mangostana) pericarp waste extracts.

PubMed

Park, Ji Su; Ahn, Eun-Young; Park, Youmie

2017-01-01

Mangosteen ( Garcinia mangostana ) pericarp waste extract was used to synthesize gold and silver nanoparticles by a green strategy. The extract was both a reducing and stabilizing agent during synthesis. Phytochemical screening of the extract was conducted to obtain information regarding the presence/absence of primary and secondary metabolites in the extract. The in vitro antioxidant activity results demonstrated that the extract had excellent antioxidant activity, which was comparable to a standard (butylated hydroxy toluene). Spherical gold nanoparticles (gold nanoparticles green synthesized by mangosteen pericarp extract [GM-AuNPs]) with an average size of 15.37±3.99 to 44.20±16.99 nm were observed in high-resolution transmission electron microscopy (HR-TEM) images. Most interestingly, the silver nanoparticles (silver nanoparticles green synthesized by mangosteen pericarp extract [GM-AgNPs]) had asymmetric nanodumbbell shapes where one tail grew from a spherical head. The average head size was measured to be 13.65±5.07 to 31.08±3.99 nm from HR-TEM images. The hydrodynamic size of both nanoparticles tended to increase with increasing extract concentration. Large negative zeta potentials (-18.92 to -34.77 mV) suggested that each nanoparticle solution possessed excellent colloidal stability. The reaction yields were 99.7% for GM-AuNPs and 82.8% for GM-AgNPs, which were assessed by inductively coupled plasma optical emission spectroscopy. A high-resolution X-ray diffraction pattern confirmed the face-centered cubic structure of both nanoparticles. Based on phytochemical screening and Fourier transform infrared spectra, the hydroxyl functional groups of carbohydrates, flavonoids, glycosides, and phenolic compounds were most likely involved in a reduction reaction of gold or silver salts to their corresponding nanoparticles. The in vitro cytotoxicity (based on a water-soluble tetrazolium assay) demonstrated that GM-AgNPs were toxic to both A549 (a human lung cancer cell) and NIH3T3 (a mouse fibroblast cell). The cytotoxicity of GM-AgNPs on A549 cells was related to apoptotic cell death. However, GM-AuNPs did not show any significant cytotoxicity to either cell. These results suggest that GM-AuNPs have the potential to be drug delivery vehicles or carriers for pharmaceutical and biomedical applications.

Pulse shape discrimination and classification methods for continuous depth of interaction encoding PET detectors.

PubMed

Roncali, Emilie; Phipps, Jennifer E; Marcu, Laura; Cherry, Simon R

2012-10-21

In previous work we demonstrated the potential of positron emission tomography (PET) detectors with depth-of-interaction (DOI) encoding capability based on phosphor-coated crystals. A DOI resolution of 8 mm full-width at half-maximum was obtained for 20 mm long scintillator crystals using a delayed charge integration linear regression method (DCI-LR). Phosphor-coated crystals modify the pulse shape to allow continuous DOI information determination, but the relationship between pulse shape and DOI is complex. We are therefore interested in developing a sensitive and robust method to estimate the DOI. Here, linear discriminant analysis (LDA) was implemented to classify the events based on information extracted from the pulse shape. Pulses were acquired with 2×2×20 mm(3) phosphor-coated crystals at five irradiation depths and characterized by their DCI values or Laguerre coefficients. These coefficients were obtained by expanding the pulses on a Laguerre basis set and constituted a unique signature for each pulse. The DOI of individual events was predicted using LDA based on Laguerre coefficients (Laguerre-LDA) or DCI values (DCI-LDA) as discriminant features. Predicted DOIs were compared to true irradiation depths. Laguerre-LDA showed higher sensitivity and accuracy than DCI-LDA and DCI-LR and was also more robust to predict the DOI of pulses with higher statistical noise due to low light levels (interaction depths further from the photodetector face). This indicates that Laguerre-LDA may be more suitable to DOI estimation in smaller crystals where lower collected light levels are expected. This novel approach is promising for calculating DOI using pulse shape discrimination in single-ended readout depth-encoding PET detectors.

Pulse Shape Discrimination and Classification Methods for Continuous Depth of Interaction Encoding PET Detectors

PubMed Central

Roncali, Emilie; Phipps, Jennifer E.; Marcu, Laura; Cherry, Simon R.

2012-01-01

In previous work we demonstrated the potential of positron emission tomography (PET) detectors with depth-of-interaction (DOI) encoding capability based on phosphor-coated crystals. A DOI resolution of 8 mm full-width at half-maximum was obtained for 20 mm long scintillator crystals using a delayed charge integration linear regression method (DCI-LR). Phosphor-coated crystals modify the pulse shape to allow continuous DOI information determination, but the relationship between pulse shape and DOI is complex. We are therefore interested in developing a sensitive and robust method to estimate the DOI. Here, linear discriminant analysis (LDA) was implemented to classify the events based on information extracted from the pulse shape. Pulses were acquired with 2 × 2 × 20 mm3 phosphor-coated crystals at five irradiation depths and characterized by their DCI values or Laguerre coefficients. These coefficients were obtained by expanding the pulses on a Laguerre basis set and constituted a unique signature for each pulse. The DOI of individual events was predicted using LDA based on Laguerre coefficients (Laguerre-LDA) or DCI values (DCI-LDA) as discriminant features. Predicted DOIs were compared to true irradiation depths. Laguerre-LDA showed higher sensitivity and accuracy than DCI-LDA and DCI-LR and was also more robust to predict the DOI of pulses with higher statistical noise due to low light levels (interaction depths further from the photodetector face). This indicates that Laguerre-LDA may be more suitable to DOI estimation in smaller crystals where lower collected light levels are expected. This novel approach is promising for calculating DOI using pulse shape discrimination in single-ended readout depth-encoding PET detectors. PMID:23010690

Extracting built-up areas from TerraSAR-X data using object-oriented classification method

NASA Astrophysics Data System (ADS)

Wang, SuYun; Sun, Z. C.

2017-02-01

Based on single-polarized TerraSAR-X, the approach generates homogeneous segments on an arbitrary number of scale levels by applying a region-growing algorithm which takes the intensity of backscatter and shape-related properties into account. The object-oriented procedure consists of three main steps: firstly, the analysis of the local speckle behavior in the SAR intensity data, leading to the generation of a texture image; secondly, a segmentation based on the intensity image; thirdly, the classification of each segment using the derived texture file and intensity information in order to identify and extract build-up areas. In our research, the distribution of BAs in Dongying City is derived from single-polarized TSX SM image (acquired on 17th June 2013) with average ground resolution of 3m using our proposed approach. By cross-validating the random selected validation points with geo-referenced field sites, Quick Bird high-resolution imagery, confusion matrices with statistical indicators are calculated and used for assessing the classification results. The results demonstrate that an overall accuracy 92.89 and a kappa coefficient of 0.85 could be achieved. We have shown that connect texture information with the analysis of the local speckle divergence, combining texture and intensity of construction extraction is feasible, efficient and rapid.

Chemical information obtained from Auger depth profiles by means of advanced factor analysis (MLCFA)

NASA Astrophysics Data System (ADS)

De Volder, P.; Hoogewijs, R.; De Gryse, R.; Fiermans, L.; Vennik, J.

1993-01-01

The advanced multivariate statistical technique "maximum likelihood common factor analysis (MLCFA)" is shown to be superior to "principal component analysis (PCA)" for decomposing overlapping peaks into their individual component spectra of which neither the number of components nor the peak shape of the component spectra is known. An examination of the maximum resolving power of both techniques, MLCFA and PCA, by means of artificially created series of multicomponent spectra confirms this finding unambiguously. Substantial progress in the use of AES as a chemical-analysis technique is accomplished through the implementation of MLCFA. Chemical information from Auger depth profiles is extracted by investigating the variation of the line shape of the Auger signal as a function of the changing chemical state of the element. In particular, MLCFA combined with Auger depth profiling has been applied to problems related to steelcord-rubber tyre adhesion. MLCFA allows one to elucidate the precise nature of the interfacial layer of reaction products between natural rubber vulcanized on a thin brass layer. This study reveals many interesting chemical aspects of the oxi-sulfidation of brass undetectable with classical AES.

Confirmatory factor analysis of different versions of the Body Shape Questionnaire applied to Brazilian university students.

PubMed

da Silva, Wanderson Roberto; Dias, Juliana Chioda Ribeiro; Maroco, João; Campos, Juliana Alvares Duarte Bonini

2014-09-01

This study aimed at evaluating the validity, reliability, and factorial invariance of the complete (34-item) and shortened (8-item and 16-item) versions of the Body Shape Questionnaire (BSQ) when applied to Brazilian university students. A total of 739 female students with a mean age of 20.44 (standard deviation=2.45) years participated. Confirmatory factor analysis was conducted to verify the degree to which the one-factor structure satisfies the proposal for the BSQ's expected structure. Two items of the 34-item version were excluded because they had factor weights (λ)<40. All models had adequate convergent validity (average variance extracted=.43-.58; composite reliability=.85-.97) and internal consistency (α=.85-.97). The 8-item B version was considered the best shortened BSQ version (Akaike information criterion=84.07, Bayes information criterion=157.75, Browne-Cudeck criterion=84.46), with strong invariance for independent samples (Δχ(2)λ(7)=5.06, Δχ(2)Cov(8)=5.11, Δχ(2)Res(16)=19.30). Copyright © 2014 Elsevier Ltd. All rights reserved.

Shape Effect of Electrochemical Chloride Extraction in Structural Reinforced Concrete Elements Using a New Cement-Based Anodic System

PubMed Central

Carmona, Jesús; Climent, Miguel-Ángel; Antón, Carlos; de Vera, Guillem; Garcés, Pedro

2015-01-01

This article shows the research carried out by the authors focused on how the shape of structural reinforced concrete elements treated with electrochemical chloride extraction can affect the efficiency of this process. Assuming the current use of different anode systems, the present study considers the comparison of results between conventional anodes based on Ti-RuO2 wire mesh and a cement-based anodic system such as a paste of graphite-cement. Reinforced concrete elements of a meter length were molded to serve as laboratory specimens, to closely represent authentic structural supports, with circular and rectangular sections. Results confirm almost equal performances for both types of anode systems when electrochemical chloride extraction is applied to isotropic structural elements. In the case of anisotropic ones, such as rectangular sections with no uniformly distributed rebar, differences in electrical flow density were detected during the treatment. Those differences were more extreme for Ti-RuO2 mesh anode system. This particular shape effect is evidenced by obtaining the efficiencies of electrochemical chloride extraction in different points of specimens.

Research on feature extraction techniques of Hainan Li brocade pattern

NASA Astrophysics Data System (ADS)

Zhou, Yuping; Chen, Fuqiang; Zhou, Yuhua

2016-03-01

Hainan Li brocade skills has been listed as world non-material cultural heritage preservation, therefore, the research on Hainan Li brocade patterns plays an important role in Li brocade culture inheritance. The meaning of Li brocade patterns was analyzed and the shape feature extraction techniques to original Li brocade patterns were advanced in this paper, based on the contour tracking algorithm. First, edge detection was made on the design patterns, and then the morphological closing operation was used to smooth the image, and finally contour tracking was used to extract the outer contours of Li brocade patterns. The extracted contour features were processed by means of morphology, and digital characteristics of contours are obtained by invariant moments. At last, different patterns of Li brocade design are briefly analyzed according to the digital characteristics. The results showed that the pattern extraction method to Li brocade pattern shapes is feasible and effective according to above method.

[Comparison of the anti-fertility effects of four extracts from the roots of Rhynchosia volubilis Lour].

PubMed

Wang, Jian-Gang; Xiong, Cheng-Liang; Wang, Shu-Ying; Wu, Yin-Ping; Fu, Yin-Feng; Zhang, Zhao-Hui

2007-10-01

To compare the anti-fertility effects of the four extracts from the roots of Rhynchosia volubilis Lour on male mice, that is, ethanolic extract, ethyl acetate extract, n-butanol extract and aqueous extract. Four extracts from the roots of Rhynchosia volubilis Lour (1%, 0.1 ml/10 g), were administered orally for 11 weeks to adult male mice. The fertility and testicular function of the mice were assessed by mating tests and analyses of sperm motility in cauda epididymides and biochemical and histological indexes in the blood samples and reproductive organs. The four extracts, especially aqueous extract, gradually decreased the pregnancy rate of the experimental mice from the 77th day of the treatment, with an obvious reduction in the number of spermatozoa. Morphological observation of the reproductive organs by light microscopy showed that the numbers of the secondary spermatocytes and spermatids were decreased in varied degrees, and the seminiferous tubules were disarranged, while the numbers and shapes of and spermatids were decreased in varied degrees, and the seminiferous tubules were disarranged, while the numbers and shapes of spermatogonia, Sertoli cells and Leydig cells remained unchanged. The four extracts from the roots of Rhynchosia volubilis Lour all have anti-fertility effects on male mice, and that of the aqueous extract is more obvious.

Recognition of fiducial marks applied to robotic systems. Thesis

NASA Technical Reports Server (NTRS)

Georges, Wayne D.

1991-01-01

The objective was to devise a method to determine the position and orientation of the links of a PUMA 560 using fiducial marks. As a result, it is necessary to design fiducial marks and a corresponding feature extraction algorithm. The marks used are composites of three basic shapes, a circle, an equilateral triangle and a square. Once a mark is imaged, it is thresholded and the borders of each shape are extracted. These borders are subsequently used in a feature extraction algorithm. Two feature extraction algorithms are used to determine which one produces the most reliable results. The first algorithm is based on moment invariants and the second is based on the discrete version of the psi-s curve of the boundary. The latter algorithm is clearly superior for this application.

3D shape extraction segmentation and representation of soil microstructures using generalized cylinders

NASA Astrophysics Data System (ADS)

Ngom, Ndèye Fatou; Monga, Olivier; Ould Mohamed, Mohamed Mahmoud; Garnier, Patricia

2012-02-01

This paper focuses on the modeling of soil microstructures using generalized cylinders, with a specific application to pore space. The geometric modeling of these microstructures is a recent area of study, made possible by the improved performance of computed tomography techniques. X-scanners provide very-high-resolution 3D volume images ( 3-5μm) of soil samples in which pore spaces can be extracted by thresholding. However, in most cases, the pore space defines a complex volume shape that cannot be approximated using simple analytical functions. We propose representing this shape using a compact, stable, and robust piecewise approximation by means of generalized cylinders. This intrinsic shape representation conserves its topological and geometric properties. Our algorithm includes three main processing stages. The first stage consists in describing the volume shape using a minimum number of balls included within the shape, such that their union recovers the shape skeleton. The second stage involves the optimum extraction of simply connected chains of balls. The final stage copes with the approximation of each simply optimal chain using generalized cylinders: circular generalized cylinders, tori, cylinders, and truncated cones. This technique was applied to several data sets formed by real volume computed tomography soil samples. It was possible to demonstrate that our geometric representation supplied a good approximation of the pore space. We also stress the compactness and robustness of this method with respect to any changes affecting the initial data, as well as its coherence with the intuitive notion of pores. During future studies, this geometric pore space representation will be used to simulate biological dynamics.

Complex Road Intersection Modelling Based on Low-Frequency GPS Track Data

NASA Astrophysics Data System (ADS)

Huang, J.; Deng, M.; Zhang, Y.; Liu, H.

2017-09-01

It is widely accepted that digital map becomes an indispensable guide for human daily traveling. Traditional road network maps are produced in the time-consuming and labour-intensive ways, such as digitizing printed maps and extraction from remote sensing images. At present, a large number of GPS trajectory data collected by floating vehicles makes it a reality to extract high-detailed and up-to-date road network information. Road intersections are often accident-prone areas and very critical to route planning and the connectivity of road networks is mainly determined by the topological geometry of road intersections. A few studies paid attention on detecting complex road intersections and mining the attached traffic information (e.g., connectivity, topology and turning restriction) from massive GPS traces. To the authors' knowledge, recent studies mainly used high frequency (1 s sampling rate) trajectory data to detect the crossroads regions or extract rough intersection models. It is still difficult to make use of low frequency (20-100 s) and easily available trajectory data to modelling complex road intersections geometrically and semantically. The paper thus attempts to construct precise models for complex road intersection by using low frequency GPS traces. We propose to firstly extract the complex road intersections by a LCSS-based (Longest Common Subsequence) trajectory clustering method, then delineate the geometry shapes of complex road intersections by a K-segment principle curve algorithm, and finally infer the traffic constraint rules inside the complex intersections.

Combined preoperative measurement of three inferior alveolar canal factors using computed tomography predicts the risk of inferior alveolar nerve injury during lower third molar extraction.

PubMed

Tachinami, H; Tomihara, K; Fujiwara, K; Nakamori, K; Noguchi, M

2017-11-01

A retrospective cohort study was performed to assess the clinical usefulness of combination assessment using computed tomography (CT) images in patients undergoing third molar extraction. This study included 85 patients (124 extraction sites). The relationship between cortication status, buccolingual position, and shape of the inferior alveolar canal (IAC) on CT images and the incidence of inferior alveolar nerve (IAN) injury after third molar extraction was evaluated. IAN injury was observed at eight of the 124 sites (6.5%), and in five of 19 sites (26.3%) in which cortication was absent+the IAC had a lingual position+the IAC had a dumbbell shape. Significant relationships were found between IAN injury and the three IAC factors (cortication status, IAC position, and IAC shape; P=0.0001). In patients with the three IAC factors, logistic regression analysis indicated a strong association between these factors and IAN injury (P=0.007). An absence of cortication, a lingually positioned IAC, and a dumbbell-shaped IAC are considered to indicate a high risk of IAN injury according to the logistic regression analysis (P=0.007). These results suggest that a combined assessment of these three IAC factors could be useful for the improved prediction of IAN injury. Copyright © 2017 International Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

Direct extraction of electron parameters from magnetoconductance analysis in mesoscopic ring array structures

NASA Astrophysics Data System (ADS)

Sawada, A.; Faniel, S.; Mineshige, S.; Kawabata, S.; Saito, K.; Kobayashi, K.; Sekine, Y.; Sugiyama, H.; Koga, T.

2018-05-01

We report an approach for examining electron properties using information about the shape and size of a nanostructure as a measurement reference. This approach quantifies the spin precession angles per unit length directly by considering the time-reversal interferences on chaotic return trajectories within mesoscopic ring arrays (MRAs). Experimentally, we fabricated MRAs using nanolithography in InGaAs quantum wells which had a gate-controllable spin-orbit interaction (SOI). As a result, we observed an Onsager symmetry related to relativistic magnetic fields, which provided us with indispensable information for the semiclassical billiard ball simulation. Our simulations, developed based on the real-space formalism of the weak localization/antilocalization effect including the degree of freedom for electronic spin, reproduced the experimental magnetoconductivity (MC) curves with high fidelity. The values of five distinct electron parameters (Fermi wavelength, spin precession angles per unit length for two different SOIs, impurity scattering length, and phase coherence length) were thereby extracted from a single MC curve. The methodology developed here is applicable to wide ranges of nanomaterials and devices, providing a diagnostic tool for exotic properties of two-dimensional electron systems.

Experience of the ARGO autonomous vehicle

NASA Astrophysics Data System (ADS)

Bertozzi, Massimo; Broggi, Alberto; Conte, Gianni; Fascioli, Alessandra

1998-07-01

This paper presents and discusses the first results obtained by the GOLD (Generic Obstacle and Lane Detection) system as an automatic driver of ARGO. ARGO is a Lancia Thema passenger car equipped with a vision-based system that allows to extract road and environmental information from the acquired scene. By means of stereo vision, obstacles on the road are detected and localized, while the processing of a single monocular image allows to extract the road geometry in front of the vehicle. The generality of the underlying approach allows to detect generic obstacles (without constraints on shape, color, or symmetry) and to detect lane markings even in dark and in strong shadow conditions. The hardware system consists of a PC Pentium 200 Mhz with MMX technology and a frame-grabber board able to acquire 3 b/w images simultaneously; the result of the processing (position of obstacles and geometry of the road) is used to drive an actuator on the steering wheel, while debug information are presented to the user on an on-board monitor and a led-based control panel.

Fourier transform infrared spectroscopy microscopic imaging classification based on spatial-spectral features

NASA Astrophysics Data System (ADS)

Liu, Lian; Yang, Xiukun; Zhong, Mingliang; Liu, Yao; Jing, Xiaojun; Yang, Qin

2018-04-01

The discrete fractional Brownian incremental random (DFBIR) field is used to describe the irregular, random, and highly complex shapes of natural objects such as coastlines and biological tissues, for which traditional Euclidean geometry cannot be used. In this paper, an anisotropic variable window (AVW) directional operator based on the DFBIR field model is proposed for extracting spatial characteristics of Fourier transform infrared spectroscopy (FTIR) microscopic imaging. Probabilistic principal component analysis first extracts spectral features, and then the spatial features of the proposed AVW directional operator are combined with the former to construct a spatial-spectral structure, which increases feature-related information and helps a support vector machine classifier to obtain more efficient distribution-related information. Compared to Haralick’s grey-level co-occurrence matrix, Gabor filters, and local binary patterns (e.g. uniform LBPs, rotation-invariant LBPs, uniform rotation-invariant LBPs), experiments on three FTIR spectroscopy microscopic imaging datasets show that the proposed AVW directional operator is more advantageous in terms of classification accuracy, particularly for low-dimensional spaces of spatial characteristics.

The Use of Empirical Data Sources in HRA

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

Bruce Hallbert; David Gertman; Julie Marble

This paper presents a review of available information related to human performance to support Human Reliability Analysis (HRA) performed for nuclear power plants (NPPs). A number of data sources are identified as potentially useful. These include NPP licensee event reports (LERs), augmented inspection team (AIT) reports, operator requalification data, results from the literature in experimental psychology, and the Aviation Safety Reporting System (ASRSs). The paper discusses how utilizing such information improves our capability to model and quantify human performance. In particular the paper discusses how information related to performance shaping factors (PSFs) can be extracted from empirical data to determinemore » their size effect, their relative effects, as well as their interactions. The paper concludes that appropriate use of existing sources can help addressing some of the important issues we are currently facing in HRA.« less

iGRaND: an invariant frame for RGBD sensor feature detection and descriptor extraction with applications

NASA Astrophysics Data System (ADS)

Willis, Andrew R.; Brink, Kevin M.

2016-06-01

This article describes a new 3D RGBD image feature, referred to as iGRaND, for use in real-time systems that use these sensors for tracking, motion capture, or robotic vision applications. iGRaND features use a novel local reference frame derived from the image gradient and depth normal (hence iGRaND) that is invariant to scale and viewpoint for Lambertian surfaces. Using this reference frame, Euclidean invariant feature components are computed at keypoints which fuse local geometric shape information with surface appearance information. The performance of the feature for real-time odometry is analyzed and its computational complexity and accuracy is compared with leading alternative 3D features.

Object-oriented feature extraction approach for mapping supraglacial debris in Schirmacher Oasis using very high-resolution satellite data

NASA Astrophysics Data System (ADS)

Jawak, Shridhar D.; Jadhav, Ajay; Luis, Alvarinho J.

2016-05-01

Supraglacial debris was mapped in the Schirmacher Oasis, east Antarctica, by using WorldView-2 (WV-2) high resolution optical remote sensing data consisting of 8-band calibrated Gram Schmidt (GS)-sharpened and atmospherically corrected WV-2 imagery. This study is a preliminary attempt to develop an object-oriented rule set to extract supraglacial debris for Antarctic region using 8-spectral band imagery. Supraglacial debris was manually digitized from the satellite imagery to generate the ground reference data. Several trials were performed using few existing traditional pixel-based classification techniques and color-texture based object-oriented classification methods to extract supraglacial debris over a small domain of the study area. Multi-level segmentation and attributes such as scale, shape, size, compactness along with spectral information from the data were used for developing the rule set. The quantitative analysis of error was carried out against the manually digitized reference data to test the practicability of our approach over the traditional pixel-based methods. Our results indicate that OBIA-based approach (overall accuracy: 93%) for extracting supraglacial debris performed better than all the traditional pixel-based methods (overall accuracy: 80-85%). The present attempt provides a comprehensive improved method for semiautomatic feature extraction in supraglacial environment and a new direction in the cryospheric research.

A shape-based inter-layer contours correspondence method for ICT-based reverse engineering

PubMed Central

Duan, Liming; Yang, Shangpeng; Zhang, Gui; Feng, Fei; Gu, Minghui

2017-01-01

The correspondence of a stack of planar contours in ICT (industrial computed tomography)-based reverse engineering, a key step in surface reconstruction, is difficult when the contours or topology of the object are complex. Given the regularity of industrial parts and similarity of the inter-layer contours, a specialized shape-based inter-layer contours correspondence method for ICT-based reverse engineering was presented to solve the above problem based on the vectorized contours. In this paper, the vectorized contours extracted from the slices consist of three graphical primitives: circles, arcs and segments. First, the correspondence of the inter-layer primitives is conducted based on the characteristics of the primitives. Second, based on the corresponded primitives, the inter-layer contours correspond with each other using the proximity rules and exhaustive search. The proposed method can make full use of the shape information to handle industrial parts with complex structures. The feasibility and superiority of this method have been demonstrated via the related experiments. This method can play an instructive role in practice and provide a reference for the related research. PMID:28489867

A shape-based inter-layer contours correspondence method for ICT-based reverse engineering.

PubMed

Duan, Liming; Yang, Shangpeng; Zhang, Gui; Feng, Fei; Gu, Minghui

2017-01-01

The correspondence of a stack of planar contours in ICT (industrial computed tomography)-based reverse engineering, a key step in surface reconstruction, is difficult when the contours or topology of the object are complex. Given the regularity of industrial parts and similarity of the inter-layer contours, a specialized shape-based inter-layer contours correspondence method for ICT-based reverse engineering was presented to solve the above problem based on the vectorized contours. In this paper, the vectorized contours extracted from the slices consist of three graphical primitives: circles, arcs and segments. First, the correspondence of the inter-layer primitives is conducted based on the characteristics of the primitives. Second, based on the corresponded primitives, the inter-layer contours correspond with each other using the proximity rules and exhaustive search. The proposed method can make full use of the shape information to handle industrial parts with complex structures. The feasibility and superiority of this method have been demonstrated via the related experiments. This method can play an instructive role in practice and provide a reference for the related research.

Anisometric Particle Systems—from Shape Characterization to Suspension Rheology

NASA Astrophysics Data System (ADS)

Gregorová, Eva; Pabst, Willi; Vaněrková, Lucie

2009-06-01

Methods for the characterization of anisometric particle systems are discussed. For prolate particles, the aspect ratio determination via microscopic image analysis is recalled, and aspect ratio distributions as well as shape-size dependences are commented upon. For oblate particles a simple relation is recalled with can be used to determine an average aspect ratio when size distributions are available from two methods, typically from sedimentation analysis and laser diffraction. The connection between particle shape (aspect ratio) and suspension rheology is outlined and it is shown how a generic procedure, based on Brenner's theory, can be applied to predict the intrinsic viscosity when the aspect ratio is known. On the other hand it is shown, how information on the intrinsic viscosity and the critical solids volume fraction can be extracted from experiments, when the measured concentration dependence of the effective suspension viscosity is adequately interpreted (using the Krieger relation for fitting). The examples mentioned in this paper include systems with oblate or prolate ceramic particles (kaolins, pyrophyllite, wollastonite, silicon carbide) as well as (prolate) pharmaceuticals (mesalamine, ibuprofen, nifuroxazide, paracetamol).

Efficient local representations for three-dimensional palmprint recognition

NASA Astrophysics Data System (ADS)

Yang, Bing; Wang, Xiaohua; Yao, Jinliang; Yang, Xin; Zhu, Wenhua

2013-10-01

Palmprints have been broadly used for personal authentication because they are highly accurate and incur low cost. Most previous works have focused on two-dimensional (2-D) palmprint recognition in the past decade. Unfortunately, 2-D palmprint recognition systems lose the shape information when capturing palmprint images. Moreover, such 2-D palmprint images can be easily forged or affected by noise. Hence, three-dimensional (3-D) palmprint recognition has been regarded as a promising way to further improve the performance of palmprint recognition systems. We have developed a simple, but efficient method for 3-D palmprint recognition by using local features. We first utilize shape index representation to describe the geometry of local regions in 3-D palmprint data. Then, we extract local binary pattern and Gabor wavelet features from the shape index image. The two types of complementary features are finally fused at a score level for further improvements. The experimental results on the Hong Kong Polytechnic 3-D palmprint database, which contains 8000 samples from 400 palms, illustrate the effectiveness of the proposed method.

Circular blurred shape model for multiclass symbol recognition.

PubMed

Escalera, Sergio; Fornés, Alicia; Pujol, Oriol; Lladós, Josep; Radeva, Petia

2011-04-01

In this paper, we propose a circular blurred shape model descriptor to deal with the problem of symbol detection and classification as a particular case of object recognition. The feature extraction is performed by capturing the spatial arrangement of significant object characteristics in a correlogram structure. The shape information from objects is shared among correlogram regions, where a prior blurring degree defines the level of distortion allowed in the symbol, making the descriptor tolerant to irregular deformations. Moreover, the descriptor is rotation invariant by definition. We validate the effectiveness of the proposed descriptor in both the multiclass symbol recognition and symbol detection domains. In order to perform the symbol detection, the descriptors are learned using a cascade of classifiers. In the case of multiclass categorization, the new feature space is learned using a set of binary classifiers which are embedded in an error-correcting output code design. The results over four symbol data sets show the significant improvements of the proposed descriptor compared to the state-of-the-art descriptors. In particular, the results are even more significant in those cases where the symbols suffer from elastic deformations.

Statistical estimation of femur micro-architecture using optimal shape and density predictors.

PubMed

Lekadir, Karim; Hazrati-Marangalou, Javad; Hoogendoorn, Corné; Taylor, Zeike; van Rietbergen, Bert; Frangi, Alejandro F

2015-02-26

The personalization of trabecular micro-architecture has been recently shown to be important in patient-specific biomechanical models of the femur. However, high-resolution in vivo imaging of bone micro-architecture using existing modalities is still infeasible in practice due to the associated acquisition times, costs, and X-ray radiation exposure. In this study, we describe a statistical approach for the prediction of the femur micro-architecture based on the more easily extracted subject-specific bone shape and mineral density information. To this end, a training sample of ex vivo micro-CT images is used to learn the existing statistical relationships within the low and high resolution image data. More specifically, optimal bone shape and mineral density features are selected based on their predictive power and used within a partial least square regression model to estimate the unknown trabecular micro-architecture within the anatomical models of new subjects. The experimental results demonstrate the accuracy of the proposed approach, with average errors of 0.07 for both the degree of anisotropy and tensor norms. Copyright © 2015 Elsevier Ltd. All rights reserved.

Damage detection methodology on beam-like structures based on combined modal Wavelet Transform strategy

NASA Astrophysics Data System (ADS)

Serra, Roger; Lopez, Lautaro

2018-05-01

Different approaches on the detection of damages based on dynamic measurement of structures have appeared in the last decades. They were based, amongst others, on changes in natural frequencies, modal curvatures, strain energy or flexibility. Wavelet analysis has also been used to detect the abnormalities on modal shapes induced by damages. However the majority of previous work was made with non-corrupted by noise signals. Moreover, the damage influence for each mode shape was studied separately. This paper proposes a new methodology based on combined modal wavelet transform strategy to cope with noisy signals, while at the same time, able to extract the relevant information from each mode shape. The proposed methodology will be then compared with the most frequently used and wide-studied methods from the bibliography. To evaluate the performance of each method, their capacity to detect and localize damage will be analyzed in different cases. The comparison will be done by simulating the oscillations of a cantilever steel beam with and without defect as a numerical case. The proposed methodology proved to outperform classical methods in terms of noisy signals.

Real-Time Three-Dimensional Cell Segmentation in Large-Scale Microscopy Data of Developing Embryos.

PubMed

Stegmaier, Johannes; Amat, Fernando; Lemon, William C; McDole, Katie; Wan, Yinan; Teodoro, George; Mikut, Ralf; Keller, Philipp J

2016-01-25

We present the Real-time Accurate Cell-shape Extractor (RACE), a high-throughput image analysis framework for automated three-dimensional cell segmentation in large-scale images. RACE is 55-330 times faster and 2-5 times more accurate than state-of-the-art methods. We demonstrate the generality of RACE by extracting cell-shape information from entire Drosophila, zebrafish, and mouse embryos imaged with confocal and light-sheet microscopes. Using RACE, we automatically reconstructed cellular-resolution tissue anisotropy maps across developing Drosophila embryos and quantified differences in cell-shape dynamics in wild-type and mutant embryos. We furthermore integrated RACE with our framework for automated cell lineaging and performed joint segmentation and cell tracking in entire Drosophila embryos. RACE processed these terabyte-sized datasets on a single computer within 1.4 days. RACE is easy to use, as it requires adjustment of only three parameters, takes full advantage of state-of-the-art multi-core processors and graphics cards, and is available as open-source software for Windows, Linux, and Mac OS. Copyright © 2016 Elsevier Inc. All rights reserved.

Study on cold forming of special fasteners using finite element method

NASA Astrophysics Data System (ADS)

Hsia, Shao-Yi; Chou, Yu-Tuan; Yang, Chun-Chieh

2013-12-01

The cold forming plays an important role in the field of fasteners. It can be extended to the automotive industry, construction, aerospace and 3C products. This study used Deform-3D analysis software to investigate the effect of the preforms for standard hex nuts. The effective stress, effective strain, velocity field and other information could be obtained from the numerical simulation. The outcome was verified with the physical phenomena and experiments. Furthermore, the analytical process can also be used to explore the forming technology of the special shaped nuts. When comparing to the standard hex nuts during the different stages, the optimized cold forming parameters could be extracted from the simulation and adopted to improve the performance of manufacturing for the special shaped nuts. The results can help the multi-pass processing factory to establish a cold forming capacity in the development of new products. Consequence, the ability of self-design and self-manufacture for special shaped fasteners in Taiwan would be increased widely to enhance the international competition of domestic industries.

In Situ Three-Dimensional Reciprocal-Space Mapping of Diffuse Scattering Intensity Distribution and Data Analysis for Precursor Phenomenon in Shape-Memory Alloy

NASA Astrophysics Data System (ADS)

Cheng, Tian-Le; Ma, Fengde D.; Zhou, Jie E.; Jennings, Guy; Ren, Yang; Jin, Yongmei M.; Wang, Yu U.

2012-01-01

Diffuse scattering contains rich information on various structural disorders, thus providing a useful means to study the nanoscale structural deviations from the average crystal structures determined by Bragg peak analysis. Extraction of maximal information from diffuse scattering requires concerted efforts in high-quality three-dimensional (3D) data measurement, quantitative data analysis and visualization, theoretical interpretation, and computer simulations. Such an endeavor is undertaken to study the correlated dynamic atomic position fluctuations caused by thermal vibrations (phonons) in precursor state of shape-memory alloys. High-quality 3D diffuse scattering intensity data around representative Bragg peaks are collected by using in situ high-energy synchrotron x-ray diffraction and two-dimensional digital x-ray detector (image plate). Computational algorithms and codes are developed to construct the 3D reciprocal-space map of diffuse scattering intensity distribution from the measured data, which are further visualized and quantitatively analyzed to reveal in situ physical behaviors. Diffuse scattering intensity distribution is explicitly formulated in terms of atomic position fluctuations to interpret the experimental observations and identify the most relevant physical mechanisms, which help set up reduced structural models with minimal parameters to be efficiently determined by computer simulations. Such combined procedures are demonstrated by a study of phonon softening phenomenon in precursor state and premartensitic transformation of Ni-Mn-Ga shape-memory alloy.

Recognition of Similar Shaped Handwritten Marathi Characters Using Artificial Neural Network

NASA Astrophysics Data System (ADS)

Jane, Archana P.; Pund, Mukesh A.

2012-03-01

The growing need have handwritten Marathi character recognition in Indian offices such as passport, railways etc has made it vital area of a research. Similar shape characters are more prone to misclassification. In this paper a novel method is provided to recognize handwritten Marathi characters based on their features extraction and adaptive smoothing technique. Feature selections methods avoid unnecessary patterns in an image whereas adaptive smoothing technique form smooth shape of charecters.Combination of both these approaches leads to the better results. Previous study shows that, no one technique achieves 100% accuracy in handwritten character recognition area. This approach of combining both adaptive smoothing & feature extraction gives better results (approximately 75-100) and expected outcomes.

Photovoltaic panel extraction from very high-resolution aerial imagery using region-line primitive association analysis and template matching

NASA Astrophysics Data System (ADS)

Wang, Min; Cui, Qi; Sun, Yujie; Wang, Qiao

2018-07-01

In object-based image analysis (OBIA), object classification performance is jointly determined by image segmentation, sample or rule setting, and classifiers. Typically, as a crucial step to obtain object primitives, image segmentation quality significantly influences subsequent feature extraction and analyses. By contrast, template matching extracts specific objects from images and prevents shape defects caused by image segmentation. However, creating or editing templates is tedious and sometimes results in incomplete or inaccurate templates. In this study, we combine OBIA and template matching techniques to address these problems and aim for accurate photovoltaic panel (PVP) extraction from very high-resolution (VHR) aerial imagery. The proposed method is based on the previously proposed region-line primitive association framework, in which complementary information between region (segment) and line (straight line) primitives is utilized to achieve a more powerful performance than routine OBIA. Several novel concepts, including the mutual fitting ratio and best-fitting template based on region-line primitive association analyses, are proposed. Automatic template generation and matching method for PVP extraction from VHR imagery are designed for concept and model validation. Results show that the proposed method can successfully extract PVPs without any user-specified matching template or training sample. High user independency and accuracy are the main characteristics of the proposed method in comparison with routine OBIA and template matching techniques.

a Web-Based Platform for Visualizing Spatiotemporal Dynamics of Big Taxi Data

NASA Astrophysics Data System (ADS)

Xiong, H.; Chen, L.; Gui, Z.

2017-09-01

With more and more vehicles equipped with Global Positioning System (GPS), access to large-scale taxi trajectory data has become increasingly easy. Taxis are valuable sensors and information associated with taxi trajectory can provide unprecedented insight into many aspects of city life. But analysing these data presents many challenges. Visualization of taxi data is an efficient way to represent its distributions and structures and reveal hidden patterns in the data. However, Most of the existing visualization systems have some shortcomings. On the one hand, the passenger loading status and speed information cannot be expressed. On the other hand, mono-visualization form limits the information presentation. In view of these problems, this paper designs and implements a visualization system in which we use colour and shape to indicate passenger loading status and speed information and integrate various forms of taxi visualization. The main work as follows: 1. Pre-processing and storing the taxi data into MongoDB database. 2. Visualization of hotspots for taxi pickup points. Through DBSCAN clustering algorithm, we cluster the extracted taxi passenger's pickup locations to produce passenger hotspots. 3. Visualizing the dynamic of taxi moving trajectory using interactive animation. We use a thinning algorithm to reduce the amount of data and design a preloading strategyto load the data smoothly. Colour and shape are used to visualize the taxi trajectory data.

The intrinsic three-dimensional shape of galactic bars

NASA Astrophysics Data System (ADS)

Méndez-Abreu, J.; Costantin, L.; Aguerri, J. A. L.; de Lorenzo-Cáceres, A.; Corsini, E. M.

2018-06-01

We present the first statistical study on the intrinsic three-dimensional (3D) shape of a sample of 83 galactic bars extracted from the CALIFA survey. We use the galaXYZ code to derive the bar intrinsic shape with a statistical approach. The method uses only the geometric information (ellipticities and position angles) of bars and discs obtained from a multi-component photometric decomposition of the galaxy surface-brightness distributions. We find that bars are predominantly prolate-triaxial ellipsoids (68%), with a small fraction of oblate-triaxial ellipsoids (32%). The typical flattening (intrinsic C/A semiaxis ratio) of the bars in our sample is 0.34, which matches well the typical intrinsic flattening of stellar discs at these galaxy masses. We demonstrate that, for prolate-triaxial bars, the intrinsic shape of bars depends on the galaxy Hubble type and stellar mass (bars in massive S0 galaxies are thicker and more circular than those in less massive spirals). The bar intrinsic shape correlates with bulge, disc, and bar parameters. In particular with the bulge-to-total (B/T) luminosity ratio, disc g - r color, and central surface brightness of the bar, confirming the tight link between bars and their host galaxies. Combining the probability distributions of the intrinsic shape of bulges and bars in our sample we show that 52% (16%) of bulges are thicker (flatter) than the surrounding bar at 1σ level. We suggest that these percentages might be representative of the fraction of classical and disc-like bulges in our sample, respectively.

Morphology of the Physiological Apical Foramen in Maxillary and Mandibular First Molars

PubMed Central

Abarca, J.; Zaror, C.; Monardes, H.; Hermosilla, V.; Muñoz, C.; Cantin, M.

2015-01-01

SUMMARY Information regarding the anatomy of the physiological apical foramen is limited. Knowing its diameter and shapes contributes to clinical work, specifically to the cleaning and shaping of the apical third. The aim of this ex vivo study was to determine the minimum and maximum diameters and shape of the physiological apical foramen in the roots of maxillary and mandibular first molars. A descriptive study was conducted on 89 recently extracted first molars. Roots 3–5 mm from the apex were sectioned and prepared for analysis at 40× magnification. The minimum and maximum diameters of each physiological foramen were measured using the program Motic Images plus 2.0 ML. The shape of the foramina, classified as round, oval or irregular, was determined by the difference between the maximum and minimum diameters. A total of 174 physiological foramina were analyzed. The average of the minimum and maximum diameters was between 0.24–0.33 mm in maxillary first molars and between 0.25–0.33 mm in mandibular first molars. In maxillary molars, the most common shape of the foramen was oval (50%), then irregular (32%), then round (18%). In mandibular molars, the oval shape was also the most frequent (59%), followed by irregular (23%) and round (18%). The findings of this study regarding the morphology of physiological apical foramina in first molars make it easier for the operator to choose the appropriately-sized instruments to perform endodontic therapy successfully. PMID:25937698

Morphology of the Physiological Apical Foramen in Maxillary and Mandibular First Molars.

PubMed

Abarca, J; Zaror, C; Monardes, H; Hermosilla, V; Muñoz, C; Cantin, M

2014-06-01

Information regarding the anatomy of the physiological apical foramen is limited. Knowing its diameter and shapes contributes to clinical work, specifically to the cleaning and shaping of the apical third. The aim of this ex vivo study was to determine the minimum and maximum diameters and shape of the physiological apical foramen in the roots of maxillary and mandibular first molars. A descriptive study was conducted on 89 recently extracted first molars. Roots 3-5 mm from the apex were sectioned and prepared for analysis at 40× magnification. The minimum and maximum diameters of each physiological foramen were measured using the program Motic Images plus 2.0 ML. The shape of the foramina, classified as round, oval or irregular, was determined by the difference between the maximum and minimum diameters. A total of 174 physiological foramina were analyzed. The average of the minimum and maximum diameters was between 0.24-0.33 mm in maxillary first molars and between 0.25-0.33 mm in mandibular first molars. In maxillary molars, the most common shape of the foramen was oval (50%), then irregular (32%), then round (18%). In mandibular molars, the oval shape was also the most frequent (59%), followed by irregular (23%) and round (18%). The findings of this study regarding the morphology of physiological apical foramina in first molars make it easier for the operator to choose the appropriately-sized instruments to perform endodontic therapy successfully.

Object Detection Applied to Indoor Environments for Mobile Robot Navigation.

PubMed

Hernández, Alejandra Carolina; Gómez, Clara; Crespo, Jonathan; Barber, Ramón

2016-07-28

To move around the environment, human beings depend on sight more than their other senses, because it provides information about the size, shape, color and position of an object. The increasing interest in building autonomous mobile systems makes the detection and recognition of objects in indoor environments a very important and challenging task. In this work, a vision system to detect objects considering usual human environments, able to work on a real mobile robot, is developed. In the proposed system, the classification method used is Support Vector Machine (SVM) and as input to this system, RGB and depth images are used. Different segmentation techniques have been applied to each kind of object. Similarly, two alternatives to extract features of the objects are explored, based on geometric shape descriptors and bag of words. The experimental results have demonstrated the usefulness of the system for the detection and location of the objects in indoor environments. Furthermore, through the comparison of two proposed methods for extracting features, it has been determined which alternative offers better performance. The final results have been obtained taking into account the proposed problem and that the environment has not been changed, that is to say, the environment has not been altered to perform the tests.

Object Detection Applied to Indoor Environments for Mobile Robot Navigation

PubMed Central

Hernández, Alejandra Carolina; Gómez, Clara; Crespo, Jonathan; Barber, Ramón

2016-01-01

To move around the environment, human beings depend on sight more than their other senses, because it provides information about the size, shape, color and position of an object. The increasing interest in building autonomous mobile systems makes the detection and recognition of objects in indoor environments a very important and challenging task. In this work, a vision system to detect objects considering usual human environments, able to work on a real mobile robot, is developed. In the proposed system, the classification method used is Support Vector Machine (SVM) and as input to this system, RGB and depth images are used. Different segmentation techniques have been applied to each kind of object. Similarly, two alternatives to extract features of the objects are explored, based on geometric shape descriptors and bag of words. The experimental results have demonstrated the usefulness of the system for the detection and location of the objects in indoor environments. Furthermore, through the comparison of two proposed methods for extracting features, it has been determined which alternative offers better performance. The final results have been obtained taking into account the proposed problem and that the environment has not been changed, that is to say, the environment has not been altered to perform the tests. PMID:27483264

3D palmprint data fast acquisition and recognition

NASA Astrophysics Data System (ADS)

Wang, Xiaoxu; Huang, Shujun; Gao, Nan; Zhang, Zonghua

2014-11-01

This paper presents a fast 3D (Three-Dimension) palmprint capturing system and develops an efficient 3D palmprint feature extraction and recognition method. In order to fast acquire accurate 3D shape and texture of palmprint, a DLP projector triggers a CCD camera to realize synchronization. By generating and projecting green fringe pattern images onto the measured palm surface, 3D palmprint data are calculated from the fringe pattern images. The periodic feature vector can be derived from the calculated 3D palmprint data, so undistorted 3D biometrics is obtained. Using the obtained 3D palmprint data, feature matching test have been carried out by Gabor filter, competition rules and the mean curvature. Experimental results on capturing 3D palmprint show that the proposed acquisition method can fast get 3D shape information of palmprint. Some initial experiments on recognition show the proposed method is efficient by using 3D palmprint data.

Catalogue of X-Ray Texture Data for Al-Cu-Li Alloy 1460, 2090, 2096 and 2195 Near-Net-Shape Extrusions, Sheet and Plate

NASA Technical Reports Server (NTRS)

Hales, Stephen J.; Hafley, Robert A.; Alexa, Joel A.

1998-01-01

The effect of crystallographic texture on the mechanical properties of near-net-shape extrusions is of major interest ff these products are to find application in launch vehicle or aircraft structures. The objective of this research was to produce a catalogue containing quantitative texture information for extruded product, sheet and plate. The material characterized was extracted from wide, integrally stiffened panels fabricated from the Al-Cu-Li alloys 1460, 2090, 2096 and 2195. The textural characteristics of sheet and plate products of the same alloys were determined for comparison purposes. The approach involved using X-ray diffraction to generate pole figures in combination with orientation distribution function analysis. The data were compiled as a function of location in the extruded cross-sections and the variation in the major deformation- and recrystallization-related texture components was identified.

Automatic Coregistration for Multiview SAR Images in Urban Areas

NASA Astrophysics Data System (ADS)

Xiang, Y.; Kang, W.; Wang, F.; You, H.

2017-09-01

Due to the high resolution property and the side-looking mechanism of SAR sensors, complex buildings structures make the registration of SAR images in urban areas becomes very hard. In order to solve the problem, an automatic and robust coregistration approach for multiview high resolution SAR images is proposed in the paper, which consists of three main modules. First, both the reference image and the sensed image are segmented into two parts, urban areas and nonurban areas. Urban areas caused by double or multiple scattering in a SAR image have a tendency to show higher local mean and local variance values compared with general homogeneous regions due to the complex structural information. Based on this criterion, building areas are extracted. After obtaining the target regions, L-shape structures are detected using the SAR phase congruency model and Hough transform. The double bounce scatterings formed by wall and ground are shown as strong L- or T-shapes, which are usually taken as the most reliable indicator for building detection. According to the assumption that buildings are rectangular and flat models, planimetric buildings are delineated using the L-shapes, then the reconstructed target areas are obtained. For the orignal areas and the reconstructed target areas, the SAR-SIFT matching algorithm is implemented. Finally, correct corresponding points are extracted by the fast sample consensus (FSC) and the transformation model is also derived. The experimental results on a pair of multiview TerraSAR images with 1-m resolution show that the proposed approach gives a robust and precise registration performance, compared with the orignal SAR-SIFT method.

Research of spectacle frame measurement system based on structured light method

NASA Astrophysics Data System (ADS)

Guan, Dong; Chen, Xiaodong; Zhang, Xiuda; Yan, Huimin

2016-10-01

Automatic eyeglass lens edging system is now widely used to automatically cut and polish the uncut lens based on the spectacle frame shape data which is obtained from the spectacle frame measuring machine installed on the system. The conventional approach to acquire the frame shape data works in the contact scanning mode with a probe tracing around the groove contour of the spectacle frame which requires a sophisticated mechanical and numerical control system. In this paper, a novel non-contact optical measuring method based on structured light to measure the three dimensional (3D) data of the spectacle frame is proposed. First we focus on the processing approach solving the problem of deterioration of the structured light stripes caused by intense specular reflection on the frame surface. The techniques of bright-dark bi-level fringe projecting, multiple exposuring and high dynamic range imaging are introduced to obtain a high-quality image of structured light stripes. Then, the Gamma transform and median filtering are applied to enhance image contrast. In order to get rid of background noise from the image and extract the region of interest (ROI), an auxiliary lighting system of special design is utilized to help effectively distinguish between the object and the background. In addition, a morphological method with specific morphological structure-elements is adopted to remove noise between stripes and boundary of the spectacle frame. By further fringe center extraction and depth information acquisition through the method of look-up table, the 3D shape of the spectacle frame is recovered.

Reconstruction of the in-plane mode shape of a rotating tire with a continuous scanning measurement using the Hilbert-Huang transform.

PubMed

Lee, Jongsuh; Wang, Semyung; Pluymers, Bert; Desmet, Wim; Kindt, Peter

2015-02-01

Generally, the dynamic characteristics (natural frequency, damping, and mode shape) of a structure can be estimated by experimental modal analysis. Among these dynamic characteristics, mode shape requires multiple measurements of the structure at different positions, which increases the experimental cost and time. Recently, the Hilbert-Huang transform (HHT) method has been introduced to extract mode-shape information from a continuous measurement, which requires vibration measurements from one position to another position continuously with a non-contact sensor. In this research study, an effort has been made to estimate the mode shapes of a rolling tire with a single measurement instead of using the conventional experimental setup (i.e., measurement of the vibration of a rolling tire at multiple positions similar to the case of a non-rotating structure), which is used to estimate the dynamic behavior of a rolling tire. For this purpose, HHT, which was used in the continuous measurement of a non-rotating structure in previous research studies, has been used for the case of a rotating system in this study. Ambiguous mode combinations can occur in this rotating system, and therefore, a method to overcome this ambiguity is proposed in this study. In addition, the specific phenomenon for a rotating system is introduced, and the effect of this phenomenon with regard to the obtained results through HHT is investigated.

Extended Graph-Based Models for Enhanced Similarity Search in Cavbase.

PubMed

Krotzky, Timo; Fober, Thomas; Hüllermeier, Eyke; Klebe, Gerhard

2014-01-01

To calculate similarities between molecular structures, measures based on the maximum common subgraph are frequently applied. For the comparison of protein binding sites, these measures are not fully appropriate since graphs representing binding sites on a detailed atomic level tend to get very large. In combination with an NP-hard problem, a large graph leads to a computationally demanding task. Therefore, for the comparison of binding sites, a less detailed coarse graph model is used building upon so-called pseudocenters. Consistently, a loss of structural data is caused since many atoms are discarded and no information about the shape of the binding site is considered. This is usually resolved by performing subsequent calculations based on additional information. These steps are usually quite expensive, making the whole approach very slow. The main drawback of a graph-based model solely based on pseudocenters, however, is the loss of information about the shape of the protein surface. In this study, we propose a novel and efficient modeling formalism that does not increase the size of the graph model compared to the original approach, but leads to graphs containing considerably more information assigned to the nodes. More specifically, additional descriptors considering surface characteristics are extracted from the local surface and attributed to the pseudocenters stored in Cavbase. These properties are evaluated as additional node labels, which lead to a gain of information and allow for much faster but still very accurate comparisons between different structures.

Shape reconstruction of irregular bodies with multiple complementary data sources

NASA Astrophysics Data System (ADS)

Kaasalainen, M.; Viikinkoski, M.; Carry, B.; Durech, J.; Lamy, P.; Jorda, L.; Marchis, F.; Hestroffer, D.

2011-10-01

Irregularly shaped bodies with at most partial in situ data are a particular challenge for shape reconstruction and mapping. We have created an inversion algorithm and software package for complementary data sources, with which it is possible to create shape and spin models with feature details even when only groundbased data are available. The procedure uses photometry, adaptive optics or other images, occultation timings, and interferometry as main data sources, and we are extending it to include range-Doppler radar and thermal infrared data as well. The data sources are described as generalized projections in various observable spaces [2], which allows their uniform handling with essentially the same techniques, making the addition of new data sources inexpensive in terms of computation time or software development. We present a generally applicable shape support that can be automatically used for all surface types, including strongly nonconvex or non-starlike shapes. New models of Kleopatra (from photometry, adaptive optics, and interferometry) and Hermione are examples of this approach. When using adaptive optics images, the main information from these is extracted from the limb and terminator contours that can be determined much more accurately than the image pixel brightnesses that inevitably contain large errors for most targets. We have shown that the contours yield a wealth of information independent of the scattering properties of the surface [3]. Their use also facilitates a very fast and robustly converging algorithm. An important concept in the inversion is the optimal weighting of the various data modes. We have developed a mathematicallly rigorous scheme for this purpose. The resulting maximum compatibility estimate [3], a multimodal generalization of the maximum likelihood estimate, ensures that the actual information content of each source is properly taken into account, and that the resolution scale of the ensuing model can be reliably estimated. We have applied our procedure to several asteroids, and the ground truth from the Rosetta/Lutetia flyby confirmed the ability of the approach to recover shape details [1] (see also Carry et al., this meeting). We have created a general flyby-version of the procedure to construct full models of planetary targets for which probe images are only available of a part of the surface (a typical setup for many planetary missions). We have successfully combined flyby images with photometry (Steins [4]) and adaptive optics images (Lutetia); the portion of the surface accurately determined by the flyby constrains the shape solution of the "dark side" efficiently.

The Limits of Shape Recognition following Late Emergence from Blindness.

PubMed

McKyton, Ayelet; Ben-Zion, Itay; Doron, Ravid; Zohary, Ehud

2015-09-21

Visual object recognition develops during the first years of life. But what if one is deprived of vision during early post-natal development? Shape information is extracted using both low-level cues (e.g., intensity- or color-based contours) and more complex algorithms that are largely based on inference assumptions (e.g., illumination is from above, objects are often partially occluded). Previous studies, testing visual acuity using a 2D shape-identification task (Lea symbols), indicate that contour-based shape recognition can improve with visual experience, even after years of visual deprivation from birth. We hypothesized that this may generalize to other low-level cues (shape, size, and color), but not to mid-level functions (e.g., 3D shape from shading) that might require prior visual knowledge. To that end, we studied a unique group of subjects in Ethiopia that suffered from an early manifestation of dense bilateral cataracts and were surgically treated only years later. Our results suggest that the newly sighted rapidly acquire the ability to recognize an odd element within an array, on the basis of color, size, or shape differences. However, they are generally unable to find the odd shape on the basis of illusory contours, shading, or occlusion relationships. Little recovery of these mid-level functions is seen within 1 year post-operation. We find that visual performance using low-level cues is relatively robust to prolonged deprivation from birth. However, the use of pictorial depth cues to infer 3D structure from the 2D retinal image is highly susceptible to early and prolonged visual deprivation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Electron beam extraction on plasma cathode electron sources system

NASA Astrophysics Data System (ADS)

Purwadi, Agus; Taufik, M., Lely Susita R.; Suprapto, Saefurrochman, H., Anjar A.; Wibowo, Kurnia; Aziz, Ihwanul; Siswanto, Bambang

2017-03-01

ELECTRON BEAM EXTRACTION ON PLASMA CATHODE ELECTRON SOURCES SYSTEM. The electron beam extraction through window of Plasma Generator Chamber (PGC) for Pulsed Electron Irradiator (PEI) device and simulation of plasma potential has been studied. Plasma electron beam is extracted to acceleration region for enlarging their power by the external accelerating high voltage (Vext) and then it is passed foil window of the PEI for being irradiated to any target (atmospheric pressure). Electron beam extraction from plasma surface must be able to overcome potential barrier at the extraction window region which is shown by estimate simulation (Opera program) based on data of plasma surface potential of 150 V with Ueks values are varied by 150 kV, 175 kV and 200 kV respectively. PGC is made of 304 stainless steel with cylindrical shape in 30 cm of diameter, 90 cm length, electrons extraction window as many as 975 holes on the area of (15 × 65) cm2 with extraction hole cell in 0.3 mm of radius each other, an cylindrical shape IEP chamber is made of 304 stainless steel in 70 cm diameter and 30 cm length. The research result shown that the acquisition of electron beam extraction current depends on plasma parameters (electron density ne, temperature Te), accelerating high voltage Vext, the value of discharge parameter G, anode area Sa, electron extraction window area Se and extraction efficiency value α.

Pharmacognostic studies of the leaves and stem of Careya arborea Roxb.

PubMed Central

Gupta, Prakash Chandra; Sharma, Nisha; Rao, Ch V

2012-01-01

Objective To study detailed pharmacognostic profile of leaves and stem of Careya arborea (C. arborea) Roxb. (Lecthyidaceae), an important medicinal plant in the Indian system of medicine. Methods Leaf and stem samples of C. arborea were studied by macroscopical, microscopical, physicochemical, phytochemical, fluorescence analysis of powder of the plant and other methods for standardization recommended by WHO. Results Macroscopically, the leaves are simple, broadly obovate in shape, acuminate apex with crenate, dentate margin, petioles (0.1–1.8 cm) long. Microscopically, the leaf showed the presence of median large size vascular bundle covered with fibrous bundle sheath, arrangement of xylem in cup shape and presence of cortical vascular bundle, patches of sclerenchyma, phloem fibers in groups and brown pigment containing cells in stem are some of the diagnostic features noted from anatomical study. Powder microscopy of leaf revealed the presence of parenchyma cells, xylem with pitted vessels and epidermis with anisocytic stomata. The investigations also included leaf surface data; quantitative leaf microscopy and fluorescence analysis. Physiochemical parameters such as loss on drying, swelling index, extractive values and ash values were also determined and results showed that total ash of the stem bark was about two times higher than leaf and water soluble extractive value of leaf and stem bark was two times higher than alcohol soluble extractive value. Preliminary phytochemical screening showed the presence of triterpenoids, saponins, tannins and flavonoids. Conclusions The results of the study can serve as a valuable source of information and provide suitable standards for identification of this plant material in future investigations and applications. PMID:23569939

A subdivision-based parametric deformable model for surface extraction and statistical shape modeling of the knee cartilages

NASA Astrophysics Data System (ADS)

Fripp, Jurgen; Crozier, Stuart; Warfield, Simon K.; Ourselin, Sébastien

2006-03-01

Subdivision surfaces and parameterization are desirable for many algorithms that are commonly used in Medical Image Analysis. However, extracting an accurate surface and parameterization can be difficult for many anatomical objects of interest, due to noisy segmentations and the inherent variability of the object. The thin cartilages of the knee are an example of this, especially after damage is incurred from injuries or conditions like osteoarthritis. As a result, the cartilages can have different topologies or exist in multiple pieces. In this paper we present a topology preserving (genus 0) subdivision-based parametric deformable model that is used to extract the surfaces of the patella and tibial cartilages in the knee. These surfaces have minimal thickness in areas without cartilage. The algorithm inherently incorporates several desirable properties, including: shape based interpolation, sub-division remeshing and parameterization. To illustrate the usefulness of this approach, the surfaces and parameterizations of the patella cartilage are used to generate a 3D statistical shape model.

Etched poly(ether ether ketone) jacket stir bar with detachable dumbbell-shaped structure for stir bar sorptive extraction.

PubMed

Zhou, Wei; Wang, Chenlu; Wang, Xuemei; Chen, Zilin

2018-06-08

Development of stir bar sorptive extraction (SBSE) device with high stability and extraction efficiency is critical and challenging by date. In this work, etched poly(ether ether ketone) (PEEK) tube with high mechanical strength and large specific surface area was used as jacket for SBSE device. By etching with concentrated sulfuric acid, the smooth outer surface of PEEK become porous with plenty of micro holes, which was beneficial for coating of sorbents and significantly improved the extraction performance. After functionalized by bio-polydopamine method, strong hydrophobic p-naphtholbenzein molecular was immobilized onto the chemical resistant PEEK surface (PNB@E-PEEK) as stationary phase. We also firstly developed a simple detachable dumbbell-shaped structure for improving the workability of PEEK jacket stir bar. The dumbbell-shaped construction can eliminate the friction between stir bar and container, and the design of detachable structure make elution can be accomplished easier with small amount of organic solvent. It was interesting that the developed detachable dumbbell-shaped PNB@E-PEEK stir bar showed exceptional stability and extraction efficiency for SBSE enrichment of multiple analytes including several Sudan dyes, triazines, polycyclic aromatic hydrocarbons (PAHs), alkaloids and flavonoid. By coupling with high performance liquid chromatography-ultraviolet detection (HPLC-UV), PNB@E-PEEK stir bar based SBSE-HPLC-UV method was applied for the analysis of common Sudan dye pollutants. The method showed low limits of detection (0.02-0.03 ng/mL), good linearity (R 2  ≥ 0.9979) and good reproducibility (relative standard deviation ≤ 7.96%). It has been successfully applied to determine three dye pollutants in tap and lake water. Copyright © 2018 Elsevier B.V. All rights reserved.

3-Dimensional Reconstruction of the ROSETTA Targets - Application to Asteroid 2867 Steins

NASA Astrophysics Data System (ADS)

Besse, Sebastien; Groussin, O.; Jorda, L.; Lamy, P.; OSIRIS Team

2008-09-01

The OSIRIS imaging experiment aboard the Rosetta spacecraft will image asteroids Steins in September 2008 and Lutetia in 2010, and comet 67P/Churyumov-Gerasimenko in 2014. An accurate determination of the shape is a key point for the success of the mission operations and scientific objectives. Based on the experience of previous space missions (Deep Impact, Near, Galileo, Hayabusa), we are developing our own procedure for the shape reconstruction of small bodies. We use two different techniques : i) limb and terminator constraints and ii) ground control points (GCP) constraints. The first method allows the determination of a rough shape of the body when it is poorly resolved and no features are visible on the surface, while the second method provides an accurate shape model using high resolution images. We are currently testing both methods on simulated data, using and developing different algorithms for limb and terminator extraction (e.g.,wavelet), detection of points of interest (Harris, Susan, Fast Corner Detection), points pairing using correlation techniques (geometric model) and 3-dimensional reconstruction using line-of-sight information (photogrammetry). Both methods will be fully automated. We will hopefully present the 3D reconstruction of the Steins asteroid from images obtained during its flyby. Acknowledgment: Sébastien Besse acknowledges CNES and Thales for funding.

DD production and their interactions

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

Liu Yanrui; Oka, Makoto; Takizawa, Makoto

2010-07-01

S- and P-wave DD scatterings are studied in a meson exchange model with the coupling constants obtained in the heavy quark effective theory. With the extracted P-wave phase shifts and the separable potential approximation, we include the DD rescattering effect and investigate the production process e{sup +}e{sup -{yields}}DD. We find that it is difficult to explain the anomalous line shape observed by the BES Collaboration with this mechanism. Combining our model calculation and the experimental measurement, we estimate the upper limit of the nearly universal cutoff parameter to be around 2 GeV. With this number, the upper limits of themore » binding energies of the S-wave DD and BB bound states are obtained. Assuming that the S-wave and P-wave interactions rely on the same cutoff, our study provides a way of extracting the information about S-wave molecular bound states from the P-wave meson pair production.« less

Pose estimation of teeth through crown-shape matching

NASA Astrophysics Data System (ADS)

Mok, Vevin; Ong, Sim Heng; Foong, Kelvin W. C.; Kondo, Toshiaki

2002-05-01

This paper presents a technique for determining a tooth's pose given a dental plaster cast and a set of generic tooth models. The ultimate goal of pose estimation is to obtain information about the sizes and positions of the roots, which lie hidden within the gums, without the use of X-rays, CT or MRI. In our approach, the tooth of interest is first extracted from the 3D dental cast image through segmentation. 2D views are then generated from the extracted tooth and are matched against a target view generated from the generic model with known pose. Additional views are generated in the vicinity of the best view and the entire process is repeated until convergence. Upon convergence, the generic tooth is superimposed onto the dental cast to show the position of the root. The results of applying the technique to canines demonstrate the excellent potential of the algorithm for generic tooth fitting.

Capturing Revolute Motion and Revolute Joint Parameters with Optical Tracking

NASA Astrophysics Data System (ADS)

Antonya, C.

2017-12-01

Optical tracking of users and various technical systems are becoming more and more popular. It consists of analysing sequence of recorded images using video capturing devices and image processing algorithms. The returned data contains mainly point-clouds, coordinates of markers or coordinates of point of interest. These data can be used for retrieving information related to the geometry of the objects, but also to extract parameters for the analytical model of the system useful in a variety of computer aided engineering simulations. The parameter identification of joints deals with extraction of physical parameters (mainly geometric parameters) for the purpose of constructing accurate kinematic and dynamic models. The input data are the time-series of the marker’s position. The least square method was used for fitting the data into different geometrical shapes (ellipse, circle, plane) and for obtaining the position and orientation of revolute joins.

Wrapping SRS with CORBA: from textual data to distributed objects.

PubMed

Coupaye, T

1999-04-01

Biological data come in very different shapes. Databanks are maintained and used by distinct organizations. Text is the de facto Standard exchange format. The SRS system can integrate heterogeneous textual databanks but it was lacking a way to structure the extracted data. This paper presents a CORBA interface to the SRS system which manages databanks in a flat file format. SRS Object Servers are CORBA wrappers for SRS. They allow client applications (visualisation tools, data mining tools, etc.) to access and query SRS servers remotely through an Object Request Broker (ORB). They provide loader objects that contain the information extracted from the databanks by SRS. Loader objects are not hard-coded but generated in a flexible way by using loader specifications which allow SRS administrators to package data coming from distinct databanks. The prototype may be available for beta-testing. Please contact the SRS group (http://srs.ebi.ac.uk).

Raft cultivation area extraction from high resolution remote sensing imagery by fusing multi-scale region-line primitive association features

NASA Astrophysics Data System (ADS)

Wang, Min; Cui, Qi; Wang, Jie; Ming, Dongping; Lv, Guonian

2017-01-01

In this paper, we first propose several novel concepts for object-based image analysis, which include line-based shape regularity, line density, and scale-based best feature value (SBV), based on the region-line primitive association framework (RLPAF). We then propose a raft cultivation area (RCA) extraction method for high spatial resolution (HSR) remote sensing imagery based on multi-scale feature fusion and spatial rule induction. The proposed method includes the following steps: (1) Multi-scale region primitives (segments) are obtained by image segmentation method HBC-SEG, and line primitives (straight lines) are obtained by phase-based line detection method. (2) Association relationships between regions and lines are built based on RLPAF, and then multi-scale RLPAF features are extracted and SBVs are selected. (3) Several spatial rules are designed to extract RCAs within sea waters after land and water separation. Experiments show that the proposed method can successfully extract different-shaped RCAs from HR images with good performance.

Fusion of infrared polarization and intensity images based on improved toggle operator

NASA Astrophysics Data System (ADS)

Zhu, Pan; Ding, Lei; Ma, Xiaoqing; Huang, Zhanhua

2018-01-01

Integration of infrared polarization and intensity images has been a new topic in infrared image understanding and interpretation. The abundant infrared details and target from infrared image and the salient edge and shape information from polarization image should be preserved or even enhanced in the fused result. In this paper, a new fusion method is proposed for infrared polarization and intensity images based on the improved multi-scale toggle operator with spatial scale, which can effectively extract the feature information of source images and heavily reduce redundancy among different scale. Firstly, the multi-scale image features of infrared polarization and intensity images are respectively extracted at different scale levels by the improved multi-scale toggle operator. Secondly, the redundancy of the features among different scales is reduced by using spatial scale. Thirdly, the final image features are combined by simply adding all scales of feature images together, and a base image is calculated by performing mean value weighted method on smoothed source images. Finally, the fusion image is obtained by importing the combined image features into the base image with a suitable strategy. Both objective assessment and subjective vision of the experimental results indicate that the proposed method obtains better performance in preserving the details and edge information as well as improving the image contrast.

Proponent-Indigenous agreements and the implementation of the right to free, prior, and informed consent in Canada

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

Papillon, Martin, E-mail: martin.papillon@umontreal.ca; Rodon, Thierry, E-mail: thierry.rodon@pol.ulaval.ca

Indigenous peoples have gained considerable agency in shaping decisions regarding resource development on their traditional lands. This growing agency is reflected in the emergence of the right to free, prior, and informed consent (FPIC) when Indigenous rights may be adversely affected by major resource development projects. While many governments remain non-committal toward FPIC, corporate actors are more proactive at engaging with Indigenous peoples in seeking their consent to resource extraction projects through negotiated Impact and Benefit Agreements. Focusing on the Canadian context, this article discusses the roots and implications of a proponent-driven model for seeking Indigenous consent to natural resourcemore » extraction on their traditional lands. Building on two case studies, the paper argues that negotiated consent through IBAs offers a truncated version of FPIC from the perspective of the communities involved. The deliberative ethic at the core of FPIC is often undermined in the negotiation process associated with proponent-led IBAs. - Highlights: • FPIC is becoming a norm for resource extraction projects on Indigenous lands. • Proponent-led IBAs have become the main instrument to establish FPIC in Canada. • Case studies show elite-driven IBA negotiations do not always create the conditions for FPIC. • We need to pay attention to community deliberations as an inherent aspect of FPIC.« less

Toward a Computer Vision-based Wayfinding Aid for Blind Persons to Access Unfamiliar Indoor Environments.

PubMed

Tian, Yingli; Yang, Xiaodong; Yi, Chucai; Arditi, Aries

2013-04-01

Independent travel is a well known challenge for blind and visually impaired persons. In this paper, we propose a proof-of-concept computer vision-based wayfinding aid for blind people to independently access unfamiliar indoor environments. In order to find different rooms (e.g. an office, a lab, or a bathroom) and other building amenities (e.g. an exit or an elevator), we incorporate object detection with text recognition. First we develop a robust and efficient algorithm to detect doors, elevators, and cabinets based on their general geometric shape, by combining edges and corners. The algorithm is general enough to handle large intra-class variations of objects with different appearances among different indoor environments, as well as small inter-class differences between different objects such as doors and door-like cabinets. Next, in order to distinguish intra-class objects (e.g. an office door from a bathroom door), we extract and recognize text information associated with the detected objects. For text recognition, we first extract text regions from signs with multiple colors and possibly complex backgrounds, and then apply character localization and topological analysis to filter out background interference. The extracted text is recognized using off-the-shelf optical character recognition (OCR) software products. The object type, orientation, location, and text information are presented to the blind traveler as speech.

Adventitious sounds identification and extraction using temporal-spectral dominance-based features.

PubMed

Jin, Feng; Krishnan, Sridhar Sri; Sattar, Farook

2011-11-01

Respiratory sound (RS) signals carry significant information about the underlying functioning of the pulmonary system by the presence of adventitious sounds (ASs). Although many studies have addressed the problem of pathological RS classification, only a limited number of scientific works have focused on the analysis of the evolution of symptom-related signal components in joint time-frequency (TF) plane. This paper proposes a new signal identification and extraction method for various ASs based on instantaneous frequency (IF) analysis. The presented TF decomposition method produces a noise-resistant high definition TF representation of RS signals as compared to the conventional linear TF analysis methods, yet preserving the low computational complexity as compared to those quadratic TF analysis methods. The discarded phase information in conventional spectrogram has been adopted for the estimation of IF and group delay, and a temporal-spectral dominance spectrogram has subsequently been constructed by investigating the TF spreads of the computed time-corrected IF components. The proposed dominance measure enables the extraction of signal components correspond to ASs from noisy RS signal at high noise level. A new set of TF features has also been proposed to quantify the shapes of the obtained TF contours, and therefore strongly, enhances the identification of multicomponents signals such as polyphonic wheezes. An overall accuracy of 92.4±2.9% for the classification of real RS recordings shows the promising performance of the presented method.

Toward a Computer Vision-based Wayfinding Aid for Blind Persons to Access Unfamiliar Indoor Environments

PubMed Central

Tian, YingLi; Yang, Xiaodong; Yi, Chucai; Arditi, Aries

2012-01-01

Independent travel is a well known challenge for blind and visually impaired persons. In this paper, we propose a proof-of-concept computer vision-based wayfinding aid for blind people to independently access unfamiliar indoor environments. In order to find different rooms (e.g. an office, a lab, or a bathroom) and other building amenities (e.g. an exit or an elevator), we incorporate object detection with text recognition. First we develop a robust and efficient algorithm to detect doors, elevators, and cabinets based on their general geometric shape, by combining edges and corners. The algorithm is general enough to handle large intra-class variations of objects with different appearances among different indoor environments, as well as small inter-class differences between different objects such as doors and door-like cabinets. Next, in order to distinguish intra-class objects (e.g. an office door from a bathroom door), we extract and recognize text information associated with the detected objects. For text recognition, we first extract text regions from signs with multiple colors and possibly complex backgrounds, and then apply character localization and topological analysis to filter out background interference. The extracted text is recognized using off-the-shelf optical character recognition (OCR) software products. The object type, orientation, location, and text information are presented to the blind traveler as speech. PMID:23630409

A rapid biosynthesis route for the preparation of gold nanoparticles by aqueous extract of cypress leaves at room temperature

NASA Astrophysics Data System (ADS)

Noruzi, Masumeh; Zare, Davood; Davoodi, Daryoush

In the present study, green synthesis of gold nanoparticles was reported using the aqueous extract of cypress leaves. The reduction of gold salt with the extract of cypress leaves resulted in the formation of gold nanoparticles. Effects of extract concentration and extract pH were investigated on the size of the nanoparticles. It was found that the average particle size of synthesized gold nanoparticles depends strongly on extract concentration and extract pH. FT-IR spectroscopy showed that bioorganic capping molecules were bound to the surface of particles. X-ray techniques confirmed the formation of gold nanoparticles and their crystalline structure. The inductively coupled plasma atomic emission spectroscopy analysis displayed that the reaction progress is higher than 90% at room temperature. Gold nanoparticles were mostly spherical in shape along with some irregular shapes. Cypress is an evergreen plant and its leaves are easily available in all four seasons. Also, the rate of the reaction was high and it was completed in only 10 min. For these reasons, this method is cost-effective and environmentally friendly. Thus, it can be used in the synthesis of gold nanoparticles instead of chemical methods and other biosynthesis approaches.

Modeling U-shaped dose-response curves for manganese using categorical regression.

PubMed

Milton, Brittany; Krewski, Daniel; Mattison, Donald R; Karyakina, Nataliya A; Ramoju, Siva; Shilnikova, Natalia; Birkett, Nicholas; Farrell, Patrick J; McGough, Doreen

2017-01-01

Manganese is an essential nutrient which can cause adverse effects if ingested to excess or in insufficient amounts, leading to a U-shaped exposure-response relationship. Methods have recently been developed to describe such relationships by simultaneously modeling the exposure-response curves for excess and deficiency. These methods incorporate information from studies with diverse adverse health outcomes within the same analysis by assigning severity scores to achieve a common response metric for exposure-response modeling. We aimed to provide an estimate of the optimal dietary intake of manganese to balance adverse effects from deficient or excess intake. We undertook a systematic review of the literature from 1930 to 2013 and extracted information on adverse effects from manganese deficiency and excess to create a database on manganese toxicity following oral exposure. Although data were available for seven different species, only the data from rats was sufficiently comprehensive to support analytical modelling. The toxicological outcomes were standardized on an 18-point severity scale, allowing for a common analysis of all available toxicological data. Logistic regression modelling was used to simultaneously estimate the exposure-response profile for dietary deficiency and excess for manganese and generate a U-shaped exposure-response curve for all outcomes. Data were available on the adverse effects of 6113 rats. The nadir of the U-shaped joint response curve occurred at a manganese intake of 2.70mg/kgbw/day with a 95% confidence interval of 2.51-3.02. The extremes of both deficient and excess intake were associated with a 90% probability of some measurable adverse event. The manganese database supports estimation of optimal intake based on combining information on adverse effects from systematic review of published experiments. There is a need for more studies on humans. Translation of our results from rats to humans will require adjustment for interspecies differences in sensitivity to manganese. Copyright © 2016 Elsevier B.V. All rights reserved.

Fringe-projection profilometry based on two-dimensional empirical mode decomposition.

PubMed

Zheng, Suzhen; Cao, Yiping

2013-11-01

In 3D shape measurement, because deformed fringes often contain low-frequency information degraded with random noise and background intensity information, a new fringe-projection profilometry is proposed based on 2D empirical mode decomposition (2D-EMD). The fringe pattern is first decomposed into numbers of intrinsic mode functions by 2D-EMD. Because the method has partial noise reduction, the background components can be removed to obtain the fundamental components needed to perform Hilbert transformation to retrieve the phase information. The 2D-EMD can effectively extract the modulation phase of a single direction fringe and an inclined fringe pattern because it is a full 2D analysis method and considers the relationship between adjacent lines of a fringe patterns. In addition, as the method does not add noise repeatedly, as does ensemble EMD, the data processing time is shortened. Computer simulations and experiments prove the feasibility of this method.

Fused Deposition Modeling Enables the Low-Cost Fabrication of Porous, Customized-Shape Sorbents for Small-Molecule Extraction.

PubMed

Belka, Mariusz; Ulenberg, Szymon; Bączek, Tomasz

2017-04-18

Fused deposition modeling, one of the most common techniques in three-dimensional printing and additive manufacturing, has many practical applications in the fields of chemistry and pharmacy. We demonstrate that a thermoplastic elastomer-poly(vinyl alcohol) (PVA) composite material (LAY-FOMM 60), which presents porous properties after PVA removal, is useful for the extraction of small-molecule drug-like compounds from water samples. The usefulness of the proposed approach is demonstrated by the extraction of glimepiride from a water sample, followed by LC-MS analysis. The recovery was 82.24%, with a relative standard deviation of less than 5%. The proposed approach can change the way of thinking about extraction and sample preparation due to a shift to the use of sorbents with customizable size, shape, and chemical properties that do not rely on commercial suppliers.

Global 21 cm Signal Extraction from Foreground and Instrumental Effects. I. Pattern Recognition Framework for Separation Using Training Sets

NASA Astrophysics Data System (ADS)

Tauscher, Keith; Rapetti, David; Burns, Jack O.; Switzer, Eric

2018-02-01

The sky-averaged (global) highly redshifted 21 cm spectrum from neutral hydrogen is expected to appear in the VHF range of ∼20–200 MHz and its spectral shape and strength are determined by the heating properties of the first stars and black holes, by the nature and duration of reionization, and by the presence or absence of exotic physics. Measurements of the global signal would therefore provide us with a wealth of astrophysical and cosmological knowledge. However, the signal has not yet been detected because it must be seen through strong foregrounds weighted by a large beam, instrumental calibration errors, and ionospheric, ground, and radio-frequency-interference effects, which we collectively refer to as “systematics.” Here, we present a signal extraction method for global signal experiments which uses Singular Value Decomposition of “training sets” to produce systematics basis functions specifically suited to each observation. Instead of requiring precise absolute knowledge of the systematics, our method effectively requires precise knowledge of how the systematics can vary. After calculating eigenmodes for the signal and systematics, we perform a weighted least square fit of the corresponding coefficients and select the number of modes to include by minimizing an information criterion. We compare the performance of the signal extraction when minimizing various information criteria and find that minimizing the Deviance Information Criterion most consistently yields unbiased fits. The methods used here are built into our widely applicable, publicly available Python package, pylinex, which analytically calculates constraints on signals and systematics from given data, errors, and training sets.

Computer-aided diagnostic detection system of venous beading in retinal images

NASA Astrophysics Data System (ADS)

Yang, Ching-Wen; Ma, DyeJyun; Chao, ShuennChing; Wang, ChuinMu; Wen, Chia-Hsien; Lo, ChienShun; Chung, Pau-Choo; Chang, Chein-I.

2000-05-01

The detection of venous beading in retinal images provides an early sign of diabetic retinopathy and plays an important role as a preprocessing step in diagnosing ocular diseases. We present a computer-aided diagnostic system to automatically detect venous beading of blood vessels. It comprises of two modules, referred to as the blood vessel extraction module and the venus beading detection module. The former uses a bell-shaped Gaussian kernel with 12 azimuths to extract blood vessels while the latter applies a neural network-based shape cognitron to detect venous beading among the extracted blood vessels for diagnosis. Both modules are fully computer-automated. To evaluate the proposed system, 61 retinal images (32 beaded and 29 normal images) are used for performance evaluation.

3D Gravity Inversion using Tikhonov Regularization

NASA Astrophysics Data System (ADS)

Toushmalani, Reza; Saibi, Hakim

2015-08-01

Subsalt exploration for oil and gas is attractive in regions where 3D seismic depth-migration to recover the geometry of a salt base is difficult. Additional information to reduce the ambiguity in seismic images would be beneficial. Gravity data often serve these purposes in the petroleum industry. In this paper, the authors present an algorithm for a gravity inversion based on Tikhonov regularization and an automatically regularized solution process. They examined the 3D Euler deconvolution to extract the best anomaly source depth as a priori information to invert the gravity data and provided a synthetic example. Finally, they applied the gravity inversion to recently obtained gravity data from the Bandar Charak (Hormozgan, Iran) to identify its subsurface density structure. Their model showed the 3D shape of salt dome in this region.

Remote imagery for unmanned ground vehicles: the future of path planning for ground robotics

NASA Astrophysics Data System (ADS)

Frederick, Philip A.; Theisen, Bernard L.; Ward, Derek

2006-10-01

Remote Imagery for Unmanned Ground Vehicles (RIUGV) uses a combination of high-resolution multi-spectral satellite imagery and advanced commercial off-the-self (COTS) object-oriented image processing software to provide automated terrain feature extraction and classification. This information, along with elevation data, infrared imagery, a vehicle mobility model and various meta-data (local weather reports, Zobler Soil map, etc...), is fed into automated path planning software to provide a stand-alone ability to generate rapidly updateable dynamic mobility maps for Manned or Unmanned Ground Vehicles (MGVs or UGVs). These polygon based mobility maps can reside on an individual platform or a tactical network. When new information is available, change files are generated and ingested into existing mobility maps based on user selected criteria. Bandwidth concerns are mitigated by the use of shape files for the representation of the data (e.g. each object in the scene is represented by a shape file and thus can be transmitted individually). User input (desired level of stealth, required time of arrival, etc...) determines the priority in which objects are tagged for updates. This paper will also discuss the planned July 2006 field experiment.

Spike Code Flow in Cultured Neuronal Networks.

PubMed

Tamura, Shinichi; Nishitani, Yoshi; Hosokawa, Chie; Miyoshi, Tomomitsu; Sawai, Hajime; Kamimura, Takuya; Yagi, Yasushi; Mizuno-Matsumoto, Yuko; Chen, Yen-Wei

2016-01-01

We observed spike trains produced by one-shot electrical stimulation with 8 × 8 multielectrodes in cultured neuronal networks. Each electrode accepted spikes from several neurons. We extracted the short codes from spike trains and obtained a code spectrum with a nominal time accuracy of 1%. We then constructed code flow maps as movies of the electrode array to observe the code flow of "1101" and "1011," which are typical pseudorandom sequence such as that we often encountered in a literature and our experiments. They seemed to flow from one electrode to the neighboring one and maintained their shape to some extent. To quantify the flow, we calculated the "maximum cross-correlations" among neighboring electrodes, to find the direction of maximum flow of the codes with lengths less than 8. Normalized maximum cross-correlations were almost constant irrespective of code. Furthermore, if the spike trains were shuffled in interval orders or in electrodes, they became significantly small. Thus, the analysis suggested that local codes of approximately constant shape propagated and conveyed information across the network. Hence, the codes can serve as visible and trackable marks of propagating spike waves as well as evaluating information flow in the neuronal network.

Taxonomy of multi-focal nematode image stacks by a CNN based image fusion approach.

PubMed

Liu, Min; Wang, Xueping; Zhang, Hongzhong

2018-03-01

In the biomedical field, digital multi-focal images are very important for documentation and communication of specimen data, because the morphological information for a transparent specimen can be captured in form of a stack of high-quality images. Given biomedical image stacks containing multi-focal images, how to efficiently extract effective features from all layers to classify the image stacks is still an open question. We present to use a deep convolutional neural network (CNN) image fusion based multilinear approach for the taxonomy of multi-focal image stacks. A deep CNN based image fusion technique is used to combine relevant information of multi-focal images within a given image stack into a single image, which is more informative and complete than any single image in the given stack. Besides, multi-focal images within a stack are fused along 3 orthogonal directions, and multiple features extracted from the fused images along different directions are combined by canonical correlation analysis (CCA). Because multi-focal image stacks represent the effect of different factors - texture, shape, different instances within the same class and different classes of objects, we embed the deep CNN based image fusion method within a multilinear framework to propose an image fusion based multilinear classifier. The experimental results on nematode multi-focal image stacks demonstrated that the deep CNN image fusion based multilinear classifier can reach a higher classification rate (95.7%) than that by the previous multilinear based approach (88.7%), even we only use the texture feature instead of the combination of texture and shape features as in the previous work. The proposed deep CNN image fusion based multilinear approach shows great potential in building an automated nematode taxonomy system for nematologists. It is effective to classify multi-focal image stacks. Copyright © 2018 Elsevier B.V. All rights reserved.

Learned predictiveness training modulates biases towards using boundary or landmark cues during navigation

PubMed Central

Buckley, Matthew G.; Smith, Alastair D.; Haselgrove, Mark

2015-01-01

A number of navigational theories state that learning about landmark information should not interfere with learning about shape information provided by the boundary walls of an environment. A common test of such theories has been to assess whether landmark information will overshadow, or restrict, learning about shape information. Whilst a number of studies have shown that landmarks are not able to overshadow learning about shape information, some have shown that landmarks can, in fact, overshadow learning about shape information. Given the continued importance of theories that grant the shape information that is provided by the boundary of an environment a special status during learning, the experiments presented here were designed to assess whether the relative salience of shape and landmark information could account for the discrepant results of overshadowing studies. In Experiment 1, participants were first trained that either the landmarks within an arena (landmark-relevant), or the shape information provided by the boundary walls of an arena (shape-relevant), were relevant to finding a hidden goal. In a subsequent stage, when novel landmark and shape information were made relevant to finding the hidden goal, landmarks dominated behaviour for those given landmark-relevant training, whereas shape information dominated behaviour for those given shape-relevant training. Experiment 2, which was conducted without prior relevance training, revealed that the landmark cues, unconditionally, dominated behaviour in our task. The results of the present experiments, and the conflicting results from previous overshadowing experiments, are explained in terms of associative models that incorporate an attention variant. PMID:25409751

CHEMINFORMATICS TOOLS FOR TOXICANT CHARACTERIZATION

EPA Science Inventory

• Continued development of the Shape Signatures method is planed.  This effort will include further development of the Shape Signatures database of PDB-extracted ligands and of the clustering algorithm.

• In addition, we plan to develop an...

• Structure of S-shaped growth in innovation diffusion

  NASA Astrophysics Data System (ADS)

  Shimogawa, Shinsuke; Shinno, Miyuki; Saito, Hiroshi

  2012-05-01

  A basic question on innovation diffusion is why the growth curve of the adopter population in a large society is often S shaped. From macroscopic, microscopic, and mesoscopic viewpoints, the growth of the adopter population is observed as the growth curve, individual adoptions, and differences among individual adoptions, respectively. The S shape can be explained if an empirical model of the growth curve can be deduced from models of microscopic and mesoscopic structures. However, even the structure of growth curve has not been revealed yet because long-term extrapolations by proposed models of S-shaped curves are unstable and it has been very difficult to predict the long-term growth and final adopter population. This paper studies the S-shaped growth from the viewpoint of social regularities. Simple methods to analyze power laws enable us to extract the structure of the growth curve directly from the growth data of recent basic telecommunication services. This empirical model of growth curve is singular at the inflection point and a logarithmic function of time after this point, which explains the unstable extrapolations obtained using previously proposed models and the difficulty in predicting the final adopter population. Because the empirical S curve can be expressed in terms of two power laws of the regularity found in social performances of individuals, we propose the hypothesis that the S shape represents the heterogeneity of the adopter population, and the heterogeneity parameter is distributed under the regularity in social performances of individuals. This hypothesis is so powerful as to yield models of microscopic and mesoscopic structures. In the microscopic model, each potential adopter adopts the innovation when the information accumulated by the learning about the innovation exceeds a threshold. The accumulation rate of information is heterogeneous among the adopter population, whereas the threshold is a constant, which is the opposite of previously proposed models. In the mesoscopic model, flows of innovation information incoming to individuals are organized as dimorphic and partially clustered. These microscopic and mesoscopic models yield the empirical model of the S curve and explain the S shape as representing the regularities of information flows generated through a social self-organization. To demonstrate the validity and importance of the hypothesis, the models of three level structures are applied to reveal the mechanism determining and differentiating diffusion speeds. The empirical model of S curves implies that the coefficient of variation of the flow rates determines the diffusion speed for later adopters. Based on this property, a model describing the inside of information flow clusters can be given, which provides a formula interconnecting the diffusion speed, cluster populations, and a network topological parameter of the flow clusters. For two recent basic telecommunication services in Japan, the formula represents the variety of speeds in different areas and enables us to explain speed gaps between urban and rural areas and between the two services. Furthermore, the formula provides a method to estimate the final adopter population.

• Satellite altimetry in sea ice regions - detecting open water for estimating sea surface heights

  NASA Astrophysics Data System (ADS)

  Müller, Felix L.; Dettmering, Denise; Bosch, Wolfgang

  2017-04-01

  The Greenland Sea and the Farm Strait are transporting sea ice from the central Arctic ocean southwards. They are covered by a dynamic changing sea ice layer with significant influences on the Earth climate system. Between the sea ice there exist various sized open water areas known as leads, straight lined open water areas, and polynyas exhibiting a circular shape. Identifying these leads by satellite altimetry enables the extraction of sea surface height information. Analyzing the radar echoes, also called waveforms, provides information on the surface backscatter characteristics. For example waveforms reflected by calm water have a very narrow and single-peaked shape. Waveforms reflected by sea ice show more variability due to diffuse scattering. Here we analyze altimeter waveforms from different conventional pulse-limited satellite altimeters to separate open water and sea ice waveforms. An unsupervised classification approach employing partitional clustering algorithms such as K-medoids and memory-based classification methods such as K-nearest neighbor is used. The classification is based on six parameters derived from the waveform's shape, for example the maximum power or the peak's width. The open-water detection is quantitatively compared to SAR images processed while accounting for sea ice motion. The classification results are used to derive information about the temporal evolution of sea ice extent and sea surface heights. They allow to provide evidence on climate change relevant influences as for example Arctic sea level rise due to enhanced melting rates of Greenland's glaciers and an increasing fresh water influx into the Arctic ocean. Additionally, the sea ice cover extent analyzed over a long-time period provides an important indicator for a globally changing climate system.

Deep sub-wavelength metrology for advanced defect classification

NASA Astrophysics Data System (ADS)

van der Walle, P.; Kramer, E.; van der Donck, J. C. J.; Mulckhuyse, W.; Nijsten, L.; Bernal Arango, F. A.; de Jong, A.; van Zeijl, E.; Spruit, H. E. T.; van den Berg, J. H.; Nanda, G.; van Langen-Suurling, A. K.; Alkemade, P. F. A.; Pereira, S. F.; Maas, D. J.

2017-06-01

Particle defects are important contributors to yield loss in semi-conductor manufacturing. Particles need to be detected and characterized in order to determine and eliminate their root cause. We have conceived a process flow for advanced defect classification (ADC) that distinguishes three consecutive steps; detection, review and classification. For defect detection, TNO has developed the Rapid Nano (RN3) particle scanner, which illuminates the sample from nine azimuth angles. The RN3 is capable of detecting 42 nm Latex Sphere Equivalent (LSE) particles on XXX-flat Silicon wafers. For each sample, the lower detection limit (LDL) can be verified by an analysis of the speckle signal, which originates from the surface roughness of the substrate. In detection-mode (RN3.1), the signal from all illumination angles is added. In review-mode (RN3.9), the signals from all nine arms are recorded individually and analyzed in order to retrieve additional information on the shape and size of deep sub-wavelength defects. This paper presents experimental and modelling results on the extraction of shape information from the RN3.9 multi-azimuth signal such as aspect ratio, skewness, and orientation of test defects. Both modeling and experimental work confirm that the RN3.9 signal contains detailed defect shape information. After review by RN3.9, defects are coarsely classified, yielding a purified Defect-of-Interest (DoI) list for further analysis on slower metrology tools, such as SEM, AFM or HIM, that provide more detailed review data and further classification. Purifying the DoI list via optical metrology with RN3.9 will make inspection time on slower review tools more efficient.

Vessel Classification in Cosmo-Skymed SAR Data Using Hierarchical Feature Selection

NASA Astrophysics Data System (ADS)

Makedonas, A.; Theoharatos, C.; Tsagaris, V.; Anastasopoulos, V.; Costicoglou, S.

2015-04-01

SAR based ship detection and classification are important elements of maritime monitoring applications. Recently, high-resolution SAR data have opened new possibilities to researchers for achieving improved classification results. In this work, a hierarchical vessel classification procedure is presented based on a robust feature extraction and selection scheme that utilizes scale, shape and texture features in a hierarchical way. Initially, different types of feature extraction algorithms are implemented in order to form the utilized feature pool, able to represent the structure, material, orientation and other vessel type characteristics. A two-stage hierarchical feature selection algorithm is utilized next in order to be able to discriminate effectively civilian vessels into three distinct types, in COSMO-SkyMed SAR images: cargos, small ships and tankers. In our analysis, scale and shape features are utilized in order to discriminate smaller types of vessels present in the available SAR data, or shape specific vessels. Then, the most informative texture and intensity features are incorporated in order to be able to better distinguish the civilian types with high accuracy. A feature selection procedure that utilizes heuristic measures based on features' statistical characteristics, followed by an exhaustive research with feature sets formed by the most qualified features is carried out, in order to discriminate the most appropriate combination of features for the final classification. In our analysis, five COSMO-SkyMed SAR data with 2.2m x 2.2m resolution were used to analyse the detailed characteristics of these types of ships. A total of 111 ships with available AIS data were used in the classification process. The experimental results show that this method has good performance in ship classification, with an overall accuracy reaching 83%. Further investigation of additional features and proper feature selection is currently in progress.

Binary Programming Models of Spatial Pattern Recognition: Applications in Remote Sensing Image Analysis

DTIC Science & Technology

1991-12-01

9 2.6.1 Multi-Shape Detection. .. .. .. .. .. .. ...... 9 Page 2.6.2 Line Segment Extraction and Re-Combination.. 9 2.6.3 Planimetric Feature... Extraction ............... 10 2.6.4 Line Segment Extraction From Statistical Texture Analysis .............................. 11 2.6.5 Edge Following as Graph...image after image, could benefit clue to the fact that major spatial characteristics of subregions could be extracted , and minor spatial changes could be

A quantitative study of shape descriptors from glioblastoma multiforme phenotypes for predicting survival outcome

PubMed Central

Desrosiers, Christian; Hassan, Lama; Tanougast, Camel

2016-01-01

Objective: Predicting the survival outcome of patients with glioblastoma multiforme (GBM) is of key importance to clinicians for selecting the optimal course of treatment. The goal of this study was to evaluate the usefulness of geometric shape features, extracted from MR images, as a potential non-invasive way to characterize GBM tumours and predict the overall survival times of patients with GBM. Methods: The data of 40 patients with GBM were obtained from the Cancer Genome Atlas and Cancer Imaging Archive. The T1 weighted post-contrast and fluid-attenuated inversion-recovery volumes of patients were co-registered and segmented into delineate regions corresponding to three GBM phenotypes: necrosis, active tumour and oedema/invasion. A set of two-dimensional shape features were then extracted slicewise from each phenotype region and combined over slices to describe the three-dimensional shape of these phenotypes. Thereafter, a Kruskal–Wallis test was employed to identify shape features with significantly different distributions across phenotypes. Moreover, a Kaplan–Meier analysis was performed to find features strongly associated with GBM survival. Finally, a multivariate analysis based on the random forest model was used for predicting the survival group of patients with GBM. Results: Our analysis using the Kruskal–Wallis test showed that all but one shape feature had statistically significant differences across phenotypes, with p-value < 0.05, following Holm–Bonferroni correction, justifying the analysis of GBM tumour shapes on a per-phenotype basis. Furthermore, the survival analysis based on the Kaplan–Meier estimator identified three features derived from necrotic regions (i.e. Eccentricity, Extent and Solidity) that were significantly correlated with overall survival (corrected p-value < 0.05; hazard ratios between 1.68 and 1.87). In the multivariate analysis, features from necrotic regions gave the highest accuracy in predicting the survival group of patients, with a mean area under the receiver-operating characteristic curve (AUC) of 63.85%. Combining the features of all three phenotypes increased the mean AUC to 66.99%, suggesting that shape features from different phenotypes can be used in a synergic manner to predict GBM survival. Conclusion: Results show that shape features, in particular those extracted from necrotic regions, can be used effectively to characterize GBM tumours and predict the overall survival of patients with GBM. Advances in knowledge: Simple volumetric features have been largely used to characterize the different phenotypes of a GBM tumour (i.e. active tumour, oedema and necrosis). This study extends previous work by considering a wide range of shape features, extracted in different phenotypes, for the prediction of survival in patients with GBM. PMID:27781499

Differentiating defects in red oak lumber by discriminant analysis using color, shape, and density

Treesearch

B. H. Bond; D. Earl Kline; Philip A. Araman

2002-01-01

Defect color, shape, and density measures aid in the differentiation of knots, bark pockets, stain/mineral streak, and clearwood in red oak, (Quercus rubra). Various color, shape, and density measures were extracted for defects present in color and X-ray images captured using a color line scan camera and an X-ray line scan detector. Analysis of variance was used to...

Automatic segmentation of the bone and extraction of the bone cartilage interface from magnetic resonance images of the knee

NASA Astrophysics Data System (ADS)

Fripp, Jurgen; Crozier, Stuart; Warfield, Simon K.; Ourselin, Sébastien

2007-03-01

The accurate segmentation of the articular cartilages from magnetic resonance (MR) images of the knee is important for clinical studies and drug trials into conditions like osteoarthritis. Currently, segmentations are obtained using time-consuming manual or semi-automatic algorithms which have high inter- and intra-observer variabilities. This paper presents an important step towards obtaining automatic and accurate segmentations of the cartilages, namely an approach to automatically segment the bones and extract the bone-cartilage interfaces (BCI) in the knee. The segmentation is performed using three-dimensional active shape models, which are initialized using an affine registration to an atlas. The BCI are then extracted using image information and prior knowledge about the likelihood of each point belonging to the interface. The accuracy and robustness of the approach was experimentally validated using an MR database of fat suppressed spoiled gradient recall images. The (femur, tibia, patella) bone segmentation had a median Dice similarity coefficient of (0.96, 0.96, 0.89) and an average point-to-surface error of 0.16 mm on the BCI. The extracted BCI had a median surface overlap of 0.94 with the real interface, demonstrating its usefulness for subsequent cartilage segmentation or quantitative analysis.

Identification of the traditional Tibetan medicine "Shaji" and their different extracts through tri-step infrared spectroscopy

NASA Astrophysics Data System (ADS)

Liu, Yue; Li, Jingyi; Fan, Gang; Sun, Suqin; Zhang, Yuxin; Zhang, Yi; Tu, Ya

2016-11-01

Hippophae rhamnoides subsp. sinensis Rousi, Hippophae gyantsensis (Rousi) Y. S. Lian, Hippophae neurocarpa S. W. Liu & T. N. He and Hippophae tibetana Schlechtendal are typically used under one name "Shaji", to treat cardiovascular diseases and lung disorders in Tibetan medicine (TM). A complete set of infrared (IR) macro-fingerprints of these four Hippophae species should be characterized and compared simply, accurately, and in detail for identification. In the present study, tri-step IR spectroscopy, which included Fourier transform IR (FT-IR) spectroscopy, second derivative IR (SD-IR) spectroscopy and two-dimensional correlation IR (2D-IR) spectroscopy, was employed to discriminate the four Hippophae species and their corresponding extracts using different solvents. The relevant spectra exhibited the holistic chemical compositions and variations. Flavonoids, fatty acids and sugars were found to be the main chemical components. Characteristic peak positions, intensities and shapes derived from FT-IR, SD-IR and 2D-IR spectra provided valuable information for sample discrimination. Principal component analysis (PCA) of spectral differences was performed to illustrate the objective identification. Results showed that the species and their extracts can be clearly distinguished. Thus, a quick, precise and effective tri-step IR spectroscopy combined with PCA can be applied to identify and discriminate medicinal materials and their extracts in TM research.

A Method for Extracting Suspected Parotid Lesions in CT Images using Feature-based Segmentation and Active Contours based on Stationary Wavelet Transform

NASA Astrophysics Data System (ADS)

Wu, T. Y.; Lin, S. F.

2013-10-01

Automatic suspected lesion extraction is an important application in computer-aided diagnosis (CAD). In this paper, we propose a method to automatically extract the suspected parotid regions for clinical evaluation in head and neck CT images. The suspected lesion tissues in low contrast tissue regions can be localized with feature-based segmentation (FBS) based on local texture features, and can be delineated with accuracy by modified active contour models (ACM). At first, stationary wavelet transform (SWT) is introduced. The derived wavelet coefficients are applied to derive the local features for FBS, and to generate enhanced energy maps for ACM computation. Geometric shape features (GSFs) are proposed to analyze each soft tissue region segmented by FBS; the regions with higher similarity GSFs with the lesions are extracted and the information is also applied as the initial conditions for fine delineation computation. Consequently, the suspected lesions can be automatically localized and accurately delineated for aiding clinical diagnosis. The performance of the proposed method is evaluated by comparing with the results outlined by clinical experts. The experiments on 20 pathological CT data sets show that the true-positive (TP) rate on recognizing parotid lesions is about 94%, and the dimension accuracy of delineation results can also approach over 93%.

Doubling the Spectrum of Time-Domain Induced Polarization: Removal of Harmonic Noise and Self-Potential Drift

NASA Astrophysics Data System (ADS)

Fiandaca, G.; Olsson, P. I.; Auken, E.; Larsen, J. J.; Maurya, P. K.; Dahlin, T.

2015-12-01

The extraction of spectral information in the inversion process of time-domain (TD) induced polarization (IP) data is changing the use of the IP method. Data interpretation is evolving from a qualitative description of the soil, able only to discriminate the presence of contrasts in chargeability parameters, towards a quantitative analysis of the investigated media, which allows soil-type characterization. Two major limitations restrict the extraction of the spectral information of TDIP data in the field: i) the difficulty of acquiring reliable early-time measurements, in the millisecond range and ii) the self-potential drift in the measured potentials distorting the shape of the late time IP decays, in the second range. For measuring at early-times, we developed a new method for removing the powerline noise contained in the data through a model-based approach, localizing the fundamental frequency of the powerline signal in the full-waveform IP recordings. By this, we cancel both the fundamental signal and its harmonics. This noise cancellation allows the use of earlier and narrower gates, down to a few milliseconds after the current turn-off. Even earlier gates can be measured but they will be inductively "contaminated" which we at present want to avoid. A proper removal of the self-potential drift present between the potential electrodes is essential for preserving the shape of the TD decays, especially for late times. Usually constant or linear drift-removal algorithms are used, but these algorithms fail in removing the background potentials due to the polarization of the electrodes previously used for current injection. We developed a drift-removal scheme that model the polarization effect and efficiently allows for preserving the shape of the IP decays. The removal of both the harmonic noise and self-potential drift allows for doubling the usable range of TDIP data to more than three decades in time (corresponding to three decays in frequency), and will significantly advance the science and the applicability of the IP method in exploration and environmental geophysics.

A new feature extraction method for signal classification applied to cord dorsum potentials detection

PubMed Central

Vidaurre, D.; Rodríguez, E. E.; Bielza, C.; Larrañaga, P.; Rudomin, P.

2012-01-01

In the spinal cord of the anesthetized cat, spontaneous cord dorsum potentials (CDPs) appear synchronously along the lumbo-sacral segments. These CDPs have different shapes and magnitudes. Previous work has indicated that some CDPs appear to be specially associated with the activation of spinal pathways that lead to primary afferent depolarization and presynaptic inhibition. Visual detection and classification of these CDPs provides relevant information on the functional organization of the neural networks involved in the control of sensory information and allows the characterization of the changes produced by acute nerve and spinal lesions. We now present a novel feature extraction approach for signal classification, applied to CDP detection. The method is based on an intuitive procedure. We first remove by convolution the noise from the CDPs recorded in each given spinal segment. Then, we assign a coefficient for each main local maximum of the signal using its amplitude and distance to the most important maximum of the signal. These coefficients will be the input for the subsequent classification algorithm. In particular, we employ gradient boosting classification trees. This combination of approaches allows a faster and more accurate discrimination of CDPs than is obtained by other methods. PMID:22929924

A new feature extraction method for signal classification applied to cord dorsum potential detection.

PubMed

Vidaurre, D; Rodríguez, E E; Bielza, C; Larrañaga, P; Rudomin, P

2012-10-01

In the spinal cord of the anesthetized cat, spontaneous cord dorsum potentials (CDPs) appear synchronously along the lumbo-sacral segments. These CDPs have different shapes and magnitudes. Previous work has indicated that some CDPs appear to be specially associated with the activation of spinal pathways that lead to primary afferent depolarization and presynaptic inhibition. Visual detection and classification of these CDPs provides relevant information on the functional organization of the neural networks involved in the control of sensory information and allows the characterization of the changes produced by acute nerve and spinal lesions. We now present a novel feature extraction approach for signal classification, applied to CDP detection. The method is based on an intuitive procedure. We first remove by convolution the noise from the CDPs recorded in each given spinal segment. Then, we assign a coefficient for each main local maximum of the signal using its amplitude and distance to the most important maximum of the signal. These coefficients will be the input for the subsequent classification algorithm. In particular, we employ gradient boosting classification trees. This combination of approaches allows a faster and more accurate discrimination of CDPs than is obtained by other methods.

A preliminary study on ice shape tracing with a laser light sheet

NASA Technical Reports Server (NTRS)

Mercer, Carolyn R.; Vargas, Mario; Oldenburg, John R.

1993-01-01

Preliminary work towards the development of an automated method of measuring the shape of ice forming on an airfoil during wind tunnel tests has been completed. A thin sheet of light illuminated the front surfaces of rime, glaze, and mixed ice shapes and a solid-state camera recorded images of each. A maximum intensity algorithm extracted the profiles of the ice shapes and the results were compared to hand tracings. Very good general agreement was found in each case.

A mathematical theory of shape and neuro-fuzzy methodology-based diagnostic analysis: a comparative study on early detection and treatment planning of brain cancer.

PubMed

Kar, Subrata; Majumder, D Dutta

2017-08-01

Investigation of brain cancer can detect the abnormal growth of tissue in the brain using computed tomography (CT) scans and magnetic resonance (MR) images of patients. The proposed method classifies brain cancer on shape-based feature extraction as either benign or malignant. The authors used input variables such as shape distance (SD) and shape similarity measure (SSM) in fuzzy tools, and used fuzzy rules to evaluate the risk status as an output variable. We presented a classifier neural network system (NNS), namely Levenberg-Marquardt (LM), which is a feed-forward back-propagation learning algorithm used to train the NN for the status of brain cancer, if any, and which achieved satisfactory performance with 100% accuracy. The proposed methodology is divided into three phases. First, we find the region of interest (ROI) in the brain to detect the tumors using CT and MR images. Second, we extract the shape-based features, like SD and SSM, and grade the brain tumors as benign or malignant with the concept of SD function and SSM as shape-based parameters. Third, we classify the brain cancers using neuro-fuzzy tools. In this experiment, we used a 16-sample database with SSM (μ) values and classified the benignancy or malignancy of the brain tumor lesions using the neuro-fuzzy system (NFS). We have developed a fuzzy expert system (FES) and NFS for early detection of brain cancer from CT and MR images. In this experiment, shape-based features, such as SD and SSM, were extracted from the ROI of brain tumor lesions. These shape-based features were considered as input variables and, using fuzzy rules, we were able to evaluate brain cancer risk values for each case. We used an NNS with LM, a feed-forward back-propagation learning algorithm, as a classifier for the diagnosis of brain cancer and achieved satisfactory performance with 100% accuracy. The proposed network was trained with MR image datasets of 16 cases. The 16 cases were fed to the ANN with 2 input neurons, one hidden layer of 10 neurons and 2 output neurons. Of the 16-sample database, 10 datasets for training, 3 datasets for validation, and 3 datasets for testing were used in the ANN classification system. From the SSM (µ) confusion matrix, the number of output datasets of true positive, false positive, true negative and false negative was 6, 0, 10, and 0, respectively. The sensitivity, specificity and accuracy were each equal to 100%. The method of diagnosing brain cancer presented in this study is a successful model to assist doctors in the screening and treatment of brain cancer patients. The presented FES successfully identified the presence of brain cancer in CT and MR images using the extracted shape-based features and the use of NFS for the identification of brain cancer in the early stages. From the analysis and diagnosis of the disease, the doctors can decide the stage of cancer and take the necessary steps for more accurate treatment. Here, we have presented an investigation and comparison study of the shape-based feature extraction method with the use of NFS for classifying brain tumors as showing normal or abnormal patterns. The results have proved that the shape-based features with the use of NFS can achieve a satisfactory performance with 100% accuracy. We intend to extend this methodology for the early detection of cancer in other regions such as the prostate region and human cervix.

Optimized lighting method of applying shaped-function signal for increasing the dynamic range of LED-multispectral imaging system

NASA Astrophysics Data System (ADS)

Yang, Xue; Hu, Yajia; Li, Gang; Lin, Ling

2018-02-01

This paper proposes an optimized lighting method of applying a shaped-function signal for increasing the dynamic range of light emitting diode (LED)-multispectral imaging system. The optimized lighting method is based on the linear response zone of the analog-to-digital conversion (ADC) and the spectral response of the camera. The auxiliary light at a higher sensitivity-camera area is introduced to increase the A/D quantization levels that are within the linear response zone of ADC and improve the signal-to-noise ratio. The active light is modulated by the shaped-function signal to improve the gray-scale resolution of the image. And the auxiliary light is modulated by the constant intensity signal, which is easy to acquire the images under the active light irradiation. The least square method is employed to precisely extract the desired images. One wavelength in multispectral imaging based on LED illumination was taken as an example. It has been proven by experiments that the gray-scale resolution and the accuracy of information of the images acquired by the proposed method were both significantly improved. The optimum method opens up avenues for the hyperspectral imaging of biological tissue.

Optimized lighting method of applying shaped-function signal for increasing the dynamic range of LED-multispectral imaging system.

PubMed

Yang, Xue; Hu, Yajia; Li, Gang; Lin, Ling

2018-02-01

This paper proposes an optimized lighting method of applying a shaped-function signal for increasing the dynamic range of light emitting diode (LED)-multispectral imaging system. The optimized lighting method is based on the linear response zone of the analog-to-digital conversion (ADC) and the spectral response of the camera. The auxiliary light at a higher sensitivity-camera area is introduced to increase the A/D quantization levels that are within the linear response zone of ADC and improve the signal-to-noise ratio. The active light is modulated by the shaped-function signal to improve the gray-scale resolution of the image. And the auxiliary light is modulated by the constant intensity signal, which is easy to acquire the images under the active light irradiation. The least square method is employed to precisely extract the desired images. One wavelength in multispectral imaging based on LED illumination was taken as an example. It has been proven by experiments that the gray-scale resolution and the accuracy of information of the images acquired by the proposed method were both significantly improved. The optimum method opens up avenues for the hyperspectral imaging of biological tissue.

Automated analysis of biological oscillator models using mode decomposition.

PubMed

Konopka, Tomasz

2011-04-01

Oscillating signals produced by biological systems have shapes, described by their Fourier spectra, that can potentially reveal the mechanisms that generate them. Extracting this information from measured signals is interesting for the validation of theoretical models, discovery and classification of interaction types, and for optimal experiment design. An automated workflow is described for the analysis of oscillating signals. A software package is developed to match signal shapes to hundreds of a priori viable model structures defined by a class of first-order differential equations. The package computes parameter values for each model by exploiting the mode decomposition of oscillating signals and formulating the matching problem in terms of systems of simultaneous polynomial equations. On the basis of the computed parameter values, the software returns a list of models consistent with the data. In validation tests with synthetic datasets, it not only shortlists those model structures used to generate the data but also shows that excellent fits can sometimes be achieved with alternative equations. The listing of all consistent equations is indicative of how further invalidation might be achieved with additional information. When applied to data from a microarray experiment on mice, the procedure finds several candidate model structures to describe interactions related to the circadian rhythm. This shows that experimental data on oscillators is indeed rich in information about gene regulation mechanisms. The software package is available at http://babylone.ulb.ac.be/autoosc/.

Gesture-Controlled Interfaces for Self-Service Machines

NASA Technical Reports Server (NTRS)

Cohen, Charles J.; Beach, Glenn

2006-01-01

Gesture-controlled interfaces are software- driven systems that facilitate device control by translating visual hand and body signals into commands. Such interfaces could be especially attractive for controlling self-service machines (SSMs) for example, public information kiosks, ticket dispensers, gasoline pumps, and automated teller machines (see figure). A gesture-controlled interface would include a vision subsystem comprising one or more charge-coupled-device video cameras (at least two would be needed to acquire three-dimensional images of gestures). The output of the vision system would be processed by a pure software gesture-recognition subsystem. Then a translator subsystem would convert a sequence of recognized gestures into commands for the SSM to be controlled; these could include, for example, a command to display requested information, change control settings, or actuate a ticket- or cash-dispensing mechanism. Depending on the design and operational requirements of the SSM to be controlled, the gesture-controlled interface could be designed to respond to specific static gestures, dynamic gestures, or both. Static and dynamic gestures can include stationary or moving hand signals, arm poses or motions, and/or whole-body postures or motions. Static gestures would be recognized on the basis of their shapes; dynamic gestures would be recognized on the basis of both their shapes and their motions. Because dynamic gestures include temporal as well as spatial content, this gesture- controlled interface can extract more information from dynamic than it can from static gestures.

GIS prospectivity mapping and 3D modeling validation for potential uranium deposit targets in Shangnan district, China

NASA Astrophysics Data System (ADS)

Xie, Jiayu; Wang, Gongwen; Sha, Yazhou; Liu, Jiajun; Wen, Botao; Nie, Ming; Zhang, Shuai

2017-04-01

Integrating multi-source geoscience information (such as geology, geophysics, geochemistry, and remote sensing) using GIS mapping is one of the key topics and frontiers in quantitative geosciences for mineral exploration. GIS prospective mapping and three-dimensional (3D) modeling can be used not only to extract exploration criteria and delineate metallogenetic targets but also to provide important information for the quantitative assessment of mineral resources. This paper uses the Shangnan district of Shaanxi province (China) as a case study area. GIS mapping and potential granite-hydrothermal uranium targeting were conducted in the study area combining weights of evidence (WofE) and concentration-area (C-A) fractal methods with multi-source geoscience information. 3D deposit-scale modeling using GOCAD software was performed to validate the shapes and features of the potential targets at the subsurface. The research results show that: (1) the known deposits have potential zones at depth, and the 3D geological models can delineate surface or subsurface ore-forming features, which can be used to analyze the uncertainty of the shape and feature of prospectivity mapping at the subsurface; (2) single geochemistry anomalies or remote sensing anomalies at the surface require combining the depth exploration criteria of geophysics to identify potential targets; and (3) the single or sparse exploration criteria zone with few mineralization spots at the surface has high uncertainty in terms of the exploration target.

Tree branch-shaped cupric oxide for highly effective photoelectrochemical water reduction

NASA Astrophysics Data System (ADS)

Jang, Youn Jeong; Jang, Ji-Wook; Choi, Sun Hee; Kim, Jae Young; Kim, Ju Hun; Youn, Duck Hyun; Kim, Won Yong; Han, Suenghoon; Sung Lee, Jae

2015-04-01

Highly efficient tree branch-shaped CuO photocathodes are fabricated using the hybrid microwave annealing process with a silicon susceptor within 10 minutes. The unique hierarchical, one-dimensional structure provides more facile charge transport, larger surface areas, and increased crystallinity and crystal ordering with less defects compared to irregular-shaped CuO prepared by conventional thermal annealing. As a result, the photocathode fabricated with the tree branch-shaped CuO produces an unprecedently high photocurrent density of -4.4 mA cm-2 at 0 VRHE under AM 1.5 G simulated sunlight compared to -1.44 mA cm-2 observed for a photocathode fabricated by thermal annealing. It is also confirmed that stoichiometric hydrogen and oxygen are produced from photoelectrochemical water splitting on the tree branch-shaped CuO photocathode and a platinum anode.Highly efficient tree branch-shaped CuO photocathodes are fabricated using the hybrid microwave annealing process with a silicon susceptor within 10 minutes. The unique hierarchical, one-dimensional structure provides more facile charge transport, larger surface areas, and increased crystallinity and crystal ordering with less defects compared to irregular-shaped CuO prepared by conventional thermal annealing. As a result, the photocathode fabricated with the tree branch-shaped CuO produces an unprecedently high photocurrent density of -4.4 mA cm-2 at 0 VRHE under AM 1.5 G simulated sunlight compared to -1.44 mA cm-2 observed for a photocathode fabricated by thermal annealing. It is also confirmed that stoichiometric hydrogen and oxygen are produced from photoelectrochemical water splitting on the tree branch-shaped CuO photocathode and a platinum anode. Electronic supplementary information (ESI) available: The detailed schematic diagram for the HMA process, XRD results, the temperature profile during HMA, derivative XANES results, TEM images, J-V curves, lists of previously reported copper oxide photocathode, and parameters extracted from EIS. See DOI: 10.1039/c5nr00208g

Mapping of an ultrasonic bath for ultrasound assisted extraction of mangiferin from Mangifera indica leaves.

PubMed

Kulkarni, Vrushali M; Rathod, Virendra K

2014-03-01

The present work deals with the mapping of an ultrasonic bath for the maximum extraction of mangiferin from Mangifera indica leaves. I3(-) liberation experiments (chemical transformations) and extraction (physical transformations) were carried out at different locations in an ultrasonic bath and compared. The experimental findings indicated a similar trend in variation in an ultrasonic bath by both these methods. Various parameters such as position and depth of vessel in an ultrasonic bath, diameter and shape of a vessel, frequency and input power which affect the extraction yield have been studied in detail. Maximum yield of mangiferin obtained was approximately 31 mg/g at optimized parameters: distance of 2.54 cm above the bottom of the bath, 7 cm diameter of vessel, flat bottom vessel, 6.35 cm liquid height, 122 W input power and 25 kHz frequency. The present work indicates that the position and depth of vessel in an ultrasonic bath, diameter and shape of a vessel, frequency and input power have significant effect on the extraction yield. This work can be used as a base for all ultrasonic baths to obtain maximum efficiency for ultrasound assisted extraction. Copyright © 2013 Elsevier B.V. All rights reserved.

Long term three dimensional tracking of orthodontic patients using registered cone beam CT and photogrammetry.

PubMed

Boulanger, Pierre; Flores-Mir, Carlos; Ramirez, Juan F; Mesa, Elizabeth; Branch, John W

2009-01-01

The measurements from registered images obtained from Cone Beam Computed Tomography (CBCT) and a photogrammetric sensor are used to track three-dimensional shape variations of orthodontic patients before and after their treatments. The methodology consists of five main steps: (1) the patient's bone and skin shapes are measured in 3D using the fusion of images from a CBCT and a photogrammetric sensor. (2) The bone shape is extracted from the CBCT data using a standard marching cube algorithm. (3) The bone and skin shape measurements are registered using titanium targets located on the head of the patient. (4) Using a manual segmentation technique the head and lower jaw geometry are extracted separately to deal with jaw motion at the different record visits. (5) Using natural features of the upper head the two datasets are then registered with each other and then compared to evaluate bone, teeth, and skin displacements before and after treatments. This procedure is now used at the University of Alberta orthodontic clinic.

A shape-based account for holistic face processing.

PubMed

Zhao, Mintao; Bülthoff, Heinrich H; Bülthoff, Isabelle

2016-04-01

Faces are processed holistically, so selective attention to 1 face part without any influence of the others often fails. In this study, 3 experiments investigated what type of facial information (shape or surface) underlies holistic face processing and whether generalization of holistic processing to nonexperienced faces requires extensive discrimination experience. Results show that facial shape information alone is sufficient to elicit the composite face effect (CFE), 1 of the most convincing demonstrations of holistic processing, whereas facial surface information is unnecessary (Experiment 1). The CFE is eliminated when faces differ only in surface but not shape information, suggesting that variation of facial shape information is necessary to observe holistic face processing (Experiment 2). Removing 3-dimensional (3D) facial shape information also eliminates the CFE, indicating the necessity of 3D shape information for holistic face processing (Experiment 3). Moreover, participants show similar holistic processing for faces with and without extensive discrimination experience (i.e., own- and other-race faces), suggesting that generalization of holistic processing to nonexperienced faces requires facial shape information, but does not necessarily require further individuation experience. These results provide compelling evidence that facial shape information underlies holistic face processing. This shape-based account not only offers a consistent explanation for previous studies of holistic face processing, but also suggests a new ground-in addition to expertise-for the generalization of holistic processing to different types of faces and to nonface objects. (c) 2016 APA, all rights reserved).

The relative contributions of facial shape and surface information to perceptions of attractiveness and dominance.

PubMed

Torrance, Jaimie S; Wincenciak, Joanna; Hahn, Amanda C; DeBruine, Lisa M; Jones, Benedict C

2014-01-01

Although many studies have investigated the facial characteristics that influence perceptions of others' attractiveness and dominance, the majority of these studies have focused on either the effects of shape information or surface information alone. Consequently, the relative contributions of facial shape and surface characteristics to attractiveness and dominance perceptions are unclear. To address this issue, we investigated the relationships between ratings of original versions of faces and ratings of versions in which either surface information had been standardized (i.e., shape-only versions) or shape information had been standardized (i.e., surface-only versions). For attractiveness and dominance judgments of both male and female faces, ratings of shape-only and surface-only versions independently predicted ratings of the original versions of faces. The correlations between ratings of original and shape-only versions and between ratings of original and surface-only versions differed only in two instances. For male attractiveness, ratings of original versions were more strongly related to ratings of surface-only than shape-only versions, suggesting that surface information is particularly important for men's facial attractiveness. The opposite was true for female physical dominance, suggesting that shape information is particularly important for women's facial physical dominance. In summary, our results indicate that both facial shape and surface information contribute to judgments of others' attractiveness and dominance, suggesting that it may be important to consider both sources of information in research on these topics.

3D-model building of the jaw impression

NASA Astrophysics Data System (ADS)

Ahmed, Moumen T.; Yamany, Sameh M.; Hemayed, Elsayed E.; Farag, Aly A.

1997-03-01

A novel approach is proposed to obtain a record of the patient's occlusion using computer vision. Data acquisition is obtained using intra-oral video cameras. The technique utilizes shape from shading to extract 3D information from 2D views of the jaw, and a novel technique for 3D data registration using genetic algorithms. The resulting 3D model can be used for diagnosis, treatment planning, and implant purposes. The overall purpose of this research is to develop a model-based vision system for orthodontics to replace traditional approaches. This system will be flexible, accurate, and will reduce the cost of orthodontic treatments.

Finger-Vein Verification Based on Multi-Features Fusion

PubMed Central

Qin, Huafeng; Qin, Lan; Xue, Lian; He, Xiping; Yu, Chengbo; Liang, Xinyuan

2013-01-01

This paper presents a new scheme to improve the performance of finger-vein identification systems. Firstly, a vein pattern extraction method to extract the finger-vein shape and orientation features is proposed. Secondly, to accommodate the potential local and global variations at the same time, a region-based matching scheme is investigated by employing the Scale Invariant Feature Transform (SIFT) matching method. Finally, the finger-vein shape, orientation and SIFT features are combined to further enhance the performance. The experimental results on databases of 426 and 170 fingers demonstrate the consistent superiority of the proposed approach. PMID:24196433

Modeling the Pulse Signal by Wave-Shape Function and Analyzing by Synchrosqueezing Transform

PubMed Central

Wang, Chun-Li; Yang, Yueh-Lung; Wu, Wen-Hsiang; Tsai, Tung-Hu; Chang, Hen-Hong

2016-01-01

We apply the recently developed adaptive non-harmonic model based on the wave-shape function, as well as the time-frequency analysis tool called synchrosqueezing transform (SST) to model and analyze oscillatory physiological signals. To demonstrate how the model and algorithm work, we apply them to study the pulse wave signal. By extracting features called the spectral pulse signature, and based on functional regression, we characterize the hemodynamics from the radial pulse wave signals recorded by the sphygmomanometer. Analysis results suggest the potential of the proposed signal processing approach to extract health-related hemodynamics features. PMID:27304979

Modeling the Pulse Signal by Wave-Shape Function and Analyzing by Synchrosqueezing Transform.

PubMed

Wu, Hau-Tieng; Wu, Han-Kuei; Wang, Chun-Li; Yang, Yueh-Lung; Wu, Wen-Hsiang; Tsai, Tung-Hu; Chang, Hen-Hong

2016-01-01

We apply the recently developed adaptive non-harmonic model based on the wave-shape function, as well as the time-frequency analysis tool called synchrosqueezing transform (SST) to model and analyze oscillatory physiological signals. To demonstrate how the model and algorithm work, we apply them to study the pulse wave signal. By extracting features called the spectral pulse signature, and based on functional regression, we characterize the hemodynamics from the radial pulse wave signals recorded by the sphygmomanometer. Analysis results suggest the potential of the proposed signal processing approach to extract health-related hemodynamics features.

Comprehensive analysis of NMR data using advanced line shape fitting.

PubMed

Niklasson, Markus; Otten, Renee; Ahlner, Alexandra; Andresen, Cecilia; Schlagnitweit, Judith; Petzold, Katja; Lundström, Patrik

2017-10-01

NMR spectroscopy is uniquely suited for atomic resolution studies of biomolecules such as proteins, nucleic acids and metabolites, since detailed information on structure and dynamics are encoded in positions and line shapes of peaks in NMR spectra. Unfortunately, accurate determination of these parameters is often complicated and time consuming, in part due to the need for different software at the various analysis steps and for validating the results. Here, we present an integrated, cross-platform and open-source software that is significantly more versatile than the typical line shape fitting application. The software is a completely redesigned version of PINT ( https://pint-nmr.github.io/PINT/ ). It features a graphical user interface and includes functionality for peak picking, editing of peak lists and line shape fitting. In addition, the obtained peak intensities can be used directly to extract, for instance, relaxation rates, heteronuclear NOE values and exchange parameters. In contrast to most available software the entire process from spectral visualization to preparation of publication-ready figures is done solely using PINT and often within minutes, thereby, increasing productivity for users of all experience levels. Unique to the software are also the outstanding tools for evaluating the quality of the fitting results and extensive, but easy-to-use, customization of the fitting protocol and graphical output. In this communication, we describe the features of the new version of PINT and benchmark its performance.

Vision-based stress estimation model for steel frame structures with rigid links

NASA Astrophysics Data System (ADS)

Park, Hyo Seon; Park, Jun Su; Oh, Byung Kwan

2017-07-01

This paper presents a stress estimation model for the safety evaluation of steel frame structures with rigid links using a vision-based monitoring system. In this model, the deformed shape of a structure under external loads is estimated via displacements measured by a motion capture system (MCS), which is a non-contact displacement measurement device. During the estimation of the deformed shape, the effective lengths of the rigid link ranges in the frame structure are identified. The radius of the curvature of the structural member to be monitored is calculated using the estimated deformed shape and is employed to estimate stress. Using MCS in the presented model, the safety of a structure can be assessed gauge-freely. In addition, because the stress is directly extracted from the radius of the curvature obtained from the measured deformed shape, information on the loadings and boundary conditions of the structure are not required. Furthermore, the model, which includes the identification of the effective lengths of the rigid links, can consider the influences of the stiffness of the connection and support on the deformation in the stress estimation. To verify the applicability of the presented model, static loading tests for a steel frame specimen were conducted. By comparing the stress estimated by the model with the measured stress, the validity of the model was confirmed.

Development and Feasibility Testing of Image-Guided Minimally Invasive Tissue for Diagnosis Treatment of Benign and Malignant Breast Disease

NASA Technical Reports Server (NTRS)

Jeffrey, Stefanie S.

1999-01-01

Dr. Robert Mah and Dr. Stefanie Jeffrey worked on the development of the NASA Smart Probe in its application as a device to measure and interpret physiologic and image-based parameters of breast tissue. To date the following has been achieved: 1 . Choice of candidate sensors to be tested in breast tissue. 2. Preliminary designs for probe tip, specifically use of different tip shapes, cutting edges, and sensor configuration. 3. Design of sonographic guidance system. 4. Design of data extraction and analysis tool using scanned information of images of the breast tissue to provide a higher dimension of information for breast tissue characterization and interpretation. 5. Initial ex-vivo (fruit and tofu) and in-vivo (rodent) testing to confirm unique substance and tissue characterization by the Smart Probe software.

PVA/NaCl/MgO nanocomposites-microstructural analysis by whole pattern fitting method

NASA Astrophysics Data System (ADS)

Prashanth, K. S.; Mahesh, S. S.; Prakash, M. B. Nanda; Somashekar, R.; Nagabhushana, B. M.

2018-04-01

The nanofillers in the macromolecular matrix have displayed noteworthy changes in the structure and reactivity of the polymer nanocomposites. Novel functional materials usually consist of defects and are largely disordered. The intriguing properties of these materials are often attributed to defects. X-ray line profiles from powder diffraction reveal the quantitative information about size distribution and shape of diffracting domains which governs the contribution from small conventional X-ray diffraction (XRD) techniques to enumerate the microstructural information. In this study the MgO nanoparticles were prepared by solution combustion method and PVA/NaCl/MgO nanocomposite films were synthesized by the solvent cast method. Microstructural parameters viz crystal defects like stacking faults and twin faults, compositional inhomogeneity, crystallite size and lattice strain (g in %), were extracted using whole pattern fitting method.

Computer image analysis in obtaining characteristics of images: greenhouse tomatoes in the process of generating learning sets of artificial neural networks

NASA Astrophysics Data System (ADS)

Zaborowicz, M.; Przybył, J.; Koszela, K.; Boniecki, P.; Mueller, W.; Raba, B.; Lewicki, A.; Przybył, K.

2014-04-01

The aim of the project was to make the software which on the basis on image of greenhouse tomato allows for the extraction of its characteristics. Data gathered during the image analysis and processing were used to build learning sets of artificial neural networks. Program enables to process pictures in jpeg format, acquisition of statistical information of the picture and export them to an external file. Produced software is intended to batch analyze collected research material and obtained information saved as a csv file. Program allows for analysis of 33 independent parameters implicitly to describe tested image. The application is dedicated to processing and image analysis of greenhouse tomatoes. The program can be used for analysis of other fruits and vegetables of a spherical shape.

Temperature Measurements in Dynamically-loaded Systems Using Neutron Resonance Spectroscopy (NRS) at LANSCE

NASA Astrophysics Data System (ADS)

Yuan, V. W.

2002-12-01

In previous attempts to determine the internal temperature in systems subjected to dynamic loading, experimenters have usually relied on surface-based optical techniques that are often hampered by insufficient information regarding the emissivity of the surfaces under study. Neutron Resonance Spectroscopy (NRS) is a technique that uses Doppler-broadened neutron resonances to measure internal temperatures in dynamically-loaded samples. NRS has developed its own target-moderator assembly to provide single pulses with an order of magnitude higher brightness than the Lujan production target. The resonance line shapes from which temperature information is extracted are also influenced by non-temperature-dependent broadening from the moderator and detector phosphorescence. Dynamic NRS experiments have been performed to measure the temperature in a silver sheet jet and behind the passage of a shock wave in molybdenum.

Mom's shadow: structure-from-motion in newly hatched chicks as revealed by an imprinting procedure.

PubMed

Mascalzoni, Elena; Regolin, Lucia; Vallortigara, Giorgio

2009-03-01

The ability to recognize three-dimensional objects from two-dimensional (2-D) displays was investigated in domestic chicks, focusing on the role of the object's motion. In Experiment 1 newly hatched chicks, imprinted on a three-dimensional (3-D) object, were allowed to choose between the shadows of the familiar object and of an object never seen before. In Experiments 2 and 3 random-dot displays were used to produce the perception of a solid shape only when set in motion. Overall, the results showed that domestic chicks were able to recognize familiar shapes from 2-D motion stimuli. It is likely that similar general mechanisms underlying the perception of structure-from-motion and the extraction of 3-D information are shared by humans and animals. The present data shows that they occur similarly in birds as known for mammals, two separate vertebrate classes; this possibly indicates a common phylogenetic origin of these processes.

Electron paramagnetic resonance studies of slowly tumbling vanadyl spin probes in nematic liquid crystals

NASA Technical Reports Server (NTRS)

Bruno, G. V.; Harrington, J. K.; Eastman, M. P.

1978-01-01

The purposes of this vanadyl spin probe study are threefold: (1) to establish when the breakdown of motionally narrowed formulas occurs; (2) to analyze the experimental vanadyl EPR line shapes by the stochastic Lioville method as developed by Polnaszek et al. (1973) for slow tumbling in an anisotropic liquid; and (3) to compare the vanadyl probe study results with those of Polnaszek and Freed (1975). Spectral EPR line shapes are simulated for experimental spectra of vanadyl acetylacetonate (VOAA) in nematic liquid crystal butyl p-(p-ethoxyphenoxycarbonyl) phenyl carbonate (BEPC) and Phase V of EM laboratories. It is shown that the use of typical vanadyl complexes as spin probes for nematic liquid crystals simplifies the theoretical analysis and the subsequent interpretation. Guidelines for the breakdown of motionally narrowed formulas are established. Both the slow tumbling aspects and the effects of non-Brownian rotation should be resolved in order to extract quantitative information about molecular ordering and rotational mobility.

Automated grain extraction and classification by combining improved region growing segmentation and shape descriptors in electromagnetic mill classification system

NASA Astrophysics Data System (ADS)

Budzan, Sebastian

2018-04-01

In this paper, the automatic method of grain detection and classification has been presented. As input, it uses a single digital image obtained from milling process of the copper ore with an high-quality digital camera. The grinding process is an extremely energy and cost consuming process, thus granularity evaluation process should be performed with high efficiency and time consumption. The method proposed in this paper is based on the three-stage image processing. First, using Seeded Region Growing (SRG) segmentation with proposed adaptive thresholding based on the calculation of Relative Standard Deviation (RSD) all grains are detected. In the next step results of the detection are improved using information about the shape of the detected grains using distance map. Finally, each grain in the sample is classified into one of the predefined granularity class. The quality of the proposed method has been obtained by using nominal granularity samples, also with a comparison to the other methods.

Experimental Detection of the Intrinsic Difference in Raman Optical Activity of a Photoreceptor Protein under Preresonance and Resonance Conditions.

PubMed

Haraguchi, Shojiro; Hara, Miwa; Shingae, Takahito; Kumauchi, Masato; Hoff, Wouter D; Unno, Masashi

2015-09-21

Raman optical activity (ROA) is an advanced technique capable of detecting structural deformations of light-absorbing molecules embedded in chromophoric proteins. Resonance Raman (RR) spectroscopy is widely used to enhance the band intensities. However, theoretical work has predicted that under resonance conditions the ROA spectrum resembles the shape of the RR spectrum. Herein, we use photoactive yellow protein (PYP) to measure the first experimental data on the effect of changing the excitation wavelength on the ROA spectra of a protein. We observe a close similarity between the shape of the RR spectrum and the resonance ROA spectrum of PYP. Furthermore, we experimentally verify the theoretical prediction concerning the ratio of the amplitudes of the ROA and Raman spectra. Our data demonstrate that selecting an appropriate excitation wavelength is a key factor for extracting structural information on a protein active site using ROA spectroscopy. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Spot detection and image segmentation in DNA microarray data.

PubMed

Qin, Li; Rueda, Luis; Ali, Adnan; Ngom, Alioune

2005-01-01

Following the invention of microarrays in 1994, the development and applications of this technology have grown exponentially. The numerous applications of microarray technology include clinical diagnosis and treatment, drug design and discovery, tumour detection, and environmental health research. One of the key issues in the experimental approaches utilising microarrays is to extract quantitative information from the spots, which represent genes in a given experiment. For this process, the initial stages are important and they influence future steps in the analysis. Identifying the spots and separating the background from the foreground is a fundamental problem in DNA microarray data analysis. In this review, we present an overview of state-of-the-art methods for microarray image segmentation. We discuss the foundations of the circle-shaped approach, adaptive shape segmentation, histogram-based methods and the recently introduced clustering-based techniques. We analytically show that clustering-based techniques are equivalent to the one-dimensional, standard k-means clustering algorithm that utilises the Euclidean distance.

Analysis and Recognition of Curve Type as The Basis of Object Recognition in Image

NASA Astrophysics Data System (ADS)

Nugraha, Nurma; Madenda, Sarifuddin; Indarti, Dina; Dewi Agushinta, R.; Ernastuti

2016-06-01

An object in an image when analyzed further will show the characteristics that distinguish one object with another object in an image. Characteristics that are used in object recognition in an image can be a color, shape, pattern, texture and spatial information that can be used to represent objects in the digital image. The method has recently been developed for image feature extraction on objects that share characteristics curve analysis (simple curve) and use the search feature of chain code object. This study will develop an algorithm analysis and the recognition of the type of curve as the basis for object recognition in images, with proposing addition of complex curve characteristics with maximum four branches that will be used for the process of object recognition in images. Definition of complex curve is the curve that has a point of intersection. By using some of the image of the edge detection, the algorithm was able to do the analysis and recognition of complex curve shape well.

Frequency domain analysis of knock images

NASA Astrophysics Data System (ADS)

Qi, Yunliang; He, Xin; Wang, Zhi; Wang, Jianxin

2014-12-01

High speed imaging-based knock analysis has mainly focused on time domain information, e.g. the spark triggered flame speed, the time when end gas auto-ignition occurs and the end gas flame speed after auto-ignition. This study presents a frequency domain analysis on the knock images recorded using a high speed camera with direct photography in a rapid compression machine (RCM). To clearly visualize the pressure wave oscillation in the combustion chamber, the images were high-pass-filtered to extract the luminosity oscillation. The luminosity spectrum was then obtained by applying fast Fourier transform (FFT) to three basic colour components (red, green and blue) of the high-pass-filtered images. Compared to the pressure spectrum, the luminosity spectra better identify the resonant modes of pressure wave oscillation. More importantly, the resonant mode shapes can be clearly visualized by reconstructing the images based on the amplitudes of luminosity spectra at the corresponding resonant frequencies, which agree well with the analytical solutions for mode shapes of gas vibration in a cylindrical cavity.

Automated Morphological and Morphometric Analysis of Mass Spectrometry Imaging Data: Application to Biomarker Discovery

NASA Astrophysics Data System (ADS)

Picard de Muller, Gaël; Ait-Belkacem, Rima; Bonnel, David; Longuespée, Rémi; Stauber, Jonathan

2017-12-01

Mass spectrometry imaging datasets are mostly analyzed in terms of average intensity in regions of interest. However, biological tissues have different morphologies with several sizes, shapes, and structures. The important biological information, contained in this highly heterogeneous cellular organization, could be hidden by analyzing the average intensities. Finding an analytical process of morphology would help to find such information, describe tissue model, and support identification of biomarkers. This study describes an informatics approach for the extraction and identification of mass spectrometry image features and its application to sample analysis and modeling. For the proof of concept, two different tissue types (healthy kidney and CT-26 xenograft tumor tissues) were imaged and analyzed. A mouse kidney model and tumor model were generated using morphometric - number of objects and total surface - information. The morphometric information was used to identify m/z that have a heterogeneous distribution. It seems to be a worthwhile pursuit as clonal heterogeneity in a tumor is of clinical relevance. This study provides a new approach to find biomarker or support tissue classification with more information. [Figure not available: see fulltext.

Auto-Context Convolutional Neural Network (Auto-Net) for Brain Extraction in Magnetic Resonance Imaging.

PubMed

Mohseni Salehi, Seyed Sadegh; Erdogmus, Deniz; Gholipour, Ali

2017-11-01

Brain extraction or whole brain segmentation is an important first step in many of the neuroimage analysis pipelines. The accuracy and the robustness of brain extraction, therefore, are crucial for the accuracy of the entire brain analysis process. The state-of-the-art brain extraction techniques rely heavily on the accuracy of alignment or registration between brain atlases and query brain anatomy, and/or make assumptions about the image geometry, and therefore have limited success when these assumptions do not hold or image registration fails. With the aim of designing an accurate, learning-based, geometry-independent, and registration-free brain extraction tool, in this paper, we present a technique based on an auto-context convolutional neural network (CNN), in which intrinsic local and global image features are learned through 2-D patches of different window sizes. We consider two different architectures: 1) a voxelwise approach based on three parallel 2-D convolutional pathways for three different directions (axial, coronal, and sagittal) that implicitly learn 3-D image information without the need for computationally expensive 3-D convolutions and 2) a fully convolutional network based on the U-net architecture. Posterior probability maps generated by the networks are used iteratively as context information along with the original image patches to learn the local shape and connectedness of the brain to extract it from non-brain tissue. The brain extraction results we have obtained from our CNNs are superior to the recently reported results in the literature on two publicly available benchmark data sets, namely, LPBA40 and OASIS, in which we obtained the Dice overlap coefficients of 97.73% and 97.62%, respectively. Significant improvement was achieved via our auto-context algorithm. Furthermore, we evaluated the performance of our algorithm in the challenging problem of extracting arbitrarily oriented fetal brains in reconstructed fetal brain magnetic resonance imaging (MRI) data sets. In this application, our voxelwise auto-context CNN performed much better than the other methods (Dice coefficient: 95.97%), where the other methods performed poorly due to the non-standard orientation and geometry of the fetal brain in MRI. Through training, our method can provide accurate brain extraction in challenging applications. This, in turn, may reduce the problems associated with image registration in segmentation tasks.

Shape- and Size-Controlled Synthesis of Silver Nanoparticles Using Aloe vera Plant Extract and Their Antimicrobial Activity

NASA Astrophysics Data System (ADS)

Logaranjan, Kaliyaperumal; Raiza, Anasdass Jaculin; Gopinath, Subash C. B.; Chen, Yeng; Pandian, Kannaiyan

2016-11-01

Biogenic synthesis of silver nanoparticles (AgNP) was performed at room temperature using Aloe vera plant extract in the presence of ammoniacal silver nitrate as a metal salt precursor. The formation of AgNP was monitored by UV-visible spectroscopy at different time intervals. The shape and size of the synthesized particle were visualized by scanning electron microscopy (SEM) and transmission electron microscopy (TEM) observations. These results were confirmed by X-ray powder diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR) analyses and further supported by surface-enhanced Raman spectroscopy/Raman scattering (SERS) study. UV-visible spectrum has shown a sharp peak at 420 nm and further evidenced by FTIR peak profile (at 1587.6, 1386.4, and 1076 cm-1 with corresponding compounds). The main band position with SERS was noticed at 1594 cm-1 (C-C stretching vibration). When samples were heated under microwave radiation, AgNP with octahedron shapes with 5-50 nm were found and this method can be one of the easier ways to synthesis anisotropic AgNP, in which the plant extract plays a vital role to regulate the size and shape of the nanoparticles. Enhanced antibacterial effects (two- to fourfold) were observed in the case of Aloe vera plant protected AgNP than the routinely synthesized antibiotic drugs.

High-Sensitivity Ionization Trace-Species Detector

NASA Technical Reports Server (NTRS)

Bernius, Mark T.; Chutjian, Ara

1990-01-01

Features include high ion-extraction efficiency, compactness, and light weight. Improved version of previous ionization detector features in-line geometry that enables extraction of almost every ion from region of formation. Focusing electrodes arranged and shaped into compact system of space-charge-limited reversal electron optics and ion-extraction optics. Provides controllability of ionizing electron energies, greater efficiency of ionization, and nearly 100 percent ion-collection efficiency.

Extraction of temporal information in functional MRI

NASA Astrophysics Data System (ADS)

Singh, M.; Sungkarat, W.; Jeong, Jeong-Won; Zhou, Yongxia

2002-10-01

The temporal resolution of functional MRI (fMRI) is limited by the shape of the haemodynamic response function (hrf) and the vascular architecture underlying the activated regions. Typically, the temporal resolution of fMRI is on the order of 1 s. We have developed a new data processing approach to extract temporal information on a pixel-by-pixel basis at the level of 100 ms from fMRI data. Instead of correlating or fitting the time-course of each pixel to a single reference function, which is the common practice in fMRI, we correlate each pixel's time-course to a series of reference functions that are shifted with respect to each other by 100 ms. The reference function yielding the highest correlation coefficient for a pixel is then used as a time marker for that pixel. A Monte Carlo simulation and experimental study of this approach were performed to estimate the temporal resolution as a function of signal-to-noise ratio (SNR) in the time-course of a pixel. Assuming a known and stationary hrf, the simulation and experimental studies suggest a lower limit in the temporal resolution of approximately 100 ms at an SNR of 3. The multireference function approach was also applied to extract timing information from an event-related motor movement study where the subjects flexed a finger on cue. The event was repeated 19 times with the event's presentation staggered to yield an approximately 100-ms temporal sampling of the haemodynamic response over the entire presentation cycle. The timing differences among different regions of the brain activated by the motor task were clearly visualized and quantified by this method. The results suggest that it is possible to achieve a temporal resolution of /spl sim/200 ms in practice with this approach.

Activity of hawthorn leaf and bark extracts in relation to biological membrane.

PubMed

Włoch, Aleksandra; Kapusta, Ireneusz; Bielecki, Krzysztof; Oszmiański, Jan; Kleszczyńska, Halina

2013-07-01

The aim of the study was to identify and determine the percent content of polyphenols in extracts from leaves and hawthorn bark, to examine the effect of the extracts on the properties of the biological membrane as well as to determine their antioxidant activity toward membrane lipids. In particular, a biophysical investigation was conducted on the effect of hawthorn extracts on the osmotic resistance and morphology of erythrocyte cells and on the packing of the heads of membrane lipids. Analysis of the polyphenol content of extracts used the HPLC method. Analysis of the polyphenol composition has shown a dominant share of procyanidins and epicatechin in both extracts. The research showed that the polyphenolic compounds contained in hawthorn extracts are incorporated mainly into the hydrophilic part of the erythrocyte membrane, inducing echinocyte shapes. They also diminish the packing order of the lipid polar heads of the membrane, as evidenced by the lowered generalized polarization values of Laurdan. The substances used induced increased osmotic pressure of erythrocytes, making them less sensitive to changes in osmotic pressure. The presence of the extract compounds in the outer hydrophilic part of the erythrocyte membrane, evidenced by examination of the shapes and packing in the hydrophilic part of membrane, indicates that the substances constitute a kind of barrier that protects the erythrocyte membrane against free radicals, while the membrane-bound extracts do not disturb the membrane structure and, thus, do not cause any side effects.

Extraction of Extended Small-Scale Objects in Digital Images

NASA Astrophysics Data System (ADS)

Volkov, V. Y.

2015-05-01

Detection and localization problem of extended small-scale objects with different shapes appears in radio observation systems which use SAR, infra-red, lidar and television camera. Intensive non-stationary background is the main difficulty for processing. Other challenge is low quality of images, blobs, blurred boundaries; in addition SAR images suffer from a serious intrinsic speckle noise. Statistics of background is not normal, it has evident skewness and heavy tails in probability density, so it is hard to identify it. The problem of extraction small-scale objects is solved here on the basis of directional filtering, adaptive thresholding and morthological analysis. New kind of masks is used which are open-ended at one side so it is possible to extract ends of line segments with unknown length. An advanced method of dynamical adaptive threshold setting is investigated which is based on isolated fragments extraction after thresholding. Hierarchy of isolated fragments on binary image is proposed for the analysis of segmentation results. It includes small-scale objects with different shape, size and orientation. The method uses extraction of isolated fragments in binary image and counting points in these fragments. Number of points in extracted fragments is normalized to the total number of points for given threshold and is used as effectiveness of extraction for these fragments. New method for adaptive threshold setting and control maximises effectiveness of extraction. It has optimality properties for objects extraction in normal noise field and shows effective results for real SAR images.

How Nonlinear-Type Time-Frequency Analysis Can Help in Sensing Instantaneous Heart Rate and Instantaneous Respiratory Rate from Photoplethysmography in a Reliable Way

PubMed Central

Cicone, Antonio; Wu, Hau-Tieng

2017-01-01

Despite the population of the noninvasive, economic, comfortable, and easy-to-install photoplethysmography (PPG), it is still lacking a mathematically rigorous and stable algorithm which is able to simultaneously extract from a single-channel PPG signal the instantaneous heart rate (IHR) and the instantaneous respiratory rate (IRR). In this paper, a novel algorithm called deppG is provided to tackle this challenge. deppG is composed of two theoretically solid nonlinear-type time-frequency analyses techniques, the de-shape short time Fourier transform and the synchrosqueezing transform, which allows us to extract the instantaneous physiological information from the PPG signal in a reliable way. To test its performance, in addition to validating the algorithm by a simulated signal and discussing the meaning of “instantaneous,” the algorithm is applied to two publicly available batch databases, the Capnobase and the ICASSP 2015 signal processing cup. The former contains PPG signals relative to spontaneous or controlled breathing in static patients, and the latter is made up of PPG signals collected from subjects doing intense physical activities. The accuracies of the estimated IHR and IRR are compared with the ones obtained by other methods, and represent the state-of-the-art in this field of research. The results suggest the potential of deppG to extract instantaneous physiological information from a signal acquired from widely available wearable devices, even when a subject carries out intense physical activities. PMID:29018352

Information mining in remote sensing imagery

NASA Astrophysics Data System (ADS)

Li, Jiang

The volume of remotely sensed imagery continues to grow at an enormous rate due to the advances in sensor technology, and our capability for collecting and storing images has greatly outpaced our ability to analyze and retrieve information from the images. This motivates us to develop image information mining techniques, which is very much an interdisciplinary endeavor drawing upon expertise in image processing, databases, information retrieval, machine learning, and software design. This dissertation proposes and implements an extensive remote sensing image information mining (ReSIM) system prototype for mining useful information implicitly stored in remote sensing imagery. The system consists of three modules: image processing subsystem, database subsystem, and visualization and graphical user interface (GUI) subsystem. Land cover and land use (LCLU) information corresponding to spectral characteristics is identified by supervised classification based on support vector machines (SVM) with automatic model selection, while textural features that characterize spatial information are extracted using Gabor wavelet coefficients. Within LCLU categories, textural features are clustered using an optimized k-means clustering approach to acquire search efficient space. The clusters are stored in an object-oriented database (OODB) with associated images indexed in an image database (IDB). A k-nearest neighbor search is performed using a query-by-example (QBE) approach. Furthermore, an automatic parametric contour tracing algorithm and an O(n) time piecewise linear polygonal approximation (PLPA) algorithm are developed for shape information mining of interesting objects within the image. A fuzzy object-oriented database based on the fuzzy object-oriented data (FOOD) model is developed to handle the fuzziness and uncertainty. Three specific applications are presented: integrated land cover and texture pattern mining, shape information mining for change detection of lakes, and fuzzy normalized difference vegetation index (NDVI) pattern mining. The study results show the effectiveness of the proposed system prototype and the potentials for other applications in remote sensing.

Can SNOMED CT be squeezed without losing its shape?

PubMed

López-García, Pablo; Schulz, Stefan

2016-09-21

In biomedical applications where the size and complexity of SNOMED CT become problematic, using a smaller subset that can act as a reasonable substitute is usually preferred. In a special class of use cases-like ontology-based quality assurance, or when performing scaling experiments for real-time performance-it is essential that modules show a similar shape than SNOMED CT in terms of concept distribution per sub-hierarchy. Exactly how to extract such balanced modules remains unclear, as most previous work on ontology modularization has focused on other problems. In this study, we investigate to what extent extracting balanced modules that preserve the original shape of SNOMED CT is possible, by presenting and evaluating an iterative algorithm. We used a graph-traversal modularization approach based on an input signature. To conform to our definition of a balanced module, we implemented an iterative algorithm that carefully bootstraped and dynamically adjusted the signature at each step. We measured the error for each sub-hierarchy and defined convergence as a residual sum of squares <1. Using 2000 concepts as an initial signature, our algorithm converged after seven iterations and extracted a module 4.7 % the size of SNOMED CT. Seven sub-hierarhies were either over or under-represented within a range of 1-8 %. Our study shows that balanced modules from large terminologies can be extracted using ontology graph-traversal modularization techniques under certain conditions: that the process is repeated a number of times, the input signature is dynamically adjusted in each iteration, and a moderate under/over-representation of some hierarchies is tolerated. In the case of SNOMED CT, our results conclusively show that it can be squeezed to less than 5 % of its size without any sub-hierarchy losing its shape more than 8 %, which is likely sufficient in most use cases.

Effective and easy to use extraction method shows low numbers of microplastics in offshore planktivorous fish from the northern Baltic Sea.

PubMed

Budimir, Stjepan; Setälä, Outi; Lehtiniemi, Maiju

2018-02-01

Although the presence of microplastics in marine biota has been widely recorded, extraction methods, method validation and approaches to monitoring are not standardized. In this study a method for microplastic extraction from fish guts based on a chemical alkaline digestion is presented. The average particle retrieval rate from spiked fish guts, used for method validation, was 84%. The weight and shape of the test particles (PET, PC, HD-PE) were also analysed with no noticeable changes in any particle shapes and only minor weight change in PET (2.63%). Microplastics were found in 1.8% of herrings (n=164) and in 0.9% of sprat (n=154). None of the three-spined sticklebacks (n=355) contained microplastic particles. Copyright © 2018 Elsevier Ltd. All rights reserved.

Velocity-image model for online signature verification.

PubMed

Khan, Mohammad A U; Niazi, Muhammad Khalid Khan; Khan, Muhammad Aurangzeb

2006-11-01

In general, online signature capturing devices provide outputs in the form of shape and velocity signals. In the past, strokes have been extracted while tracking velocity signal minimas. However, the resulting strokes are larger and complicated in shape and thus make the subsequent job of generating a discriminative template difficult. We propose a new stroke-based algorithm that splits velocity signal into various bands. Based on these bands, strokes are extracted which are smaller and more simpler in nature. Training of our proposed system revealed that low- and high-velocity bands of the signal are unstable, whereas the medium-velocity band can be used for discrimination purposes. Euclidean distances of strokes extracted on the basis of medium velocity band are used for verification purpose. The experiments conducted show improvement in discriminative capability of the proposed stroke-based system.

Development of Automated Tracking System with Active Cameras for Figure Skating

NASA Astrophysics Data System (ADS)

Haraguchi, Tomohiko; Taki, Tsuyoshi; Hasegawa, Junichi

This paper presents a system based on the control of PTZ cameras for automated real-time tracking of individual figure skaters moving on an ice rink. In the video images of figure skating, irregular trajectories, various postures, rapid movements, and various costume colors are included. Therefore, it is difficult to determine some features useful for image tracking. On the other hand, an ice rink has a limited area and uniform high intensity, and skating is always performed on ice. In the proposed system, an ice rink region is first extracted from a video image by the region growing method, and then, a skater region is extracted using the rink shape information. In the camera control process, each camera is automatically panned and/or tilted so that the skater region is as close to the center of the image as possible; further, the camera is zoomed to maintain the skater image at an appropriate scale. The results of experiments performed for 10 training scenes show that the skater extraction rate is approximately 98%. Thus, it was concluded that tracking with camera control was successful for almost all the cases considered in the study.

Stacked sparse autoencoder in hyperspectral data classification using spectral-spatial, higher order statistics and multifractal spectrum features

NASA Astrophysics Data System (ADS)

Wan, Xiaoqing; Zhao, Chunhui; Wang, Yanchun; Liu, Wu

2017-11-01

This paper proposes a novel classification paradigm for hyperspectral image (HSI) using feature-level fusion and deep learning-based methodologies. Operation is carried out in three main steps. First, during a pre-processing stage, wave atoms are introduced into bilateral filter to smooth HSI, and this strategy can effectively attenuate noise and restore texture information. Meanwhile, high quality spectral-spatial features can be extracted from HSI by taking geometric closeness and photometric similarity among pixels into consideration simultaneously. Second, higher order statistics techniques are firstly introduced into hyperspectral data classification to characterize the phase correlations of spectral curves. Third, multifractal spectrum features are extracted to characterize the singularities and self-similarities of spectra shapes. To this end, a feature-level fusion is applied to the extracted spectral-spatial features along with higher order statistics and multifractal spectrum features. Finally, stacked sparse autoencoder is utilized to learn more abstract and invariant high-level features from the multiple feature sets, and then random forest classifier is employed to perform supervised fine-tuning and classification. Experimental results on two real hyperspectral data sets demonstrate that the proposed method outperforms some traditional alternatives.

Hierarchical representation of shapes in visual cortex—from localized features to figural shape segregation

PubMed Central

Tschechne, Stephan; Neumann, Heiko

2014-01-01

Visual structures in the environment are segmented into image regions and those combined to a representation of surfaces and prototypical objects. Such a perceptual organization is performed by complex neural mechanisms in the visual cortex of primates. Multiple mutually connected areas in the ventral cortical pathway receive visual input and extract local form features that are subsequently grouped into increasingly complex, more meaningful image elements. Such a distributed network of processing must be capable to make accessible highly articulated changes in shape boundary as well as very subtle curvature changes that contribute to the perception of an object. We propose a recurrent computational network architecture that utilizes hierarchical distributed representations of shape features to encode surface and object boundary over different scales of resolution. Our model makes use of neural mechanisms that model the processing capabilities of early and intermediate stages in visual cortex, namely areas V1–V4 and IT. We suggest that multiple specialized component representations interact by feedforward hierarchical processing that is combined with feedback signals driven by representations generated at higher stages. Based on this, global configurational as well as local information is made available to distinguish changes in the object's contour. Once the outline of a shape has been established, contextual contour configurations are used to assign border ownership directions and thus achieve segregation of figure and ground. The model, thus, proposes how separate mechanisms contribute to distributed hierarchical cortical shape representation and combine with processes of figure-ground segregation. Our model is probed with a selection of stimuli to illustrate processing results at different processing stages. We especially highlight how modulatory feedback connections contribute to the processing of visual input at various stages in the processing hierarchy. PMID:25157228

Hierarchical representation of shapes in visual cortex-from localized features to figural shape segregation.

PubMed

Tschechne, Stephan; Neumann, Heiko

2014-01-01

Visual structures in the environment are segmented into image regions and those combined to a representation of surfaces and prototypical objects. Such a perceptual organization is performed by complex neural mechanisms in the visual cortex of primates. Multiple mutually connected areas in the ventral cortical pathway receive visual input and extract local form features that are subsequently grouped into increasingly complex, more meaningful image elements. Such a distributed network of processing must be capable to make accessible highly articulated changes in shape boundary as well as very subtle curvature changes that contribute to the perception of an object. We propose a recurrent computational network architecture that utilizes hierarchical distributed representations of shape features to encode surface and object boundary over different scales of resolution. Our model makes use of neural mechanisms that model the processing capabilities of early and intermediate stages in visual cortex, namely areas V1-V4 and IT. We suggest that multiple specialized component representations interact by feedforward hierarchical processing that is combined with feedback signals driven by representations generated at higher stages. Based on this, global configurational as well as local information is made available to distinguish changes in the object's contour. Once the outline of a shape has been established, contextual contour configurations are used to assign border ownership directions and thus achieve segregation of figure and ground. The model, thus, proposes how separate mechanisms contribute to distributed hierarchical cortical shape representation and combine with processes of figure-ground segregation. Our model is probed with a selection of stimuli to illustrate processing results at different processing stages. We especially highlight how modulatory feedback connections contribute to the processing of visual input at various stages in the processing hierarchy.

Development of representative magnetic resonance imaging-based atlases of the canine brain and evaluation of three methods for atlas-based segmentation.

PubMed

Milne, Marjorie E; Steward, Christopher; Firestone, Simon M; Long, Sam N; O'Brien, Terrence J; Moffat, Bradford A

2016-04-01

To develop representative MRI atlases of the canine brain and to evaluate 3 methods of atlas-based segmentation (ABS). 62 dogs without clinical signs of epilepsy and without MRI evidence of structural brain disease. The MRI scans from 44 dogs were used to develop 4 templates on the basis of brain shape (brachycephalic, mesaticephalic, dolichocephalic, and combined mesaticephalic and dolichocephalic). Atlas labels were generated by segmenting the brain, ventricular system, hippocampal formation, and caudate nuclei. The MRI scans from the remaining 18 dogs were used to evaluate 3 methods of ABS (manual brain extraction and application of a brain shape-specific template [A], automatic brain extraction and application of a brain shape-specific template [B], and manual brain extraction and application of a combined template [C]). The performance of each ABS method was compared by calculation of the Dice and Jaccard coefficients, with manual segmentation used as the gold standard. Method A had the highest mean Jaccard coefficient and was the most accurate ABS method assessed. Measures of overlap for ABS methods that used manual brain extraction (A and C) ranged from 0.75 to 0.95 and compared favorably with repeated measures of overlap for manual extraction, which ranged from 0.88 to 0.97. Atlas-based segmentation was an accurate and repeatable method for segmentation of canine brain structures. It could be performed more rapidly than manual segmentation, which should allow the application of computer-assisted volumetry to large data sets and clinical cases and facilitate neuroimaging research and disease diagnosis.

Global shape information increases but color information decreases the composite face effect.

PubMed

Retter, Talia L; Rossion, Bruno

2015-01-01

The separation of visual shape and surface information may be useful for understanding holistic face perception--that is, the perception of a face as a single unit (Jiang, Blanz, & Rossion, 2011, Visual Cognition, 19, 1003-1034). A widely used measure of holistic face perception is the composite face effect (CFE), in which identical top face halves appear different when aligned with bottom face halves from different identities. In the present study the influences of global face shape (ie contour of the face) and color information on the CFE are investigated, with the hypothesis that global face shape supports but color impairs holistic face perception as measured in this paradigm. In experiment 1 the CFE is significantly increased when face stimuli possess natural global shape information than when cropped to a generic (ie oval) global shape; this effect is not found when the stimuli are presented inverted. In experiment 2 the CFE is significantly decreased when face stimuli are presented with color information than when presented in grayscale. These findings indicate that grayscale stimuli maintaining natural global face shape information provide the most adept measure of holistic face perception in the behavioral composite face paradigm. More generally, they show that reducing different types of information diagnostic for individual face perception can have opposite effects on the CFE, illustrating the functional dissociation between shape and surface information in face perception.

Extended morphological processing: a practical method for automatic spot detection of biological markers from microscopic images.

PubMed

Kimori, Yoshitaka; Baba, Norio; Morone, Nobuhiro

2010-07-08

A reliable extraction technique for resolving multiple spots in light or electron microscopic images is essential in investigations of the spatial distribution and dynamics of specific proteins inside cells and tissues. Currently, automatic spot extraction and characterization in complex microscopic images poses many challenges to conventional image processing methods. A new method to extract closely located, small target spots from biological images is proposed. This method starts with a simple but practical operation based on the extended morphological top-hat transformation to subtract an uneven background. The core of our novel approach is the following: first, the original image is rotated in an arbitrary direction and each rotated image is opened with a single straight line-segment structuring element. Second, the opened images are unified and then subtracted from the original image. To evaluate these procedures, model images of simulated spots with closely located targets were created and the efficacy of our method was compared to that of conventional morphological filtering methods. The results showed the better performance of our method. The spots of real microscope images can be quantified to confirm that the method is applicable in a given practice. Our method achieved effective spot extraction under various image conditions, including aggregated target spots, poor signal-to-noise ratio, and large variations in the background intensity. Furthermore, it has no restrictions with respect to the shape of the extracted spots. The features of our method allow its broad application in biological and biomedical image information analysis.

Phytochemical screening by LC-MS and LC-PDA of ethanolic extracts from the fruits of Kigelia africana (Lam.) Benth.

PubMed

Costa, Rosaria; Albergamo, Ambrogina; Pellizzeri, Vito; Dugo, Giacomo

2017-06-01

Kigelia africana is a tree native to Africa, with a local employment in numerous fields, ranging from traditional medicine to cosmetics and religious rituals. Parts of the plant generally used are stem bark, fruits, roots and leaves. The fruits, which have a singular 'sausage' shape, are widely exploited by local folk, in particular for applications/products involving genito-urinary apparatus of both human genders. The scope of this work was to make a consistent chemical investigation on this plant species, in order to clarify and increase the information at present available in literature. To this aim, ethanolic extracts of K. africana fruits were analysed by high-performance liquid chromatography with photodiode array (HPLC-PDA) and electrospray-mass spectrometry (HPLC-ESI-MS) detection, revealing the presence of polyphenols and iridoids. The two detection systems used along with standard co-injection and comparison with previous reports, led to the identification and quantification of six phenolic compounds and three iridoids.

Uncertainties in extracted parameters of a Gaussian emission line profile with continuum background.

PubMed

Minin, Serge; Kamalabadi, Farzad

2009-12-20

We derive analytical equations for uncertainties in parameters extracted by nonlinear least-squares fitting of a Gaussian emission function with an unknown continuum background component in the presence of additive white Gaussian noise. The derivation is based on the inversion of the full curvature matrix (equivalent to Fisher information matrix) of the least-squares error, chi(2), in a four-variable fitting parameter space. The derived uncertainty formulas (equivalent to Cramer-Rao error bounds) are found to be in good agreement with the numerically computed uncertainties from a large ensemble of simulated measurements. The derived formulas can be used for estimating minimum achievable errors for a given signal-to-noise ratio and for investigating some aspects of measurement setup trade-offs and optimization. While the intended application is Fabry-Perot spectroscopy for wind and temperature measurements in the upper atmosphere, the derivation is generic and applicable to other spectroscopy problems with a Gaussian line shape.

Ultrafast single photon emitting quantum photonic structures based on a nano-obelisk.

PubMed

Kim, Je-Hyung; Ko, Young-Ho; Gong, Su-Hyun; Ko, Suk-Min; Cho, Yong-Hoon

2013-01-01

A key issue in a single photon source is fast and efficient generation of a single photon flux with high light extraction efficiency. Significant progress toward high-efficiency single photon sources has been demonstrated by semiconductor quantum dots, especially using narrow bandgap materials. Meanwhile, there are many obstacles, which restrict the use of wide bandgap semiconductor quantum dots as practical single photon sources in ultraviolet-visible region, despite offering free space communication and miniaturized quantum information circuits. Here we demonstrate a single InGaN quantum dot embedded in an obelisk-shaped GaN nanostructure. The nano-obelisk plays an important role in eliminating dislocations, increasing light extraction, and minimizing a built-in electric field. Based on the nano-obelisks, we observed nonconventional narrow quantum dot emission and positive biexciton binding energy, which are signatures of negligible built-in field in single InGaN quantum dots. This results in efficient and ultrafast single photon generation in the violet color region.

The Principal Components of Adult Female Insole Shape Align Closely with Two of Its Classic Indicators.

PubMed

Bookstein, Fred L; Domjanic, Jacqueline

2015-01-01

The plantar surface of the human foot transmits the weight and dynamic force of the owner's lower limbs to the ground and the reaction forces back to the musculoskeletal system. Its anatomical variation is intensely studied in such fields as sports medicine and orthopedic dysmorphology. Yet, strangely, the shape of the insole that accommodates this surface and elastically buffers these forces is neither an aspect of the conventional anthropometrics of feet nor an informative label on the packet that markets supplementary insoles. In this paper we pursue an earlier suggestion that insole form in vertical view be quantified in terms of the shape of the foot not at the plane of support (the "footprint") but some two millimeters above that level. Using such sections extracted from laser scans of 158 feet of adult women from the University of Zagreb, in conjunction with an appropriate modification of today's standard geometric morphometrics (GMM), we find that the sectioned form can be described by its size together with two meaningful relative warps of shape. The pattern of this shape variation is not novel. It is closely aligned with two of the standard footprint measurements, the Chippaux-Šmiřák arch index and the Clarke arch angle, whose geometrical foci (the former in the ball of the foot, the latter in the arch) it apparently combines. Thus a strong contemporary analysis complements but does not supplant the simpler anthropometric analyses of half a century ago, with implications for applied anthropology.

The Principal Components of Adult Female Insole Shape Align Closely with Two of Its Classic Indicators

PubMed Central

Bookstein, Fred L.; Domjanic, Jacqueline

2015-01-01

The plantar surface of the human foot transmits the weight and dynamic force of the owner’s lower limbs to the ground and the reaction forces back to the musculoskeletal system. Its anatomical variation is intensely studied in such fields as sports medicine and orthopedic dysmorphology. Yet, strangely, the shape of the insole that accommodates this surface and elastically buffers these forces is neither an aspect of the conventional anthropometrics of feet nor an informative label on the packet that markets supplementary insoles. In this paper we pursue an earlier suggestion that insole form in vertical view be quantified in terms of the shape of the foot not at the plane of support (the “footprint”) but some two millimeters above that level. Using such sections extracted from laser scans of 158 feet of adult women from the University of Zagreb, in conjunction with an appropriate modification of today’s standard geometric morphometrics (GMM), we find that the sectioned form can be described by its size together with two meaningful relative warps of shape. The pattern of this shape variation is not novel. It is closely aligned with two of the standard footprint measurements, the Chippaux-Šmiřák arch index and the Clarke arch angle, whose geometrical foci (the former in the ball of the foot, the latter in the arch) it apparently combines. Thus a strong contemporary analysis complements but does not supplant the simpler anthropometric analyses of half a century ago, with implications for applied anthropology. PMID:26308442

Phytofabrication of bioinspired zinc oxide nanocrystals for biomedical application.

PubMed

Velmurugan, Palanivel; Park, Jung-Hee; Lee, Sang-Myeong; Jang, Jum-Suk; Yi, Young-Joo; Han, Sang-Sub; Lee, Sang-Hyun; Cho, Kwang-Min; Cho, Min; Oh, Byung-Taek

2016-09-01

In the present study, we investigated a novel green route for synthesis of zinc oxide nanoparticles (ZnO NPs) using the extract of young cones of Pinus densiflora as a reducing agent. Standard characterization studies were carried out to confirm the obtained product using UV-Vis spectra, SEM-EDS, FTIR, and XRD. TEM images showed that various shapes of ZnO NPs were synthesized, including hexagonal (wurtzite), triangular, spherical, and oval-shaped particles, with average sizes between 10 and 100 nm. The synthesized ZnO NPs blended with the young pine cone extract have very good activity against bacterial and fungal pathogens, similar to that of commercial ZnO NPs.

Automatic archaeological feature extraction from satellite VHR images

NASA Astrophysics Data System (ADS)

Jahjah, Munzer; Ulivieri, Carlo

2010-05-01

Archaeological applications need a methodological approach on a variable scale able to satisfy the intra-site (excavation) and the inter-site (survey, environmental research). The increased availability of high resolution and micro-scale data has substantially favoured archaeological applications and the consequent use of GIS platforms for reconstruction of archaeological landscapes based on remotely sensed data. Feature extraction of multispectral remotely sensing image is an important task before any further processing. High resolution remote sensing data, especially panchromatic, is an important input for the analysis of various types of image characteristics; it plays an important role in the visual systems for recognition and interpretation of given data. The methods proposed rely on an object-oriented approach based on a theory for the analysis of spatial structures called mathematical morphology. The term "morphology" stems from the fact that it aims at analysing object shapes and forms. It is mathematical in the sense that the analysis is based on the set theory, integral geometry, and lattice algebra. Mathematical morphology has proven to be a powerful image analysis technique; two-dimensional grey tone images are seen as three-dimensional sets by associating each image pixel with an elevation proportional to its intensity level. An object of known shape and size, called the structuring element, is then used to investigate the morphology of the input set. This is achieved by positioning the origin of the structuring element to every possible position of the space and testing, for each position, whether the structuring element either is included or has a nonempty intersection with the studied set. The shape and size of the structuring element must be selected according to the morphology of the searched image structures. Other two feature extraction techniques were used, eCognition and ENVI module SW, in order to compare the results. These techniques were applied to different archaeological sites in Turkmenistan (Nisa) and in Iraq (Babylon); a further change detection analysis was applied to the Babylon site using two HR images as a pre-post second gulf war. We had different results or outputs, taking into consideration the fact that the operative scale of sensed data determines the final result of the elaboration and the output of the information quality, because each of them was sensitive to specific shapes in each input image, we had mapped linear and nonlinear objects, updating archaeological cartography, automatic change detection analysis for the Babylon site. The discussion of these techniques has the objective to provide the archaeological team with new instruments for the orientation and the planning of a remote sensing application.

Synthesis of silver nano-materials from Grevillea robusta A Cunn (Silver-oak tree) leaves extract and shape directing role of cetyltrimethylammonium bromide

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

Ahmad, Rabia; Faisal, Qamer; Hussain, Sajjad

Grevillea robusta (Silver-oak tree) tree is a medicinal tree. Conventional UV-visible spectrophotometric and transmission electron microscopic technique were used to determine the morphology of silver nanoplates (AgNP) using Grevillea robusta (Silver-oak tree) aqueous leaves extract for the first time. The visible spectra showed the presence of three well defined surface plasmon absorption (SPR) bands at 500, 550 and 675 nm which was attributed to the anisotropic growth of Ag-nanoplates. Transmission electron microscopic (TEM) analysis of AgNP showed formation of truncated triangular, polyhedral with some irregular shapes nanoplates in the size range 8-20 nm. Cetyltrimethylammonium bromide (CTAB) has no significant effect on themore » shape of the spectra, position of SPR bands, size and size distribution of AgNP.« less

A new mathematical modelling based shape extraction technique for Forensic Odontology.

PubMed

G, Jaffino; A, Banumathi; Gurunathan, Ulaganathan; B, Vijayakumari; J, Prabin Jose

2017-04-01

Forensic Odontology is a specific means for identifying a person in which deceased, and particularly in fatality incidents. The algorithm can be proposed to identify a person by comparing both postmortem (PM) and antemortem (AM) dental radiographs and photographs. This work aims to introduce a new mathematical algorithm for photographs in addition with radiographs. Isoperimetric graph partitioning method is used to extract the shape of dental images in forensic identification. Shape matching is done by comparing AM and PM dental images using both similarity and distance measures. Experimental results prove that the higher matching distance is observed by distance metric rather than similarity measures. The results of this algorithm show that a high hit rate is observed for distance based performance measures and it is well suited for forensic odontologist to identify a person. Copyright © 2017 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Introducing Urtica dioica, A Native Plant of Khuzestan, As an Antibacterial Medicinal Plant.

PubMed

Motamedi, Hossein; Seyyednejad, Seyyed Mansour; Bakhtiari, Ameneh; Vafaei, Mozhan

2014-11-01

Urtica dioica is a flowering plant with long history of use in folk medicine and as a food source. This study examined in vitro antibacterial potential of alcoholic extracts of U. dioica. Hydroalcoholic extracts from aerial parts were prepared using aqueous solution of ethanol and methanol and their inhibitory effects against clinical isolates was examined by disc diffusion method at different doses. Minimum inhibitory concentrations (MIC) and minimum bactericidal concentration (MBC) indexes were also investigated. The scanning electron microscopy (SEM) analysis was also performed to find structural changes of affected bacteria consequent to exposing with extracts. Both extracts were active against Bacillus cereus, Staphylococcus aureus, Staphylococcus epidermidis, and Escherichia coli with respectively 16, 10, 18, and 14 mm (methanolic) and 11, 9, 17, and 16 mm (ethanolic) inhibition zone. The MIC of ethanolic extract against S. epidermidis and E. coli was respectively 10 and 40 mg/mL. The MIC of methanolic extract against S. aureus and S. epidermidis was 40 and 10 mg/mL, respectively. The MBC was found only for S. epidermidis (20 mg/mL). In SEM analysis the round shape of S. epidermidis was changed and irregular shapes were appeared, which suggest that the main target of these extracts was cell wall. Extracts of U. dioica showed significant antibacterial effect against some clinically important pathogenic bacteria. Based on the obtained results it can be concluded that U. dioica is useful as antibacterial and bactericidal agent in treating infectious diseases.

Arabidopsis phenotyping through Geometric Morphometrics.

PubMed

Manacorda, Carlos A; Asurmendi, Sebastian

2018-06-18

Recently, much technical progress was achieved in the field of plant phenotyping. High-throughput platforms and the development of improved algorithms for rosette image segmentation make it now possible to extract shape and size parameters for genetic, physiological and environmental studies on a large scale. The development of low-cost phenotyping platforms and freeware resources make it possible to widely expand phenotypic analysis tools for Arabidopsis. However, objective descriptors of shape parameters that could be used independently of platform and segmentation software used are still lacking and shape descriptions still rely on ad hoc or even sometimes contradictory descriptors, which could make comparisons difficult and perhaps inaccurate. Modern geometric morphometrics is a family of methods in quantitative biology proposed to be the main source of data and analytical tools in the emerging field of phenomics studies. Based on the location of landmarks (corresponding points) over imaged specimens and by combining geometry, multivariate analysis and powerful statistical techniques, these tools offer the possibility to reproducibly and accurately account for shape variations amongst groups and measure them in shape distance units. Here, a particular scheme of landmarks placement on Arabidopsis rosette images is proposed to study shape variation in the case of viral infection processes. Shape differences between controls and infected plants are quantified throughout the infectious process and visualized. Quantitative comparisons between two unrelated ssRNA+ viruses are shown and reproducibility issues are assessed. Combined with the newest automated platforms and plant segmentation procedures, geometric morphometric tools could boost phenotypic features extraction and processing in an objective, reproducible manner.

Information Geometry for Landmark Shape Analysis: Unifying Shape Representation and Deformation

PubMed Central

Peter, Adrian M.; Rangarajan, Anand

2010-01-01

Shape matching plays a prominent role in the comparison of similar structures. We present a unifying framework for shape matching that uses mixture models to couple both the shape representation and deformation. The theoretical foundation is drawn from information geometry wherein information matrices are used to establish intrinsic distances between parametric densities. When a parameterized probability density function is used to represent a landmark-based shape, the modes of deformation are automatically established through the information matrix of the density. We first show that given two shapes parameterized by Gaussian mixture models (GMMs), the well-known Fisher information matrix of the mixture model is also a Riemannian metric (actually, the Fisher-Rao Riemannian metric) and can therefore be used for computing shape geodesics. The Fisher-Rao metric has the advantage of being an intrinsic metric and invariant to reparameterization. The geodesic—computed using this metric—establishes an intrinsic deformation between the shapes, thus unifying both shape representation and deformation. A fundamental drawback of the Fisher-Rao metric is that it is not available in closed form for the GMM. Consequently, shape comparisons are computationally very expensive. To address this, we develop a new Riemannian metric based on generalized ϕ-entropy measures. In sharp contrast to the Fisher-Rao metric, the new metric is available in closed form. Geodesic computations using the new metric are considerably more efficient. We validate the performance and discriminative capabilities of these new information geometry-based metrics by pairwise matching of corpus callosum shapes. We also study the deformations of fish shapes that have various topological properties. A comprehensive comparative analysis is also provided using other landmark-based distances, including the Hausdorff distance, the Procrustes metric, landmark-based diffeomorphisms, and the bending energies of the thin-plate (TPS) and Wendland splines. PMID:19110497

Building Extraction from Remote Sensing Data Using Fully Convolutional Networks

NASA Astrophysics Data System (ADS)

Bittner, K.; Cui, S.; Reinartz, P.

2017-05-01

Building detection and footprint extraction are highly demanded for many remote sensing applications. Though most previous works have shown promising results, the automatic extraction of building footprints still remains a nontrivial topic, especially in complex urban areas. Recently developed extensions of the CNN framework made it possible to perform dense pixel-wise classification of input images. Based on these abilities we propose a methodology, which automatically generates a full resolution binary building mask out of a Digital Surface Model (DSM) using a Fully Convolution Network (FCN) architecture. The advantage of using the depth information is that it provides geometrical silhouettes and allows a better separation of buildings from background as well as through its invariance to illumination and color variations. The proposed framework has mainly two steps. Firstly, the FCN is trained on a large set of patches consisting of normalized DSM (nDSM) as inputs and available ground truth building mask as target outputs. Secondly, the generated predictions from FCN are viewed as unary terms for a Fully connected Conditional Random Fields (FCRF), which enables us to create a final binary building mask. A series of experiments demonstrate that our methodology is able to extract accurate building footprints which are close to the buildings original shapes to a high degree. The quantitative and qualitative analysis show the significant improvements of the results in contrast to the multy-layer fully connected network from our previous work.

Test of the combined method for extracting spectroscopic factors in N =50 nuclei

NASA Astrophysics Data System (ADS)

Walter, David; Cizewski, J. A.; Baugher, T.; Ratkiewicz, A.; Pain, S. D.; Nunes, F. M.; Ahn, S.; Cerizza, G.; Jones, K. L.; Manning, B.; Thornsberry, C.

2017-09-01

The single-particle properties of nuclei near shell closures and r-process waiting points can be observed using single-nucleon transfer reactions with beams of rare isotopes. However, approximations have to be made about the final bound state to extract spectroscopic information. An approach to constrain the bound state potential has been proposed by Mukhamedzhanov and Nunes. At peripheral reaction energies ( 5 MeV/u), the ANC for the nucleus can be extracted, and is combined with the same reaction at higher energies ( 40 MeV/u). These combined measurements can constrain the shape of the bound state potential, and the spectroscopic factor can be reliably extracted. To test this method, the 86Kr(d , p) reaction was performed in inverse kinematics with a 35 MeV/u beam at the National Superconducting Cyclotron Laboratory (NSCL) with the ORRUBA and SIDAR arrays of silicon strip detectors coupled to the S800 spectrometer. Successful results supported the measurement of a radioactive ion beam of 84Se at 45 MeV/u at the NSCL to be measured at the end of 2017. Results from the 86Kr(d , p) measurement will be presented as well as preparations for the upcoming 84Se(d , p) measurement. This work is supported in part by the National Science Foundation and U.S. D.O.E.

The Organization of Shape and Color in Vision and Art

PubMed Central

Pinna, Baingio

2011-01-01

The aim of this work is to study the phenomenal organization of shape and color in vision and art in terms of microgenesis of the object perception and creation. The idea of “microgenesis” is that the object perception and creation takes time to develop. Our hypothesis is that the roles of shape and color are extracted in sequential order and in the same order these roles are also used by artists to paint objects. Boundary contours are coded before color contours. The microgenesis of the object formation was demonstrated (i) by introducing new conditions derived from the watercolor illusion, where the juxtaposed contours are displaced horizontally or vertically, and based on variations of Matisse’s Woman, (ii) by studying descriptions and replications of visual objects in adults and children of different ages, and (iii) by analyzing the linguistic sequence and organization in a free naming task of the attributes related to shape and color. The results supported the idea of the microgenesis of the object perception, namely the temporal order in the formation of the roles of the object properties (shape before color). Some general principles were extracted from the experimental results. They can be a starting point to explore a new domain focused on the microgenesis of shape and color within the more general problem of object organization, where integrated and multidisciplinary studies based on art and vision science can be very useful. PMID:22065954

Biosynthesis of Gold and Silver Nanoparticles Using Extracts of Callus Cultures of Pumpkin (Cucurbita maxima).

PubMed

Iyer, R Indira; Panda, Tapobrata

2018-08-01

The potential of callus cultures and field-grown organs of pumpkin (Cucurbita maxima) for the biosynthesis of nanoparticles of the noble metals gold and silver has been investigated. Biosynthesis of AuNPs (gold nanoparticles) and AgNPs (silver nanoparticles) was obtained with flowers of C. maxima but not with pulp and seeds. With callus cultures established in MS-based medium the biogenesis of both AuNPs and AgNPs could be obtained. At 65 °C the biogenesis of AuNPs and AgNPs by callus extracts was enhanced. The AuNPs and AgNPs have been characterized by UV-visible spectroscopy, TEM, DLS and XRD. Well-dispersed nanoparticles, which exhibited a remarkable diversity in size and shape, could be visualized by TEM. Gold nanoparticles were found to be of various shapes, viz., rods, triangles, star-shaped particles, spheres, hexagons, bipyramids, discoid particles, nanotrapezoids, prisms, cuboids. Silver nanoparticles were also of diverse shapes, viz., discoid, spherical, elliptical, triangle-like, belt-like, rod-shaped forms and cuboids. EDX analysis indicated that the AuNPs and AgNPs had a high degree of purity. The surface charges of the generated AuNPs and AgNPs were highly negative as indicated by zeta potential measurements. The AuNPs and AgNPs exhibited remarkable stability in solution for more than four months. FTIR studies indicated that biomolecules in the callus extracts were associated with the biosynthesis and stabilisation of the nanoparticles. The synthesized AgNPs could catalyse degradation of methylene blue and exhibited anti-bacterial activity against E. coli DH5α. There is no earlier report of the biosynthesis of nanoparticles by this plant species. Callus cultures of Cucurbita maxima are effective alternative resources of biomass for synthesis of nanoparticles.

Diffeomorphic Sulcal Shape Analysis on the Cortex

PubMed Central

Joshi, Shantanu H.; Cabeen, Ryan P.; Joshi, Anand A.; Sun, Bo; Dinov, Ivo; Narr, Katherine L.; Toga, Arthur W.; Woods, Roger P.

2014-01-01

We present a diffeomorphic approach for constructing intrinsic shape atlases of sulci on the human cortex. Sulci are represented as square-root velocity functions of continuous open curves in ℝ3, and their shapes are studied as functional representations of an infinite-dimensional sphere. This spherical manifold has some advantageous properties – it is equipped with a Riemannian metric on the tangent space and facilitates computational analyses and correspondences between sulcal shapes. Sulcal shape mapping is achieved by computing geodesics in the quotient space of shapes modulo scales, translations, rigid rotations and reparameterizations. The resulting sulcal shape atlas preserves important local geometry inherently present in the sample population. The sulcal shape atlas is integrated in a cortical registration framework and exhibits better geometric matching compared to the conventional euclidean method. We demonstrate experimental results for sulcal shape mapping, cortical surface registration, and sulcal classification for two different surface extraction protocols for separate subject populations. PMID:22328177

Spatiotemporal attention operator using isotropic contrast and regional homogeneity

NASA Astrophysics Data System (ADS)

Palenichka, Roman; Lakhssassi, Ahmed; Zaremba, Marek

2011-04-01

A multiscale operator for spatiotemporal isotropic attention is proposed to reliably extract attention points during image sequence analysis. Its consecutive local maxima indicate attention points as the centers of image fragments of variable size with high intensity contrast, region homogeneity, regional shape saliency, and temporal change presence. The scale-adaptive estimation of temporal change (motion) and its aggregation with the regional shape saliency contribute to the accurate determination of attention points in image sequences. Multilocation descriptors of an image sequence are extracted at the attention points in the form of a set of multidimensional descriptor vectors. A fast recursive implementation is also proposed to make the operator's computational complexity independent from the spatial scale size, which is the window size in the spatial averaging filter. Experiments on the accuracy of attention-point detection have proved the operator consistency and its high potential for multiscale feature extraction from image sequences.

Region Segmentation in the Frequency Domain Applied to Upper Airway Real-Time Magnetic Resonance Images

PubMed Central

Narayanan, Shrikanth

2009-01-01

We describe a method for unsupervised region segmentation of an image using its spatial frequency domain representation. The algorithm was designed to process large sequences of real-time magnetic resonance (MR) images containing the 2-D midsagittal view of a human vocal tract airway. The segmentation algorithm uses an anatomically informed object model, whose fit to the observed image data is hierarchically optimized using a gradient descent procedure. The goal of the algorithm is to automatically extract the time-varying vocal tract outline and the position of the articulators to facilitate the study of the shaping of the vocal tract during speech production. PMID:19244005

Image retrieval for identifying house plants

NASA Astrophysics Data System (ADS)

Kebapci, Hanife; Yanikoglu, Berrin; Unal, Gozde

2010-02-01

We present a content-based image retrieval system for plant identification which is intended for providing users with a simple method to locate information about their house plants. A plant image consists of a collection of overlapping leaves and possibly flowers, which makes the problem challenging. We studied the suitability of various well-known color, texture and shape features for this problem, as well as introducing some new ones. The features are extracted from the general plant region that is segmented from the background using the max-flow min-cut technique. Results on a database of 132 different plant images show promise (in about 72% of the queries, the correct plant image is retrieved among the top-15 results).

A new accurate pill recognition system using imprint information

NASA Astrophysics Data System (ADS)

Chen, Zhiyuan; Kamata, Sei-ichiro

2013-12-01

Great achievements in modern medicine benefit human beings. Also, it has brought about an explosive growth of pharmaceuticals that current in the market. In daily life, pharmaceuticals sometimes confuse people when they are found unlabeled. In this paper, we propose an automatic pill recognition technique to solve this problem. It functions mainly based on the imprint feature of the pills, which is extracted by proposed MSWT (modified stroke width transform) and described by WSC (weighted shape context). Experiments show that our proposed pill recognition method can reach an accurate rate up to 92.03% within top 5 ranks when trying to classify more than 10 thousand query pill images into around 2000 categories.

Modeling and Control of the Redundant Parallel Adjustment Mechanism on a Deployable Antenna Panel

PubMed Central

Tian, Lili; Bao, Hong; Wang, Meng; Duan, Xuechao

2016-01-01

With the aim of developing multiple input and multiple output (MIMO) coupling systems with a redundant parallel adjustment mechanism on the deployable antenna panel, a structural control integrated design methodology is proposed in this paper. Firstly, the modal information from the finite element model of the structure of the antenna panel is extracted, and then the mathematical model is established with the Hamilton principle; Secondly, the discrete Linear Quadratic Regulator (LQR) controller is added to the model in order to control the actuators and adjust the shape of the panel. Finally, the engineering practicality of the modeling and control method based on finite element analysis simulation is verified. PMID:27706076

Plenoptic Imaging of a Three Dimensional Cold Atom Cloud

NASA Astrophysics Data System (ADS)

Lott, Gordon

2017-04-01

A plenoptic imaging system is capable of sampling the rays of light in a volume, both spatially and angularly, providing information about the three dimensional (3D) volume being imaged. The extraction of the 3D structure of a cold atom cloud is demonstrated, using a single plenoptic camera and a single image. The reconstruction is tested against a reference image and the results discussed along with the capabilities and limitations of the imaging system. This capability is useful when the 3D distribution of the atoms is desired, such as determining the shape of an atom trap, particularly when there is limited optical access. Gratefully acknowledge support from AFRL.

Visualizing and quantifying the in vivo structure and dynamics of the Arabidopsis cortical cytoskeleton using CLSM and VAEM.

PubMed

Rosero, Amparo; Zárský, Viktor; Cvrčková, Fatima

2014-01-01

The cortical microtubules, and to some extent also the actin meshwork, play a central role in the shaping of plant cells. Transgenic plants expressing fluorescent protein markers specifically tagging the two main cytoskeletal systems are available, allowing noninvasive in vivo studies. Advanced microscopy techniques, in particular confocal laser scanning microscopy (CLSM) and variable angle epifluorescence microscopy (VAEM), can be nowadays used for imaging the cortical cytoskeleton of living cells with unprecedented spatial and temporal resolution. With the aid of suitable computing techniques, quantitative information can be extracted from microscopic images and video sequences, providing insight into both architecture and dynamics of the cortical cytoskeleton.

A software package for interactive motor unit potential classification using fuzzy k-NN classifier.

PubMed

Rasheed, Sarbast; Stashuk, Daniel; Kamel, Mohamed

2008-01-01

We present an interactive software package for implementing the supervised classification task during electromyographic (EMG) signal decomposition process using a fuzzy k-NN classifier and utilizing the MATLAB high-level programming language and its interactive environment. The method employs an assertion-based classification that takes into account a combination of motor unit potential (MUP) shapes and two modes of use of motor unit firing pattern information: the passive and the active modes. The developed package consists of several graphical user interfaces used to detect individual MUP waveforms from a raw EMG signal, extract relevant features, and classify the MUPs into motor unit potential trains (MUPTs) using assertion-based classifiers.

Study into the identification of irradiation ground paprika

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

Beczner, J.; Farkas, J.; Kiss, I.

From international colloquium: the identification of irradiated foodstuffs; Karlsruhe, Germany (24 Oct 1973). Several methods for the demonstration of irradiation in ground paprika were tested. In carbonyl compounds extracted by steam distillation unambiguous changes, which might have served as a basis for detecting irradiation, were not observed. Derivatography did not prove suitable either. On the basis of the size of ESR signal, the control sample and the irradiated one could be distinguished 2 to 3 weeks after irradiation. After a longer storage period, the size of the signal is irrelevant. Further study of the shape of the ESR signals maymore » yield valuable information in experiments on the demonstration of irradiation. (GE)« less

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.

Best estimate of luminal cross-sectional area of coronary arteries from angiograms

NASA Technical Reports Server (NTRS)

Lee, P. L.; Selzer, R. H.

1988-01-01

We have reexamined the problem of estimating the luminal area of an elliptically-shaped coronary artery cross section from two or more radiographic diameter measurements. The expected error is found to be much smaller than the maximum potential error. In the cae of two orthogonal views, closed form expressions have been derived for calculating the area and the uncertainty. Assuming that the underlying ellipse has limited ellipticity (major/minor axis ratio less than five), it is shown that the average uncertainty in the area is less than 14 percent. When more than two views are available, we suggest using a least-squares fit method to extract all available information from the data.

Continuous depth-of-interaction encoding using phosphor-coated scintillators.

PubMed

Du, Huini; Yang, Yongfeng; Glodo, Jarek; Wu, Yibao; Shah, Kanai; Cherry, Simon R

2009-03-21

We investigate a novel detector using a lutetium oxyorthosilicate (LSO) scintillator and YGG (yttrium-aluminum-gallium oxide:cerium, Y(3)(Al,Ga)(5)O(12):Ce) phosphor to construct a detector with continuous depth-of-interaction (DOI) information. The far end of the LSO scintillator is coated with a thin layer of YGG phosphor powder which absorbs some fraction of the LSO scintillation light and emits wavelength-shifted photons with a characteristic decay time of approximately 50 ns. The near end of the LSO scintillator is directly coupled to a photodetector. The photodetector detects a mixture of the LSO light and the light emitted by YGG. With appropriate placement of the coating, the ratio of the light converted from the YGG coating with respect to the unconverted LSO light can be made to depend on the interaction depth. DOI information can then be estimated by inspecting the overall light pulse decay time. Experiments were conducted to optimize the coating method. 19 ns decay time differences across the length of the detector were achieved experimentally when reading out a 1.5 x 1.5 x 20 mm(3) LSO crystal with unpolished surfaces and half-coated with YGG phosphor. The same coating scheme was applied to a 4 x 4 LSO array. Pulse shape discrimination (PSD) methods were studied to extract DOI information from the pulse shape changes. The DOI full-width-half-maximum (FWHM) resolution was found to be approximately 8 mm for this 2 cm thick array.

Continuous Depth-of-Interaction Encoding Using Phosphor-Coated Scintillators

PubMed Central

Du, Huini; Yang, Yongfeng; Glodo, Jarek; Wu, Yibao; Shah, Kanai; Cherry, Simon R.

2009-01-01

We investigate a novel detector using lutetium oxyorthosilicate (LSO) scintillator and YGG (yttrium aluminum gallium oxide:cerium, Y3(Al,Ga)5O12:Ce) phosphor to construct a detector with continuous depth-of-interaction (DOI) information. The far end of the LSO scintillator is coated with a thin layer of YGG phosphor powder which absorbs some fraction of the LSO scintillation light and emits wavelength-shifted photons with a characteristic decay time of ∼ 50 ns. The near end of the LSO scintillator is directly coupled to a photodetector. The photodetector detects a mixture of the LSO light and the light emitted by YGG. With appropriate placement of the coating, the ratio of the light converted from the YGG coating with respect to the unconverted LSO light can be made to depend on the interaction depth. DOI information can then be estimated by inspecting the overall light pulse decay time. Experiments were conducted to optimize the coating method. 19 ns decay time differences across the length of the detector were achieved experimentally when reading out a 1.5×1.5×20 mm3 LSO crystal with unpolished surfaces and half-coated with YGG phosphor. The same coating scheme was applied to a 4 by 4 LSO array. Pulse shape discrimination (PSD) methods were studied to extract DOI information from the pulse shape changes. The DOI full-width-half-maximum (FWHM) resolution was found to be ∼8 mm for this 2 cm thick array. PMID:19258685

Quantifying Wave Breaking Shape and Type in the Surf-Zone Using LiDAR

NASA Astrophysics Data System (ADS)

Albright, A.; Brodie, K. L.; Hartzell, P. J.; Glennie, C. L.

2017-12-01

Waves change shape as they shoal and break across the surf-zone, ultimately dissipating and transferring their energy into turbulence by either spilling or plunging. This injection of turbulence and changes in wave shape can affect the direction of sediment transport at the seafloor, and ultimately lead to morphological evolution. Typical methods for collecting wave data in the surf-zone include in-situ pressure gauges, velocimeters, ultrasonic sensors, and video imagery. Drawbacks to these data collection methods are low spatial resolution of point measurements, reliance on linear theory to calculate sea-surface elevations, and intensive computations required to extract wave properties from stereo 2D imagery. As a result, few field measurements of the shapes of plunging and/or spilling breakers exist, and existing knowledge is confined to results of laboratory studies. We therefore examine the use of a multi-beam scanning Light Detection and Ranging (LiDAR) remote sensing instrument with the goal of classifying the breaking type of propagating waves in the surf-zone and quantitatively determining wave morphometric properties. Data were collected with a Velodyne HDL-32E LiDAR scanner (360° vertical field of view) mounted on an arm of the Coastal Research Amphibious Buggy (CRAB) at the U.S. Army Corps of Engineers Field Research Facility in Duck, North Carolina. Processed laser scan data are used to visualize the lifecycle of a wave (shoaling, breaking, broken) and identify wave types (spilling, plunging, non-breaking) as they pass beneath the scanner. For each rotation of the LiDAR scanner, the point cloud data are filtered, smoothed, and detrended in order to identify individual waves and measure their properties, such as speed, height, period, upward/downward slope, asymmetry, and skewness. The 3D nature of point cloud data is advantageous for research, because it enables viewing from any angle. In our analysis, plan views are used to separate individual waves, and cross-shore profiles are used to extract wave properties. Combined with accurate georeferencing information, LiDAR has the potential to be a powerful remote sensing tool for coastal monitoring systems and the study of nearshore processes.

Detection and 3D reconstruction of traffic signs from multiple view color images

NASA Astrophysics Data System (ADS)

Soheilian, Bahman; Paparoditis, Nicolas; Vallet, Bruno

2013-03-01

3D reconstruction of traffic signs is of great interest in many applications such as image-based localization and navigation. In order to reflect the reality, the reconstruction process should meet both accuracy and precision. In order to reach such a valid reconstruction from calibrated multi-view images, accurate and precise extraction of signs in every individual view is a must. This paper presents first an automatic pipeline for identifying and extracting the silhouette of signs in every individual image. Then, a multi-view constrained 3D reconstruction algorithm provides an optimum 3D silhouette for the detected signs. The first step called detection, tackles with a color-based segmentation to generate ROIs (Region of Interests) in image. The shape of every ROI is estimated by fitting an ellipse, a quadrilateral or a triangle to edge points. A ROI is rejected if none of the three shapes can be fitted sufficiently precisely. Thanks to the estimated shape the remained candidates ROIs are rectified to remove the perspective distortion and then matched with a set of reference signs using textural information. Poor matches are rejected and the types of remained ones are identified. The output of the detection algorithm is a set of identified road signs whose silhouette in image plane is represented by and ellipse, a quadrilateral or a triangle. The 3D reconstruction process is based on a hypothesis generation and verification. Hypotheses are generated by a stereo matching approach taking into account epipolar geometry and also the similarity of the categories. The hypotheses that are plausibly correspond to the same 3D road sign are identified and grouped during this process. Finally, all the hypotheses of the same group are merged to generate a unique 3D road sign by a multi-view algorithm integrating a priori knowledges about 3D shape of road signs as constraints. The algorithm is assessed on real and synthetic images and reached and average accuracy of 3.5cm for position and 4.5° for orientation.

Feature engineering for drug name recognition in biomedical texts: feature conjunction and feature selection.

PubMed

Liu, Shengyu; Tang, Buzhou; Chen, Qingcai; Wang, Xiaolong; Fan, Xiaoming

2015-01-01

Drug name recognition (DNR) is a critical step for drug information extraction. Machine learning-based methods have been widely used for DNR with various types of features such as part-of-speech, word shape, and dictionary feature. Features used in current machine learning-based methods are usually singleton features which may be due to explosive features and a large number of noisy features when singleton features are combined into conjunction features. However, singleton features that can only capture one linguistic characteristic of a word are not sufficient to describe the information for DNR when multiple characteristics should be considered. In this study, we explore feature conjunction and feature selection for DNR, which have never been reported. We intuitively select 8 types of singleton features and combine them into conjunction features in two ways. Then, Chi-square, mutual information, and information gain are used to mine effective features. Experimental results show that feature conjunction and feature selection can improve the performance of the DNR system with a moderate number of features and our DNR system significantly outperforms the best system in the DDIExtraction 2013 challenge.

Analysing magnetism using scanning SQUID microscopy.

PubMed

Reith, P; Renshaw Wang, X; Hilgenkamp, H

2017-12-01

Scanning superconducting quantum interference device microscopy (SSM) is a scanning probe technique that images local magnetic flux, which allows for mapping of magnetic fields with high field and spatial accuracy. Many studies involving SSM have been published in the last few decades, using SSM to make qualitative statements about magnetism. However, quantitative analysis using SSM has received less attention. In this work, we discuss several aspects of interpreting SSM images and methods to improve quantitative analysis. First, we analyse the spatial resolution and how it depends on several factors. Second, we discuss the analysis of SSM scans and the information obtained from the SSM data. Using simulations, we show how signals evolve as a function of changing scan height, SQUID loop size, magnetization strength, and orientation. We also investigated 2-dimensional autocorrelation analysis to extract information about the size, shape, and symmetry of magnetic features. Finally, we provide an outlook on possible future applications and improvements.

Analysing magnetism using scanning SQUID microscopy

NASA Astrophysics Data System (ADS)

Reith, P.; Renshaw Wang, X.; Hilgenkamp, H.

2017-12-01

Scanning superconducting quantum interference device microscopy (SSM) is a scanning probe technique that images local magnetic flux, which allows for mapping of magnetic fields with high field and spatial accuracy. Many studies involving SSM have been published in the last few decades, using SSM to make qualitative statements about magnetism. However, quantitative analysis using SSM has received less attention. In this work, we discuss several aspects of interpreting SSM images and methods to improve quantitative analysis. First, we analyse the spatial resolution and how it depends on several factors. Second, we discuss the analysis of SSM scans and the information obtained from the SSM data. Using simulations, we show how signals evolve as a function of changing scan height, SQUID loop size, magnetization strength, and orientation. We also investigated 2-dimensional autocorrelation analysis to extract information about the size, shape, and symmetry of magnetic features. Finally, we provide an outlook on possible future applications and improvements.

Modeling stress–strain state of rock mass under mining of complex-shape extraction pillar

NASA Astrophysics Data System (ADS)

Fryanov, VN; Pavlova, LD

2018-03-01

Based on the results of numerical modeling of stresses and strains in rock mass, geomechanical parameters of development workings adjacent to coal face operation area are provided for multi-entry preparation and extraction of flat seams with production faces of variable length. The negative effects on the geomechanical situation during the transition from the longwall to shortwall mining in a fully mechanized extraction face are found.

Recognizing familiar objects by hand and foot: Haptic shape perception generalizes to inputs from unusual locations and untrained body parts.

PubMed

Lawson, Rebecca

2014-02-01

The limits of generalization of our 3-D shape recognition system to identifying objects by touch was investigated by testing exploration at unusual locations and using untrained effectors. In Experiments 1 and 2, people found identification by hand of real objects, plastic 3-D models of objects, and raised line drawings placed in front of themselves no easier than when exploration was behind their back. Experiment 3 compared one-handed, two-handed, one-footed, and two-footed haptic object recognition of familiar objects. Recognition by foot was slower (7 vs. 13 s) and much less accurate (9 % vs. 47 % errors) than recognition by either one or both hands. Nevertheless, item difficulty was similar across hand and foot exploration, and there was a strong correlation between an individual's hand and foot performance. Furthermore, foot recognition was better with the largest 20 of the 80 items (32 % errors), suggesting that physical limitations hampered exploration by foot. Thus, object recognition by hand generalized efficiently across the spatial location of stimuli, while object recognition by foot seemed surprisingly good given that no prior training was provided. Active touch (haptics) thus efficiently extracts 3-D shape information and accesses stored representations of familiar objects from novel modes of input.

International Space Station Model Correlation Analysis

NASA Technical Reports Server (NTRS)

Laible, Michael R.; Fitzpatrick, Kristin; Hodge, Jennifer; Grygier, Michael

2018-01-01

This paper summarizes the on-orbit structural dynamic data and the related modal analysis, model validation and correlation performed for the International Space Station (ISS) configuration ISS Stage ULF7, 2015 Dedicated Thruster Firing (DTF). The objective of this analysis is to validate and correlate the analytical models used to calculate the ISS internal dynamic loads and compare the 2015 DTF with previous tests. During the ISS configurations under consideration, on-orbit dynamic measurements were collected using the three main ISS instrumentation systems; Internal Wireless Instrumentation System (IWIS), External Wireless Instrumentation System (EWIS) and the Structural Dynamic Measurement System (SDMS). The measurements were recorded during several nominal on-orbit DTF tests on August 18, 2015. Experimental modal analyses were performed on the measured data to extract modal parameters including frequency, damping, and mode shape information. Correlation and comparisons between test and analytical frequencies and mode shapes were performed to assess the accuracy of the analytical models for the configurations under consideration. These mode shapes were also compared to earlier tests. Based on the frequency comparisons, the accuracy of the mathematical models is assessed and model refinement recommendations are given. In particular, results of the first fundamental mode will be discussed, nonlinear results will be shown, and accelerometer placement will be assessed.

Spring assisted cranioplasty: A patient specific computational model.

PubMed

Borghi, Alessandro; Rodriguez-Florez, Naiara; Rodgers, Will; James, Gregory; Hayward, Richard; Dunaway, David; Jeelani, Owase; Schievano, Silvia

2018-03-01

Implantation of spring-like distractors in the treatment of sagittal craniosynostosis is a novel technique that has proven functionally and aesthetically effective in correcting skull deformities; however, final shape outcomes remain moderately unpredictable due to an incomplete understanding of the skull-distractor interaction. The aim of this study was to create a patient specific computational model of spring assisted cranioplasty (SAC) that can help predict the individual overall final head shape. Pre-operative computed tomography images of a SAC patient were processed to extract a 3D model of the infant skull anatomy and simulate spring implantation. The distractors were modeled based on mechanical experimental data. Viscoelastic bone properties from the literature were tuned using the specific patient procedural information recorded during surgery and from x-ray measurements at follow-up. The model accurately captured spring expansion on-table (within 9% of the measured values), as well as at first and second follow-ups (within 8% of the measured values). Comparison between immediate post-operative 3D head scanning and numerical results for this patient proved that the model could successfully predict the final overall head shape. This preliminary work showed the potential application of computational modeling to study SAC, to support pre-operative planning and guide novel distractor design. Copyright © 2018 IPEM. Published by Elsevier Ltd. All rights reserved.

Nonlinear integral equations for the sausage model

NASA Astrophysics Data System (ADS)

Ahn, Changrim; Balog, Janos; Ravanini, Francesco

2017-08-01

The sausage model, first proposed by Fateev, Onofri, and Zamolodchikov, is a deformation of the O(3) sigma model preserving integrability. The target space is deformed from the sphere to ‘sausage’ shape by a deformation parameter ν. This model is defined by a factorizable S-matrix which is obtained by deforming that of the O(3) sigma model by a parameter λ. Clues for the deformed sigma model are provided by various UV and IR information through the thermodynamic Bethe ansatz (TBA) analysis based on the S-matrix. Application of TBA to the sausage model is, however, limited to the case of 1/λ integer where the coupled integral equations can be truncated to a finite number. In this paper, we propose a finite set of nonlinear integral equations (NLIEs), which are applicable to generic value of λ. Our derivation is based on T-Q relations extracted from the truncated TBA equations. For a consistency check, we compute next-leading order corrections of the vacuum energy and extract the S-matrix information in the IR limit. We also solved the NLIE both analytically and numerically in the UV limit to get the effective central charge and compared with that of the zero-mode dynamics to obtain exact relation between ν and λ. Dedicated to the memory of Petr Petrovich Kulish.

SPECTRAL LINE DE-CONFUSION IN AN INTENSITY MAPPING SURVEY

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

Cheng, Yun-Ting; Bock, James; Bradford, C. Matt

2016-12-01

Spectral line intensity mapping (LIM) has been proposed as a promising tool to efficiently probe the cosmic reionization and the large-scale structure. Without detecting individual sources, LIM makes use of all available photons and measures the integrated light in the source confusion limit to efficiently map the three-dimensional matter distribution on large scales as traced by a given emission line. One particular challenge is the separation of desired signals from astrophysical continuum foregrounds and line interlopers. Here we present a technique to extract large-scale structure information traced by emission lines from different redshifts, embedded in a three-dimensional intensity mapping data cube.more » The line redshifts are distinguished by the anisotropic shape of the power spectra when projected onto a common coordinate frame. We consider the case where high-redshift [C ii] lines are confused with multiple low-redshift CO rotational lines. We present a semi-analytic model for [C ii] and CO line estimates based on the cosmic infrared background measurements, and show that with a modest instrumental noise level and survey geometry, the large-scale [C ii] and CO power spectrum amplitudes can be successfully extracted from a confusion-limited data set, without external information. We discuss the implications and limits of this technique for possible LIM experiments.« less

Analysis of atomic force microscopy data for surface characterization using fuzzy logic

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

Al-Mousa, Amjed, E-mail: aalmousa@vt.edu; Niemann, Darrell L.; Niemann, Devin J.

2011-07-15

In this paper we present a methodology to characterize surface nanostructures of thin films. The methodology identifies and isolates nanostructures using Atomic Force Microscopy (AFM) data and extracts quantitative information, such as their size and shape. The fuzzy logic based methodology relies on a Fuzzy Inference Engine (FIE) to classify the data points as being top, bottom, uphill, or downhill. The resulting data sets are then further processed to extract quantitative information about the nanostructures. In the present work we introduce a mechanism which can consistently distinguish crowded surfaces from those with sparsely distributed structures and present an omni-directional searchmore » technique to improve the structural recognition accuracy. In order to demonstrate the effectiveness of our approach we present a case study which uses our approach to quantitatively identify particle sizes of two specimens each with a unique gold nanoparticle size distribution. - Research Highlights: {yields} A Fuzzy logic analysis technique capable of characterizing AFM images of thin films. {yields} The technique is applicable to different surfaces regardless of their densities. {yields} Fuzzy logic technique does not require manual adjustment of the algorithm parameters. {yields} The technique can quantitatively capture differences between surfaces. {yields} This technique yields more realistic structure boundaries compared to other methods.« less

Local and Total Density Measurements in Ice Shapes

NASA Technical Reports Server (NTRS)

Vargas, Mario; Broughton, Howard; Sims, James J.; Bleeze, Brian; Gaines, Vatanna

2005-01-01

Preliminary measurements of local and total densities inside ice shapes were obtained from ice shapes grown in the NASA Glenn Research Tunnel for a range of glaze ice, rime ice, and mixed phase ice conditions on a NACA 0012 airfoil at 0 angle of attack. The ice shapes were removed from the airfoil and a slice of ice 3 mm thick was obtained using a microtome. The resulting samples were then x-rayed to obtain a micro-radiography, the film was digitized, and image processing techniques were used to extract the local and total density values.

Synthesis and characterization of nano-hydroxyapatite using Sapindus Mukorossi extract

NASA Astrophysics Data System (ADS)

Subha, B.; Prasath, P. Varun; Abinaya, R.; Kavitha, R. J.; Ravichandran, K.

2015-06-01

Nano-Hydroxyapatite (HAP) powders were successfully synthesised by hydrothermal method using Sapindus Mukorossi extract as an additive. The structural and morphological analyses of thus synthesised powders were carried out using FT-IR, XRD and FESEM/EDX. The FT-IR spectra confirm the presence of phosphate and hydroxyl groups corresponding to HAP. The XRD analysis reveals the formation of HAP phase and found to reduce the crystallite size with addition of Sapindus Mukorossi extract. The morphology changes from sphere to flake shape by the influence of extract.

[Application of regular expression in extracting key information from Chinese medicine literatures about re-evaluation of post-marketing surveillance].

PubMed

Wang, Zhifei; Xie, Yanming; Wang, Yongyan

2011-10-01

Computerizing extracting information from Chinese medicine literature seems more convenient than hand searching, which could simplify searching process and improve the accuracy. However, many computerized auto-extracting methods are increasingly used, regular expression is so special that could be efficient for extracting useful information in research. This article focused on regular expression applying in extracting information from Chinese medicine literature. Two practical examples were reported in this article about regular expression to extract "case number (non-terminology)" and "efficacy rate (subgroups for related information identification)", which explored how to extract information in Chinese medicine literature by means of some special research method.

Fiber-laser frequency combs for the generation of tunable single-frequency laser lines, mm- and THz-waves and sinc-shaped Nyquist pulses

NASA Astrophysics Data System (ADS)

Schneider, Thomas

2015-03-01

High-quality frequency comb sources like femtosecond-lasers have revolutionized the metrology of fundamental physical constants. The generated comb consists of frequency lines with an equidistant separation over a bandwidth of several THz. This bandwidth can be broadened further to a super-continuum of more than an octave through propagation in nonlinear media. The frequency separation between the lines is defined by the repetition rate and the width of each comb line can be below 1 Hz, even without external stabilization. By extracting just one of these lines, an ultra-narrow linewidth, tunable laser line for applications in communications and spectroscopy can be generated. If two lines are extracted, the superposition of these lines in an appropriate photo-mixer produces high-quality millimeter- and THz-waves. The extraction of several lines can be used for the creation of almost-ideally sinc-shaped Nyquist pulses, which enable optical communications with the maximum-possible baud rate. Especially combs generated by low-cost, small-footprint fs-fiber lasers are very promising. However due to the resonator length, the comb frequencies have a typical separation of 80 - 100 MHz, far too narrow for the selection of single tones with standard optical filters. Here the extraction of single lines of an fs-fiber laser by polarization pulling assisted stimulated Brillouin scattering is presented. The application of these extracted lines as ultra-narrow, stable and tunable laser lines, for the generation of very high-quality mm and THz-waves with an ultra-narrow linewidth and phase noise and for the generation of sinc-shaped Nyquist pulses with arbitrary bandwidth and repetition rate is discussed.

Triton X-114 based cloud point extraction: a thermoreversible approach for separation/concentration and dispersion of nanomaterials in the aqueous phase.

PubMed

Liu, Jing-fu; Liu, Rui; Yin, Yong-guang; Jiang, Gui-bin

2009-03-28

Capable of preserving the sizes and shapes of nanomaterials during the phase transferring, Triton X-114 based cloud point extraction provides a general, simple, and cost-effective route for reversible concentration/separation or dispersion of various nanomaterials in the aqueous phase.

Combining heterogenous features for 3D hand-held object recognition

NASA Astrophysics Data System (ADS)

Lv, Xiong; Wang, Shuang; Li, Xiangyang; Jiang, Shuqiang

2014-10-01

Object recognition has wide applications in the area of human-machine interaction and multimedia retrieval. However, due to the problem of visual polysemous and concept polymorphism, it is still a great challenge to obtain reliable recognition result for the 2D images. Recently, with the emergence and easy availability of RGB-D equipment such as Kinect, this challenge could be relieved because the depth channel could bring more information. A very special and important case of object recognition is hand-held object recognition, as hand is a straight and natural way for both human-human interaction and human-machine interaction. In this paper, we study the problem of 3D object recognition by combining heterogenous features with different modalities and extraction techniques. For hand-craft feature, although it reserves the low-level information such as shape and color, it has shown weakness in representing hiconvolutionalgh-level semantic information compared with the automatic learned feature, especially deep feature. Deep feature has shown its great advantages in large scale dataset recognition but is not always robust to rotation or scale variance compared with hand-craft feature. In this paper, we propose a method to combine hand-craft point cloud features and deep learned features in RGB and depth channle. First, hand-held object segmentation is implemented by using depth cues and human skeleton information. Second, we combine the extracted hetegerogenous 3D features in different stages using linear concatenation and multiple kernel learning (MKL). Then a training model is used to recognize 3D handheld objects. Experimental results validate the effectiveness and gerneralization ability of the proposed method.

Changes in corneal shape after suture cutting using the argon laser for postoperative astigmatism following cataract extraction.

PubMed

Hayashi, K; Nakao, F; Hayashi, F

1993-03-01

We studied the changes in corneal shape after suture cutting with an argon laser to reduce corneal astigmatism following cataract extraction. Sixty-two patients who exhibited high with-the-rule astigmatism (> 3 diopters [D]) following extracapsular lens extraction had argon laser suture cutting. The patients were classified into three groups: Group A comprised 30 patients whose sutures were cut two to three months after planned extracapsular cataract extraction (p-ECCE); Group B consisted of eight patients who had the same treatment five to nine months after p-ECCE; Group C comprised 24 patients who had the treatment one to two months after phacoemulsification (PE). The dioptric reduction of corneal astigmatism (the percent reduction of astigmatism) was 1.83 +/- 0.98 D (37.4 +/- 18.3%) in Group A, 3.20 +/- 2.35 D (55.6 +/- 34.4%) in Group B, and 2.08 +/- 1.20 D (41.4 +/- 20.4%) in Group C. There was no statistical significance in the dioptric reduction and the percent reduction among Groups A, B, and C. This suggests that the wound size and time of cutting are not directly correlated to the effect of argon laser suture cutting. To examine the relationship between the effect and changes in corneal shape from suture cutting, we divided the patients into two subgroups; one was Subgroup (+) in which the percent reduction of astigmatism was above 25%; the other was Subgroup (-) in which the percent reduction was below 25%.(ABSTRACT TRUNCATED AT 250 WORDS)

Effects of ionic surfactants on the morphology of silver nanoparticles using Paan (Piper betel) leaf petiole extract.

PubMed

Khan, Zaheer; Bashir, Ommer; Hussain, Javed Ijaz; Kumar, Sunil; Ahmad, Rabia

2012-10-01

Stable silver nanoparticles were synthesized by the reduction of silver ions with a Paan (Piper betel) leaf petiole extract in absence and presence of cetyltrimethylammonium bromide (CTAB) and sodium dodecyl sulphate (SDS). The reaction process was simple and convenient to handle, and was monitored using ultraviolet-visible spectroscopy. Absorbance of Ag-nanoparticles increases with the concentrations of Paan leaf extract, acts as reducing, stabilizing and capping agents. The polyphenolic groups of petiole extract are responsible to the rapid reduction of Ag(+) ions into metallic Ag(0). The results indicated that the shape of the spectra, number of peaks and its position strongly depend on the concentration of CTAB, which played a shape-controlling role during the formation of silver nanoparticles in the solutions, whereas SDS has no significant effect. The morphology (spherical, truncated triangular polyhedral plate and some irregular nanoparticles) and crystalline phase of the particles were determined from transmission electron microscopy (TEM) and selected area electron diffraction (SAED). Copyright © 2012 Elsevier B.V. All rights reserved.

An augmented Lagrangian trust region method for inclusion boundary reconstruction using ultrasound/electrical dual-modality tomography

NASA Astrophysics Data System (ADS)

Liang, Guanghui; Ren, Shangjie; Dong, Feng

2018-07-01

The ultrasound/electrical dual-modality tomography utilizes the complementarity of ultrasound reflection tomography (URT) and electrical impedance tomography (EIT) to improve the speed and accuracy of image reconstruction. Due to its advantages of no-invasive, no-radiation and low-cost, ultrasound/electrical dual-modality tomography has attracted much attention in the field of dual-modality imaging and has many potential applications in industrial and biomedical imaging. However, the data fusion of URT and EIT is difficult due to their different theoretical foundations and measurement principles. The most commonly used data fusion strategy in ultrasound/electrical dual-modality tomography is incorporating the structured information extracted from the URT into the EIT image reconstruction process through a pixel-based constraint. Due to the inherent non-linearity and ill-posedness of EIT, the reconstructed images from the strategy suffer from the low resolution, especially at the boundary of the observed inclusions. To improve this condition, an augmented Lagrangian trust region method is proposed to directly reconstruct the shapes of the inclusions from the ultrasound/electrical dual-modality measurements. In the proposed method, the shape of the target inclusion is parameterized by a radial shape model whose coefficients are used as the shape parameters. Then, the dual-modality shape inversion problem is formulated by an energy minimization problem in which the energy function derived from EIT is constrained by an ultrasound measurements model through an equality constraint equation. Finally, the optimal shape parameters associated with the optimal inclusion shape guesses are determined by minimizing the constrained cost function using the augmented Lagrangian trust region method. To evaluate the proposed method, numerical tests are carried out. Compared with single modality EIT, the proposed dual-modality inclusion boundary reconstruction method has a higher accuracy and is more robust to the measurement noise.

Some new classification methods for hyperspectral remote sensing

NASA Astrophysics Data System (ADS)

Du, Pei-jun; Chen, Yun-hao; Jones, Simon; Ferwerda, Jelle G.; Chen, Zhi-jun; Zhang, Hua-peng; Tan, Kun; Yin, Zuo-xia

2006-10-01

Hyperspectral Remote Sensing (HRS) is one of the most significant recent achievements of Earth Observation Technology. Classification is the most commonly employed processing methodology. In this paper three new hyperspectral RS image classification methods are analyzed. These methods are: Object-oriented FIRS image classification, HRS image classification based on information fusion and HSRS image classification by Back Propagation Neural Network (BPNN). OMIS FIRS image is used as the example data. Object-oriented techniques have gained popularity for RS image classification in recent years. In such method, image segmentation is used to extract the regions from the pixel information based on homogeneity criteria at first, and spectral parameters like mean vector, texture, NDVI and spatial/shape parameters like aspect ratio, convexity, solidity, roundness and orientation for each region are calculated, finally classification of the image using the region feature vectors and also using suitable classifiers such as artificial neural network (ANN). It proves that object-oriented methods can improve classification accuracy since they utilize information and features both from the point and the neighborhood, and the processing unit is a polygon (in which all pixels are homogeneous and belong to the class). HRS image classification based on information fusion, divides all bands of the image into different groups initially, and extracts features from every group according to the properties of each group. Three levels of information fusion: data level fusion, feature level fusion and decision level fusion are used to HRS image classification. Artificial Neural Network (ANN) can perform well in RS image classification. In order to promote the advances of ANN used for HIRS image classification, Back Propagation Neural Network (BPNN), the most commonly used neural network, is used to HRS image classification.

Experimental evaluation of x-ray acoustic computed tomography for radiotherapy dosimetry applications.

PubMed

Hickling, Susannah; Lei, Hao; Hobson, Maritza; Léger, Pierre; Wang, Xueding; El Naqa, Issam

2017-02-01

The aim of this work was to experimentally demonstrate the feasibility of x-ray acoustic computed tomography (XACT) as a dosimetry tool in a clinical radiotherapy environment. The acoustic waves induced following a single pulse of linear accelerator irradiation in a water tank were detected with an immersion ultrasound transducer. By rotating the collimator and keeping the transducer stationary, acoustic signals at varying angles surrounding the field were detected and reconstructed to form an XACT image. Simulated XACT images were obtained using a previously developed simulation workflow. Profiles extracted from experimental and simulated XACT images were compared to profiles measured with an ion chamber. A variety of radiation field sizes and shapes were investigated. XACT images resembling the geometry of the delivered radiation field were obtained for fields ranging from simple squares to more complex shapes. When comparing profiles extracted from simulated and experimental XACT images of a 4 cm × 4 cm field, 97% of points were found to pass a 3%/3 mm gamma test. Agreement between simulated and experimental XACT images worsened when comparing fields with fine details. Profiles extracted from experimental XACT images were compared to profiles obtained through clinical ion chamber measurements, confirming that the intensity of XACT images is related to deposited radiation dose. Seventy-seven percent of the points in a profile extracted from an experimental XACT image of a 4 cm × 4 cm field passed a 7%/4 mm gamma test when compared to an ion chamber measured profile. In a complicated puzzle-piece shaped field, 86% of the points in an XACT extracted profile passed a 7%/4 mm gamma test. XACT images with intensity related to the spatial distribution of deposited dose in a water tank were formed for a variety of field sizes and shapes. XACT has the potential to be a useful tool for absolute, relative and in vivo dosimetry. © 2016 American Association of Physicists in Medicine.

Challenges in Managing Information Extraction

ERIC Educational Resources Information Center

Shen, Warren H.

2009-01-01

This dissertation studies information extraction (IE), the problem of extracting structured information from unstructured data. Example IE tasks include extracting person names from news articles, product information from e-commerce Web pages, street addresses from emails, and names of emerging music bands from blogs. IE is all increasingly…

Hybrid Signal Processing Technique to Improve the Defect Estimation in Ultrasonic Non-Destructive Testing of Composite Structures

PubMed Central

Raisutis, Renaldas; Samaitis, Vykintas

2017-01-01

This work proposes a novel hybrid signal processing technique to extract information on disbond-type defects from a single B-scan in the process of non-destructive testing (NDT) of glass fiber reinforced plastic (GFRP) material using ultrasonic guided waves (GW). The selected GFRP sample has been a segment of wind turbine blade, which possessed an aerodynamic shape. Two disbond type defects having diameters of 15 mm and 25 mm were artificially constructed on its trailing edge. The experiment has been performed using the low-frequency ultrasonic system developed at the Ultrasound Institute of Kaunas University of Technology and only one side of the sample was accessed. A special configuration of the transmitting and receiving transducers fixed on a movable panel with a separation distance of 50 mm was proposed for recording the ultrasonic guided wave signals at each one-millimeter step along the scanning distance up to 500 mm. Finally, the hybrid signal processing technique comprising the valuable features of the three most promising signal processing techniques: cross-correlation, wavelet transform, and Hilbert–Huang transform has been applied to the received signals for the extraction of defects information from a single B-scan image. The wavelet transform and cross-correlation techniques have been combined in order to extract the approximated size and location of the defects and measurements of time delays. Thereafter, Hilbert–Huang transform has been applied to the wavelet transformed signal to compare the variation of instantaneous frequencies and instantaneous amplitudes of the defect-free and defective signals. PMID:29232845

Blood vessel-based liver segmentation through the portal phase of a CT dataset

NASA Astrophysics Data System (ADS)

Maklad, Ahmed S.; Matsuhiro, Mikio; Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Moriyama, Noriyuki; Utsunomiya, Toru; Shimada, Mitsuo

2013-02-01

Blood vessels are dispersed throughout the human body organs and carry unique information for each person. This information can be used to delineate organ boundaries. The proposed method relies on abdominal blood vessels (ABV) to segment the liver considering the potential presence of tumors through the portal phase of a CT dataset. ABV are extracted and classified into hepatic (HBV) and nonhepatic (non-HBV) with a small number of interactions. HBV and non-HBV are used to guide an automatic segmentation of the liver. HBV are used to individually segment the core region of the liver. This region and non-HBV are used to construct a boundary surface between the liver and other organs to separate them. The core region is classified based on extracted posterior distributions of its histogram into low intensity tumor (LIT) and non-LIT core regions. Non-LIT case includes normal part of liver, HBV, and high intensity tumors if exist. Each core region is extended based on its corresponding posterior distribution. Extension is completed when it reaches either a variation in intensity or the constructed boundary surface. The method was applied to 80 datasets (30 Medical Image Computing and Computer Assisted Intervention (MICCAI) and 50 non-MICCAI data) including 60 datasets with tumors. Our results for the MICCAI-test data were evaluated by sliver07 [1] with an overall score of 79.7, which ranks seventh best on the site (December 2013). This approach seems a promising method for extraction of liver volumetry of various shapes and sizes and low intensity hepatic tumors.

Potential High-Temperature Shape-Memory-Alloy Actuator Material Identified

NASA Technical Reports Server (NTRS)

Noebe, Ronald D.; Gaydosh, Darrell J.; Biles, Tiffany A.; Garg, Anita

2005-01-01

Shape-memory alloys are unique "smart materials" that can be used in a wide variety of adaptive or "intelligent" components. Because of a martensitic solid-state phase transformation in these materials, they can display rather unusual mechanical properties including shape-memory behavior. This phenomenon occurs when the material is deformed at low temperatures (below the martensite finish temperature, Mf) and then heated through the martensite-to-austenite phase transformation. As the material is heated to the austenite finish temperature Af, it is able to recover its predeformed shape. If a bias is applied to the material as it tries to recover its original shape, work can be extracted from the shape-memory alloy as it transforms. Therefore, shape-memory alloys are being considered for compact solid-state actuation devices to replace hydraulic, pneumatic, or motor-driven systems.

Mutual information-based feature selection for radiomics

NASA Astrophysics Data System (ADS)

Oubel, Estanislao; Beaumont, Hubert; Iannessi, Antoine

2016-03-01

Background The extraction and analysis of image features (radiomics) is a promising field in the precision medicine era, with applications to prognosis, prediction, and response to treatment quantification. In this work, we present a mutual information - based method for quantifying reproducibility of features, a necessary step for qualification before their inclusion in big data systems. Materials and Methods Ten patients with Non-Small Cell Lung Cancer (NSCLC) lesions were followed over time (7 time points in average) with Computed Tomography (CT). Five observers segmented lesions by using a semi-automatic method and 27 features describing shape and intensity distribution were extracted. Inter-observer reproducibility was assessed by computing the multi-information (MI) of feature changes over time, and the variability of global extrema. Results The highest MI values were obtained for volume-based features (VBF). The lesion mass (M), surface to volume ratio (SVR) and volume (V) presented statistically significant higher values of MI than the rest of features. Within the same VBF group, SVR showed also the lowest variability of extrema. The correlation coefficient (CC) of feature values was unable to make a difference between features. Conclusions MI allowed to discriminate three features (M, SVR, and V) from the rest in a statistically significant manner. This result is consistent with the order obtained when sorting features by increasing values of extrema variability. MI is a promising alternative for selecting features to be considered as surrogate biomarkers in a precision medicine context.

Amplitude interpretation and visualization of three-dimensional reflection data

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

Enachescu, M.E.

1994-07-01

Digital recording and processing of modern three-dimensional surveys allow for relative good preservation and correct spatial positioning of seismic reflection amplitude. A four-dimensional seismic reflection field matrix R (x,y,t,A), which can be computer visualized (i.e., real-time interactively rendered, edited, and animated), is now available to the interpreter. The amplitude contains encoded geological information indirectly related to lithologies and reservoir properties. The magnitude of the amplitude depends not only on the acoustic impedance contrast across a boundary, but is also strongly affected by the shape of the reflective boundary. This allows the interpreter to image subtle tectonic and structural elements notmore » obvious on time-structure maps. The use of modern workstations allows for appropriate color coding of the total available amplitude range, routine on-screen time/amplitude extraction, and late display of horizon amplitude maps (horizon slices) or complex amplitude-structure spatial visualization. Stratigraphic, structural, tectonic, fluid distribution, and paleogeographic information are commonly obtained by displaying the amplitude variation A = A(x,y,t) associated with a particular reflective surface or seismic interval. As illustrated with several case histories, traditional structural and stratigraphic interpretation combined with a detailed amplitude study generally greatly enhance extraction of subsurface geological information from a reflection data volume. In the context of three-dimensional seismic surveys, the horizon amplitude map (horizon slice), amplitude attachment to structure and [open quotes]bright clouds[close quotes] displays are very powerful tools available to the interpreter.« less

Assessment of spatial information for hyperspectral imaging of lesion

NASA Astrophysics Data System (ADS)

Yang, Xue; Li, Gang; Lin, Ling

2016-10-01

Multiple diseases such as breast tumor poses a great threat to women's health and life, while the traditional detection method is complex, costly and unsuitable for frequently self-examination, therefore, an inexpensive, convenient and efficient method for tumor self-inspection is needed urgently, and lesion localization is an important step. This paper proposes an self-examination method for positioning of a lesion. The method adopts transillumination to acquire the hyperspectral images and to assess the spatial information of lesion. Firstly, multi-wavelength sources are modulated with frequency division, which is advantageous to separate images of different wavelength, meanwhile, the source serves as fill light to each other to improve the sensitivity in the low-lightlevel imaging. Secondly, the signal-to-noise ratio of transmitted images after demodulation are improved by frame accumulation technology. Next, gray distributions of transmitted images are analyzed. The gray-level differences is constituted by the actual transmitted images and fitting transmitted images of tissue without lesion, which is to rule out individual differences. Due to scattering effect, there will be transition zones between tissue and lesion, and the zone changes with wavelength change, which will help to identify the structure details of lesion. Finally, image segmentation is adopted to extract the lesion and the transition zones, and the spatial features of lesion are confirmed according to the transition zones and the differences of transmitted light intensity distributions. Experiment using flat-shaped tissue as an example shows that the proposed method can extract the space information of lesion.

Introducing Urtica dioica, A Native Plant of Khuzestan, As an Antibacterial Medicinal Plant

PubMed Central

Motamedi, Hossein; Seyyednejad, Seyyed Mansour; Bakhtiari, Ameneh; Vafaei, Mozhan

2014-01-01

Background: Urtica dioica is a flowering plant with long history of use in folk medicine and as a food source. Objectives: This study examined in vitro antibacterial potential of alcoholic extracts of U. dioica. Materials and Methods: Hydroalcoholic extracts from aerial parts were prepared using aqueous solution of ethanol and methanol and their inhibitory effects against clinical isolates was examined by disc diffusion method at different doses. Minimum inhibitory concentrations (MIC) and minimum bactericidal concentration (MBC) indexes were also investigated. The scanning electron microscopy (SEM) analysis was also performed to find structural changes of affected bacteria consequent to exposing with extracts. Results: Both extracts were active against Bacillus cereus, Staphylococcus aureus, Staphylococcus epidermidis, and Escherichia coli with respectively 16, 10, 18, and 14 mm (methanolic) and 11, 9, 17, and 16 mm (ethanolic) inhibition zone. The MIC of ethanolic extract against S. epidermidis and E. coli was respectively 10 and 40 mg/mL. The MIC of methanolic extract against S. aureus and S. epidermidis was 40 and 10 mg/mL, respectively. The MBC was found only for S. epidermidis (20 mg/mL). In SEM analysis the round shape of S. epidermidis was changed and irregular shapes were appeared, which suggest that the main target of these extracts was cell wall. Conclusions: Extracts of U. dioica showed significant antibacterial effect against some clinically important pathogenic bacteria. Based on the obtained results it can be concluded that U. dioica is useful as antibacterial and bactericidal agent in treating infectious diseases. PMID:25625045

a Probability-Based Statistical Method to Extract Water Body of TM Images with Missing Information

NASA Astrophysics Data System (ADS)

Lian, Shizhong; Chen, Jiangping; Luo, Minghai

2016-06-01

Water information cannot be accurately extracted using TM images because true information is lost in some images because of blocking clouds and missing data stripes, thereby water information cannot be accurately extracted. Water is continuously distributed in natural conditions; thus, this paper proposed a new method of water body extraction based on probability statistics to improve the accuracy of water information extraction of TM images with missing information. Different disturbing information of clouds and missing data stripes are simulated. Water information is extracted using global histogram matching, local histogram matching, and the probability-based statistical method in the simulated images. Experiments show that smaller Areal Error and higher Boundary Recall can be obtained using this method compared with the conventional methods.

Automatic firearm class identification from cartridge cases

NASA Astrophysics Data System (ADS)

Kamalakannan, Sridharan; Mann, Christopher J.; Bingham, Philip R.; Karnowski, Thomas P.; Gleason, Shaun S.

2011-03-01

We present a machine vision system for automatic identification of the class of firearms by extracting and analyzing two significant properties from spent cartridge cases, namely the Firing Pin Impression (FPI) and the Firing Pin Aperture Outline (FPAO). Within the framework of the proposed machine vision system, a white light interferometer is employed to image the head of the spent cartridge cases. As a first step of the algorithmic procedure, the Primer Surface Area (PSA) is detected using a circular Hough transform. Once the PSA is detected, a customized statistical region-based parametric active contour model is initialized around the center of the PSA and evolved to segment the FPI. Subsequently, the scaled version of the segmented FPI is used to initialize a customized Mumford-Shah based level set model in order to segment the FPAO. Once the shapes of FPI and FPAO are extracted, a shape-based level set method is used in order to compare these extracted shapes to an annotated dataset of FPIs and FPAOs from varied firearm types. A total of 74 cartridge case images non-uniformly distributed over five different firearms are processed using the aforementioned scheme and the promising nature of the results (95% classification accuracy) demonstrate the efficacy of the proposed approach.

Information extraction system

DOEpatents

Lemmond, Tracy D; Hanley, William G; Guensche, Joseph Wendell; Perry, Nathan C; Nitao, John J; Kidwell, Paul Brandon; Boakye, Kofi Agyeman; Glaser, Ron E; Prenger, Ryan James

2014-05-13

An information extraction system and methods of operating the system are provided. In particular, an information extraction system for performing meta-extraction of named entities of people, organizations, and locations as well as relationships and events from text documents are described herein.

Extracting and shaping the light of OLED devices

NASA Astrophysics Data System (ADS)

Riedel, Daniel; Dlugosch, Julian; Wehlus, Thomas; Brabec, Christoph

2015-09-01

Before the market entry of organic light emitting diodes (OLEDs) into the field of general illumination can occur, limitations in lifetime, luminous efficacy and cost must be overcome. Additional requirements for OLEDs used for general illumination may be imposed by workplace glare reduction requirements, which demand limited luminance for high viewing angles. These requirements contrast with the typical lambertian emission characteristics of OLEDs, which result in the same luminance levels for all emission angles. As a consequence, without additional measures glare reduction could limit the maximum possible luminance of lambertian OLEDs to relatively low levels. However, high luminance levels are still desirable in order to obtain high light output. We are presenting solutions to overcome this dilemma. Therefore this work is focused on light-shaping structures for OLEDs with an internal light extraction layer. Simulations of beam-shaping structures and shapes are presented, followed by experimental measurements to verify the simulations of the most promising structures. An investigation of the loss channels has been carried out and the overall optical system efficiency was evaluated for all structures. The most promising light shaping structures achieve system efficiencies up to 80%. Finally, a general illumination application scenario has been simulated. The number of OLEDs needed to illuminate an office room has been deduced from this scenario. By using light-shaping structures for OLEDs, the number of OLEDs needed to reach the mandatory illuminance level for a workplace environment can be reduced to one third compared to lambertian OLEDs.

Efficiency of extracting stereo-driven object motions

PubMed Central

Jain, Anshul; Zaidi, Qasim

2013-01-01

Most living things and many nonliving things deform as they move, requiring observers to separate object motions from object deformations. When the object is partially occluded, the task becomes more difficult because it is not possible to use two-dimensional (2-D) contour correlations (Cohen, Jain, & Zaidi, 2010). That leaves dynamic depth matching across the unoccluded views as the main possibility. We examined the role of stereo cues in extracting motion of partially occluded and deforming three-dimensional (3-D) objects, simulated by disk-shaped random-dot stereograms set at randomly assigned depths and placed uniformly around a circle. The stereo-disparities of the disks were temporally oscillated to simulate clockwise or counterclockwise rotation of the global shape. To dynamically deform the global shape, random disparity perturbation was added to each disk's depth on each stimulus frame. At low perturbation, observers reported rotation directions consistent with the global shape, even against local motion cues, but performance deteriorated at high perturbation. Using 3-D global shape correlations, we formulated an optimal Bayesian discriminator for rotation direction. Based on rotation discrimination thresholds, human observers were 75% as efficient as the optimal model, demonstrating that global shapes derived from stereo cues facilitate inferences of object motions. To complement reports of stereo and motion integration in extrastriate cortex, our results suggest the possibilities that disparity selectivity and feature tracking are linked, or that global motion selective neurons can be driven purely from disparity cues. PMID:23325345

Synthesis of gold nanostructures using fruit extract of Garcinia Indica

NASA Astrophysics Data System (ADS)

Krishnaprabha, M.; Pattabi, Manjunatha

2016-05-01

Gold nanoparticles having different shapes are synthesized using extract of fresh fruit rinds of Garcinia Indica. The onset of growth and formation of gold nanostructures is confirmed from UV-Vis spectroscopy. Morphological studies are done using FESEM. Size dependent catalytic activity is evaluated with the model reduction reaction of 4-nitrophenol to 4-aminophenol.

Biosynthesis of gold nanoparticles using Capsicum annuum var. grossum pulp extract and its catalytic activity

NASA Astrophysics Data System (ADS)

Yuan, Chun-Gang; Huo, Can; Yu, Shuixin; Gui, Bing

2017-01-01

Biological synthesis approach has been regarded as a green, eco-friendly and cost effective method for nanoparticles preparation without any toxic solvents and hazardous bi-products during the process. This present study reported a facile and rapid biosynthesis method for gold nanoparticles (GNPs) from Capsicum annuum var. grossum pulp extract in a single-pot process. The aqueous pulp extract was used as biotic reducing agent for gold nanoparticle growing. Various shapes (triangle, hexagonal, and quasi-spherical shapes) were observed within range of 6-37 nm. The UV-Vis spectra showed surface plasmon resonance (SPR) peak for the formed GNPs at 560 nm after 10 min incubation at room temperature. The possible influences of extract amount, gold ion concentration, incubation time, reaction temperature and solution pH were evaluated to obtain the optimized synthesis conditions. The effects of the experimental factors on NPs synthesis process were also discussed. The produced gold nanoparticles were characterized by transform electron microscopy (TEM), X-ray diffraction (XRD), energy dispersive X-ray (EDS) and Fourier Transform infrared spectroscopy (FTIR). The results demonstrated that the as-obtained GNPs were well dispersed and stable with good catalytic activity. Biomolecules in the aqueous extract were responsible for the capping and stabilization of GNPs.

A Developmental Study of Shape Integration Over Space and Time.

ERIC Educational Resources Information Center

Enns, James T.; Girgus, Joan S.

1986-01-01

Three experiments with observers aged 6 to 21 years of age examined the integration of shape information over successive glances. Results indicated age-related improvements in the sequential integration of shape information, both when integration occurs through successive glimpses over space and when information is separated only in time. (HOD)

Analyzing tree-shape anatomical structures using topological descriptors of branching and ensemble of classifiers.

PubMed

Skoura, Angeliki; Bakic, Predrag R; Megalooikonomou, Vasilis

2013-01-01

The analysis of anatomical tree-shape structures visualized in medical images provides insight into the relationship between tree topology and pathology of the corresponding organs. In this paper, we propose three methods to extract descriptive features of the branching topology; the asymmetry index, the encoding of branching patterns using a node labeling scheme and an extension of the Sholl analysis. Based on these descriptors, we present classification schemes for tree topologies with respect to the underlying pathology. Moreover, we present a classifier ensemble approach which combines the predictions of the individual classifiers to optimize the classification accuracy. We applied the proposed methodology to a dataset of x-ray galactograms, medical images which visualize the breast ductal tree, in order to recognize images with radiological findings regarding breast cancer. The experimental results demonstrate the effectiveness of the proposed framework compared to state-of-the-art techniques suggesting that the proposed descriptors provide more valuable information regarding the topological patterns of ductal trees and indicating the potential of facilitating early breast cancer diagnosis.

Analyzing tree-shape anatomical structures using topological descriptors of branching and ensemble of classifiers

PubMed Central

Skoura, Angeliki; Bakic, Predrag R.; Megalooikonomou, Vasilis

2014-01-01

The analysis of anatomical tree-shape structures visualized in medical images provides insight into the relationship between tree topology and pathology of the corresponding organs. In this paper, we propose three methods to extract descriptive features of the branching topology; the asymmetry index, the encoding of branching patterns using a node labeling scheme and an extension of the Sholl analysis. Based on these descriptors, we present classification schemes for tree topologies with respect to the underlying pathology. Moreover, we present a classifier ensemble approach which combines the predictions of the individual classifiers to optimize the classification accuracy. We applied the proposed methodology to a dataset of x-ray galactograms, medical images which visualize the breast ductal tree, in order to recognize images with radiological findings regarding breast cancer. The experimental results demonstrate the effectiveness of the proposed framework compared to state-of-the-art techniques suggesting that the proposed descriptors provide more valuable information regarding the topological patterns of ductal trees and indicating the potential of facilitating early breast cancer diagnosis. PMID:25414850

Prospects for cosmological collider physics

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

Meerburg, P. Daniel; Münchmeyer, Moritz; Muñoz, Julian B.

2017-03-01

It is generally expected that heavy fields are present during inflation, which can leave their imprint in late-time cosmological observables. The main signature of these fields is a small amount of distinctly shaped non-Gaussianity, which if detected, would provide a wealth of information about the particle spectrum of the inflationary Universe. Here we investigate to what extent these signatures can be detected or constrained using futuristic 21-cm surveys. We construct model-independent templates that extract the squeezed-limit behavior of the bispectrum, and examine their overlap with standard inflationary shapes and secondary non-Gaussianities. We then use these templates to forecast detection thresholdsmore » for different masses and couplings using a 3D reconstruction of modes during the dark ages ( z ∼ 30–100). We consider interactions of several broad classes of models and quantify their detectability as a function of the baseline of a dark ages interferometer. Our analysis shows that there exists the tantalizing possibility of discovering new particles with different masses and interactions with future 21-cm surveys.« less

Importance of the Correlation between Width and Length in the Shape Analysis of Nanorods: Use of a 2D Size Plot To Probe Such a Correlation.

PubMed

Zhao, Zhihua; Zheng, Zhiqin; Roux, Clément; Delmas, Céline; Marty, Jean-Daniel; Kahn, Myrtil L; Mingotaud, Christophe

2016-08-22

Analysis of nanoparticle size through a simple 2D plot is proposed in order to extract the correlation between length and width in a collection or a mixture of anisotropic particles. Compared to the usual statistics on the length associated with a second and independent statistical analysis of the width, this simple plot easily points out the various types of nanoparticles and their (an)isotropy. For each class of nano-objects, the relationship between width and length (i.e., the strong or weak correlations between these two parameters) may suggest information concerning the nucleation/growth processes. It allows one to follow the effect on the shape and size distribution of physical or chemical processes such as simple ripening. Various electron microscopy pictures from the literature or from the authors' own syntheses are used as examples to demonstrate the efficiency and simplicity of the proposed 2D plot combined with a multivariate analysis. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

UFCN: a fully convolutional neural network for road extraction in RGB imagery acquired by remote sensing from an unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Kestur, Ramesh; Farooq, Shariq; Abdal, Rameen; Mehraj, Emad; Narasipura, Omkar; Mudigere, Meenavathi

2018-01-01

Road extraction in imagery acquired by low altitude remote sensing (LARS) carried out using an unmanned aerial vehicle (UAV) is presented. LARS is carried out using a fixed wing UAV with a high spatial resolution vision spectrum (RGB) camera as the payload. Deep learning techniques, particularly fully convolutional network (FCN), are adopted to extract roads by dense semantic segmentation. The proposed model, UFCN (U-shaped FCN) is an FCN architecture, which is comprised of a stack of convolutions followed by corresponding stack of mirrored deconvolutions with the usage of skip connections in between for preserving the local information. The limited dataset (76 images and their ground truths) is subjected to real-time data augmentation during training phase to increase the size effectively. Classification performance is evaluated using precision, recall, accuracy, F1 score, and brier score parameters. The performance is compared with support vector machine (SVM) classifier, a one-dimensional convolutional neural network (1D-CNN) model, and a standard two-dimensional CNN (2D-CNN). The UFCN model outperforms the SVM, 1D-CNN, and 2D-CNN models across all the performance parameters. Further, the prediction time of the proposed UFCN model is comparable with SVM, 1D-CNN, and 2D-CNN models.

An Active Contour Model Based on Adaptive Threshold for Extraction of Cerebral Vascular Structures.

PubMed

Wang, Jiaxin; Zhao, Shifeng; Liu, Zifeng; Tian, Yun; Duan, Fuqing; Pan, Yutong

2016-01-01

Cerebral vessel segmentation is essential and helpful for the clinical diagnosis and the related research. However, automatic segmentation of brain vessels remains challenging because of the variable vessel shape and high complex of vessel geometry. This study proposes a new active contour model (ACM) implemented by the level-set method for segmenting vessels from TOF-MRA data. The energy function of the new model, combining both region intensity and boundary information, is composed of two region terms, one boundary term and one penalty term. The global threshold representing the lower gray boundary of the target object by maximum intensity projection (MIP) is defined in the first-region term, and it is used to guide the segmentation of the thick vessels. In the second term, a dynamic intensity threshold is employed to extract the tiny vessels. The boundary term is used to drive the contours to evolve towards the boundaries with high gradients. The penalty term is used to avoid reinitialization of the level-set function. Experimental results on 10 clinical brain data sets demonstrate that our method is not only able to achieve better Dice Similarity Coefficient than the global threshold based method and localized hybrid level-set method but also able to extract whole cerebral vessel trees, including the thin vessels.

From three-dimensional long-term tectonic numerical models to synthetic structural data: semi-automatic extraction of instantaneous & finite strain quantities

NASA Astrophysics Data System (ADS)

Duclaux, Guillaume; May, Dave

2017-04-01

Over the past three decades thermo-mechanical numerical modelling has transformed the way we look at deformation in the lithosphere. More than just generating aesthetically pleasing pictures, the output from a numerical models contains a rich source of quantitative information that can be used to measure deformation quantities in plan view or three-dimensions. Adding value to any numerical experiment requires a thorough post-processing of the modelling results. Such work aims to produce visual information that will resonate to seasoned structural geologists and assist with comparing experimental and observational data. Here we introduce two methods to generate synthetic structural data from numerical model outputs. We first present an image processing and shape recognition workflow developed to extract the active faults orientation from surface velocity gradients. In order to measure the active faults lengths and directions along with their distribution at the surface of the model we implemented an automated sequential mapping technique based on the second invariant of the strain rate tensor and using a suite a python functions. Active fault direction measurements are achieved using a probabilistic method for extracting linear features orientation from any surface. This method has the undeniable advantage to avoid interpretation bias. Strike measurements for individual segments are weighted according to their length and orientation distribution data are presented in an equal-area moving average rose diagrams produced using a weighted method. Finally, we discuss a method for mapping finite strain in three-dimensions. A high-resolution Lagrangian regular grid which advects during the numerical experiment is used to track the progressive deformation within the model. Thanks to this data we can measure the finite strain ellipsoids for any region of interest in the model. This method assumes that the finite strain is homogenous within one unit cell of the grid. We can compute individual ellipsoid's parameters (orientation, shape, etc.) and represent the finite deformation for any region of interest in a Flinn diagram. In addition, we can use the finite strain ellipsoids to estimate the prevailing foliation and/or lineation directions anywhere in the model. These two methods are applied to measure the instantaneous and finite deformation patterns within an oblique rift zone ongoing constant extension in the absence of surface processes.

Vibration-based damage detection in wind turbine blades using Phase-based Motion Estimation and motion magnification

NASA Astrophysics Data System (ADS)

Sarrafi, Aral; Mao, Zhu; Niezrecki, Christopher; Poozesh, Peyman

2018-05-01

Vibration-based Structural Health Monitoring (SHM) techniques are among the most common approaches for structural damage identification. The presence of damage in structures may be identified by monitoring the changes in dynamic behavior subject to external loading, and is typically performed by using experimental modal analysis (EMA) or operational modal analysis (OMA). These tools for SHM normally require a limited number of physically attached transducers (e.g. accelerometers) in order to record the response of the structure for further analysis. Signal conditioners, wires, wireless receivers and a data acquisition system (DAQ) are also typical components of traditional sensing systems used in vibration-based SHM. However, instrumentation of lightweight structures with contact sensors such as accelerometers may induce mass-loading effects, and for large-scale structures, the instrumentation is labor intensive and time consuming. Achieving high spatial measurement resolution for a large-scale structure is not always feasible while working with traditional contact sensors, and there is also the potential for a lack of reliability associated with fixed contact sensors in outliving the life-span of the host structure. Among the state-of-the-art non-contact measurements, digital video cameras are able to rapidly collect high-density spatial information from structures remotely. In this paper, the subtle motions from recorded video (i.e. a sequence of images) are extracted by means of Phase-based Motion Estimation (PME) and the extracted information is used to conduct damage identification on a 2.3-m long Skystream® wind turbine blade (WTB). The PME and phased-based motion magnification approach estimates the structural motion from the captured sequence of images for both a baseline and damaged test cases on a wind turbine blade. Operational deflection shapes of the test articles are also quantified and compared for the baseline and damaged states. In addition, having proper lighting while working with high-speed cameras can be an issue, therefore image enhancement and contrast manipulation has also been performed to enhance the raw images. Ultimately, the extracted resonant frequencies and operational deflection shapes are used to detect the presence of damage, demonstrating the feasibility of implementing non-contact video measurements to perform realistic structural damage detection.

A survey of visual preprocessing and shape representation techniques

NASA Technical Reports Server (NTRS)

Olshausen, Bruno A.

1988-01-01

Many recent theories and methods proposed for visual preprocessing and shape representation are summarized. The survey brings together research from the fields of biology, psychology, computer science, electrical engineering, and most recently, neural networks. It was motivated by the need to preprocess images for a sparse distributed memory (SDM), but the techniques presented may also prove useful for applying other associative memories to visual pattern recognition. The material of this survey is divided into three sections: an overview of biological visual processing; methods of preprocessing (extracting parts of shape, texture, motion, and depth); and shape representation and recognition (form invariance, primitives and structural descriptions, and theories of attention).

Target Classification of Canonical Scatterers Using Classical Estimation and Dictionary Based Techniques

DTIC Science & Technology

2012-03-22

shapes tested , when the objective parameter set was confined to a dictionary’s de - fined parameter space. These physical characteristics included...8 2.3 Hypothesis Testing and Detection Theory . . . . . . . . . . . . . . . 8 2.4 3-D SAR Scattering Models...basis pursuit de -noising (BPDN) algorithm is chosen to perform extraction due to inherent efficiency and error tolerance. Multiple shape dictionaries

Segmentation of anterior cruciate ligament in knee MR images using graph cuts with patient-specific shape constraints and label refinement.

PubMed

Lee, Hansang; Hong, Helen; Kim, Junmo

2014-12-01

We propose a graph-cut-based segmentation method for the anterior cruciate ligament (ACL) in knee MRI with a novel shape prior and label refinement. As the initial seeds for graph cuts, candidates for the ACL and the background are extracted from knee MRI roughly by means of adaptive thresholding with Gaussian mixture model fitting. The extracted ACL candidate is segmented iteratively by graph cuts with patient-specific shape constraints. Two shape constraints termed fence and neighbor costs are suggested such that the graph cuts prevent any leakage into adjacent regions with similar intensity. The segmented ACL label is refined by means of superpixel classification. Superpixel classification makes the segmented label propagate into missing inhomogeneous regions inside the ACL. In the experiments, the proposed method segmented the ACL with Dice similarity coefficient of 66.47±7.97%, average surface distance of 2.247±0.869, and root mean squared error of 3.538±1.633, which increased the accuracy by 14.8%, 40.3%, and 37.6% from the Boykov model, respectively. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Role of Shape in Semantic Memory Organization of Objects: An Experimental Study Using PI-Release.

PubMed

van Weelden, Lisanne; Schilperoord, Joost; Swerts, Marc; Pecher, Diane

2015-01-01

Visual information contributes fundamentally to the process of object categorization. The present study investigated whether the degree of activation of visual information in this process is dependent on the contextual relevance of this information. We used the Proactive Interference (PI-release) paradigm. In four experiments, we manipulated the information by which objects could be categorized and subsequently be retrieved from memory. The pattern of PI-release showed that if objects could be stored and retrieved both by (non-perceptual) semantic and (perceptual) shape information, then shape information was overruled by semantic information. If, however, semantic information could not be (satisfactorily) used to store and retrieve objects, then objects were stored in memory in terms of their shape. The latter effect was found to be strongest for objects from identical semantic categories.

Topology based data analysis identifies a subgroup of breast cancers with a unique mutational profile and excellent survival.

PubMed

Nicolau, Monica; Levine, Arnold J; Carlsson, Gunnar

2011-04-26

High-throughput biological data, whether generated as sequencing, transcriptional microarrays, proteomic, or other means, continues to require analytic methods that address its high dimensional aspects. Because the computational part of data analysis ultimately identifies shape characteristics in the organization of data sets, the mathematics of shape recognition in high dimensions continues to be a crucial part of data analysis. This article introduces a method that extracts information from high-throughput microarray data and, by using topology, provides greater depth of information than current analytic techniques. The method, termed Progression Analysis of Disease (PAD), first identifies robust aspects of cluster analysis, then goes deeper to find a multitude of biologically meaningful shape characteristics in these data. Additionally, because PAD incorporates a visualization tool, it provides a simple picture or graph that can be used to further explore these data. Although PAD can be applied to a wide range of high-throughput data types, it is used here as an example to analyze breast cancer transcriptional data. This identified a unique subgroup of Estrogen Receptor-positive (ER(+)) breast cancers that express high levels of c-MYB and low levels of innate inflammatory genes. These patients exhibit 100% survival and no metastasis. No supervised step beyond distinction between tumor and healthy patients was used to identify this subtype. The group has a clear and distinct, statistically significant molecular signature, it highlights coherent biology but is invisible to cluster methods, and does not fit into the accepted classification of Luminal A/B, Normal-like subtypes of ER(+) breast cancers. We denote the group as c-MYB(+) breast cancer.

Rethinking CMB foregrounds: systematic extension of foreground parametrizations

NASA Astrophysics Data System (ADS)

Chluba, Jens; Hill, James Colin; Abitbol, Maximilian H.

2017-11-01

Future high-sensitivity measurements of the cosmic microwave background (CMB) anisotropies and energy spectrum will be limited by our understanding and modelling of foregrounds. Not only does more information need to be gathered and combined, but also novel approaches for the modelling of foregrounds, commensurate with the vast improvements in sensitivity, have to be explored. Here, we study the inevitable effects of spatial averaging on the spectral shapes of typical foreground components, introducing a moment approach, which naturally extends the list of foreground parameters that have to be determined through measurements or constrained by theoretical models. Foregrounds are thought of as a superposition of individual emitting volume elements along the line of sight and across the sky, which then are observed through an instrumental beam. The beam and line-of-sight averages are inevitable. Instead of assuming a specific model for the distributions of physical parameters, our method identifies natural new spectral shapes for each foreground component that can be used to extract parameter moments (e.g. mean, dispersion, cross terms, etc.). The method is illustrated for the superposition of power laws, free-free spectra, grey-body and modified blackbody spectra, but can be applied to more complicated fundamental spectral energy distributions. Here, we focus on intensity signals but the method can be extended to the case of polarized emission. The averaging process automatically produces scale-dependent spectral shapes and the moment method can be used to propagate the required information across scales in power spectrum estimates. The approach is not limited to applications to CMB foregrounds, but could also be useful for the modelling of X-ray emission in clusters of galaxies.

Beyond HRV: attractor reconstruction using the entire cardiovascular waveform data for novel feature extraction.

PubMed

Aston, Philip J; Christie, Mark I; Huang, Ying H; Nandi, Manasi

2018-03-01

Advances in monitoring technology allow blood pressure waveforms to be collected at sampling frequencies of 250-1000 Hz for long time periods. However, much of the raw data are under-analysed. Heart rate variability (HRV) methods, in which beat-to-beat interval lengths are extracted and analysed, have been extensively studied. However, this approach discards the majority of the raw data. Our aim is to detect changes in the shape of the waveform in long streams of blood pressure data. Our approach involves extracting key features from large complex data sets by generating a reconstructed attractor in a three-dimensional phase space using delay coordinates from a window of the entire raw waveform data. The naturally occurring baseline variation is removed by projecting the attractor onto a plane from which new quantitative measures are obtained. The time window is moved through the data to give a collection of signals which relate to various aspects of the waveform shape. This approach enables visualisation and quantification of changes in the waveform shape and has been applied to blood pressure data collected from conscious unrestrained mice and to human blood pressure data. The interpretation of the attractor measures is aided by the analysis of simple artificial waveforms. We have developed and analysed a new method for analysing blood pressure data that uses all of the waveform data and hence can detect changes in the waveform shape that HRV methods cannot, which is confirmed with an example, and hence our method goes 'beyond HRV'.

SERS properties of different sized and shaped gold nanoparticles biosynthesized under different environmental conditions by Neurospora crassa extract.

PubMed

Quester, Katrin; Avalos-Borja, Miguel; Vilchis-Nestor, Alfredo Rafael; Camacho-López, Marco Antonio; Castro-Longoria, Ernestina

2013-01-01

Surface-enhanced Raman scattering (SERS) is a surface-sensitive technique that enhances Raman scattering by molecules adsorbed on rough metal surfaces. It is known that metal nanoparticles, especially gold and silver nanoparticles, exhibit great SERS properties, which make them very attractive for the development of biosensors and biocatalysts. On the other hand, the development of ecofriendly methods for the synthesis of metallic nanostructures has become the focus of research in several countries, and many microorganisms and plants have already been used to biosynthesize metallic nanostructures. However, the majority of these are pathogenic to plants or humans. Here, we report gold nanoparticles with good SERS properties, biosynthesized by Neurospora crassa extract under different environmental conditions, increasing Raman signals up to 40 times using methylene blue as a target molecule. Incubation of tetrachloroauric acid solution with the fungal extract at 60°C and a pH value of a) 3, b) 5.5, and c) 10 resulted in the formation of gold nanoparticles of a) different shapes like triangles, hexagons, pentagons etc. in a broad size range of about 10-200 nm, b) mostly quasi-spheres with some different shapes in a main size range of 6-23 nm, and c) only quasi-spheres of 3-12 nm. Analyses included TEM, HRTEM, and EDS in order to corroborate the shape and the elemental character of the gold nanoparticles, respectively. The results presented here show that these 'green' synthesized gold nanoparticles might have potential applicability in the field of biological sensing.

Beyond HRV: attractor reconstruction using the entire cardiovascular waveform data for novel feature extraction

PubMed Central

Aston, Philip J; Christie, Mark I; Huang, Ying H; Nandi, Manasi

2018-01-01

Abstract Advances in monitoring technology allow blood pressure waveforms to be collected at sampling frequencies of 250–1000 Hz for long time periods. However, much of the raw data are under-analysed. Heart rate variability (HRV) methods, in which beat-to-beat interval lengths are extracted and analysed, have been extensively studied. However, this approach discards the majority of the raw data. Objective: Our aim is to detect changes in the shape of the waveform in long streams of blood pressure data. Approach: Our approach involves extracting key features from large complex data sets by generating a reconstructed attractor in a three-dimensional phase space using delay coordinates from a window of the entire raw waveform data. The naturally occurring baseline variation is removed by projecting the attractor onto a plane from which new quantitative measures are obtained. The time window is moved through the data to give a collection of signals which relate to various aspects of the waveform shape. Main results: This approach enables visualisation and quantification of changes in the waveform shape and has been applied to blood pressure data collected from conscious unrestrained mice and to human blood pressure data. The interpretation of the attractor measures is aided by the analysis of simple artificial waveforms. Significance: We have developed and analysed a new method for analysing blood pressure data that uses all of the waveform data and hence can detect changes in the waveform shape that HRV methods cannot, which is confirmed with an example, and hence our method goes ‘beyond HRV’. PMID:29350622

SERS Properties of Different Sized and Shaped Gold Nanoparticles Biosynthesized under Different Environmental Conditions by Neurospora crassa Extract

PubMed Central

Quester, Katrin; Avalos-Borja, Miguel; Vilchis-Nestor, Alfredo Rafael; Camacho-López, Marco Antonio; Castro-Longoria, Ernestina

2013-01-01

Surface-enhanced Raman scattering (SERS) is a surface-sensitive technique that enhances Raman scattering by molecules adsorbed on rough metal surfaces. It is known that metal nanoparticles, especially gold and silver nanoparticles, exhibit great SERS properties, which make them very attractive for the development of biosensors and biocatalysts. On the other hand, the development of ecofriendly methods for the synthesis of metallic nanostructures has become the focus of research in several countries, and many microorganisms and plants have already been used to biosynthesize metallic nanostructures. However, the majority of these are pathogenic to plants or humans. Here, we report gold nanoparticles with good SERS properties, biosynthesized by Neurospora crassa extract under different environmental conditions, increasing Raman signals up to 40 times using methylene blue as a target molecule. Incubation of tetrachloroauric acid solution with the fungal extract at 60°C and a pH value of a) 3, b) 5.5, and c) 10 resulted in the formation of gold nanoparticles of a) different shapes like triangles, hexagons, pentagons etc. in a broad size range of about 10-200 nm, b) mostly quasi-spheres with some different shapes in a main size range of 6-23 nm, and c) only quasi-spheres of 3-12 nm. Analyses included TEM, HRTEM, and EDS in order to corroborate the shape and the elemental character of the gold nanoparticles, respectively. The results presented here show that these ‘green’ synthesized gold nanoparticles might have potential applicability in the field of biological sensing. PMID:24130891

Our experience with a new instrument for laparoscopic gallbladder extraction, the "Bergetrokar".

PubMed

Höferlin, A; Höhle, K D

1993-01-01

Laparoscopic cholecystectomy has become a standardized technique within the last years. However, the extraction of the stone-filled gallbladder often becomes a time-consuming and difficult part of the operation. We have developed a new instrument for quick and safe extraction of the stone-filled gallbladder. The instrument, called "Bergetrokar", is a trocar cannula with a trumpet valve and cone-shaped tip which can be spread. The application of this device is simple. After using the "Bergetrokar" in about 180 cases we have not observed any perforation of the gallbladder or loss of stones. Extraction times were reduced.

Information carriers and (reading them through) information theory in quantum chemistry.

PubMed

Geerlings, Paul; Borgoo, Alex

2011-01-21

This Perspective discusses the reduction of the electronic wave function via the second-order reduced density matrix to the electron density ρ(r), which is the key ingredient in density functional theory (DFT) as a basic carrier of information. Simplifying further, the 1-normalized density function turns out to contain essentially the same information as ρ(r) and is even of preferred use as an information carrier when discussing the periodic properties along Mendeleev's table where essentially the valence electrons are at stake. The Kullback-Leibler information deficiency turns out to be the most interesting choice to obtain information on the differences in ρ(r) or σ(r) between two systems. To put it otherwise: when looking for the construction of a functional F(AB) = F[ζ(A)(r),ζ(B)(r)] for extracting differences in information from an information carrier ζ(r) (i.e. ρ(r), σ(r)) for two systems A and B the Kullback-Leibler information measure ΔS is a particularly adequate choice. Examples are given, varying from atoms, to molecules and molecular interactions. Quantum similarity of atoms indicates that the shape function based KL information deficiency is the most appropriate tool to retrieve periodicity in the Periodic Table. The dissimilarity of enantiomers for which different information measures are presented at global and local (i.e. molecular and atomic) level leads to an extension of Mezey's holographic density theorem and shows numerical evidence that in a chiral molecule the whole molecule is pervaded by chirality. Finally Kullback-Leibler information profiles are discussed for intra- and intermolecular proton transfer reactions and a simple S(N)2 reaction indicating that the theoretical information profile can be used as a companion to the energy based Hammond postulate to discuss the early or late transition state character of a reaction. All in all this Perspective's answer is positive to the question of whether an even simpler carrier of information than the electron density function ρ(r) can be envisaged: the shape function, integrating to 1 by construction fulfils this role. On the other hand obtaining the information (or information difference) contained in one (or two) systems from ρ(r) or σ(r) can be most efficiently done by using information theory, the Kulback-Leibler information deficiency being at the moment (one of) the most advisable functionals.

A flower image retrieval method based on ROI feature.

PubMed

Hong, An-Xiang; Chen, Gang; Li, Jun-Li; Chi, Zhe-Ru; Zhang, Dan

2004-07-01

Flower image retrieval is a very important step for computer-aided plant species recognition. In this paper, we propose an efficient segmentation method based on color clustering and domain knowledge to extract flower regions from flower images. For flower retrieval, we use the color histogram of a flower region to characterize the color features of flower and two shape-based features sets, Centroid-Contour Distance (CCD) and Angle Code Histogram (ACH), to characterize the shape features of a flower contour. Experimental results showed that our flower region extraction method based on color clustering and domain knowledge can produce accurate flower regions. Flower retrieval results on a database of 885 flower images collected from 14 plant species showed that our Region-of-Interest (ROI) based retrieval approach using both color and shape features can perform better than a method based on the global color histogram proposed by Swain and Ballard (1991) and a method based on domain knowledge-driven segmentation and color names proposed by Das et al.(1999).

Mid-Infrared Spectroscopy of Carbon Stars in the Small Magellanic Cloud

DTIC Science & Technology

2006-07-10

nod. Before extracting spectra from fit a variety of spectral feature shapes using MgS considerably the images, we used the imclean software package...mined from neighboring pixels. In addition to the dust features , the IRS wavelength range also To extract spectra from the cleaned and differenced...Example of the extraction of the molecular bands and the SiC dust 24 jIm, and they avoid any potential problems at the joint be- feature from the spectrum

Shape design sensitivity analysis using domain information

NASA Technical Reports Server (NTRS)

Seong, Hwal-Gyeong; Choi, Kyung K.

1985-01-01

A numerical method for obtaining accurate shape design sensitivity information for built-up structures is developed and demonstrated through analysis of examples. The basic character of the finite element method, which gives more accurate domain information than boundary information, is utilized for shape design sensitivity improvement. A domain approach for shape design sensitivity analysis of built-up structures is derived using the material derivative idea of structural mechanics and the adjoint variable method of design sensitivity analysis. Velocity elements and B-spline curves are introduced to alleviate difficulties in generating domain velocity fields. The regularity requirements of the design velocity field are studied.

How we categorize objects is related to how we remember them: The shape bias as a memory bias

PubMed Central

Vlach, Haley A.

2016-01-01

The “shape bias” describes the phenomenon that, after a certain point in development, children and adults generalize object categories based upon shape to a greater degree than other perceptual features. The focus of research on the shape bias has been to examine the types of information that learners attend to in one moment in time. The current work takes a different approach by examining whether learners' categorical biases are related to their retention of information across time. In three experiments, children's (N = 72) and adults' (N = 240) memory performance for features of objects was examined in relation to their categorical biases. The results of these experiments demonstrated that the number of shape matches chosen during the shape bias task significantly predicted shape memory. Moreover, children and adults with a shape bias were more likely to remember the shape of objects than they were the color and size of objects. Taken together, this work suggests the development of a shape bias may engender better memory for shape information. PMID:27454236

How we categorize objects is related to how we remember them: The shape bias as a memory bias.

PubMed

Vlach, Haley A

2016-12-01

The "shape bias" describes the phenomenon that, after a certain point in development, children and adults generalize object categories based on shape to a greater degree than other perceptual features. The focus of research on the shape bias has been to examine the types of information that learners attend to in one moment in time. The current work takes a different approach by examining whether learners' categorical biases are related to their retention of information across time. In three experiments, children's (N=72) and adults' (N=240) memory performance for features of objects was examined in relation to their categorical biases. The results of these experiments demonstrated that the number of shape matches chosen during the shape bias task significantly predicted shape memory. Moreover, children and adults with a shape bias were more likely to remember the shape of objects than the color and size of objects. Taken together, this work suggests that the development of a shape bias may engender better memory for shape information. Copyright © 2016 Elsevier Inc. All rights reserved.

True lemurs…true species - species delimitation using multiple data sources in the brown lemur complex

PubMed Central

2013-01-01

Background Species are the fundamental units in evolutionary biology. However, defining them as evolutionary independent lineages requires integration of several independent sources of information in order to develop robust hypotheses for taxonomic classification. Here, we exemplarily propose an integrative framework for species delimitation in the “brown lemur complex” (BLC) of Madagascar, which consists of seven allopatric populations of the genus Eulemur (Primates: Lemuridae), which were sampled extensively across northern, eastern and western Madagascar to collect fecal samples for DNA extraction as well as recordings of vocalizations. Our data base was extended by including museum specimens with reliable identification and locality information for skull shape and pelage color analysis. Results Between-group analyses of principal components revealed significant heterogeneity in skull shape, pelage color variation and loud calls across all seven populations. Furthermore, post-hoc statistical tests between pairs of populations revealed considerable discordance among different data sets for different dyads. Despite a high degree of incomplete lineage sorting among nuclear loci, significant exclusive ancestry was found for all populations, except for E. cinereiceps, based on one mitochondrial and three nuclear genetic loci. Conclusions Using several independent lines of evidence, our results confirm the species status of the members of the BLC under the general lineage concept of species. More generally, the present analyses demonstrate the importance and value of integrating different kinds of data in delimiting recently evolved radiations. PMID:24159931

Dynamic Substrate for the Physical Encoding of Sensory Information in Bat Biosonar

NASA Astrophysics Data System (ADS)

Müller, Rolf; Gupta, Anupam K.; Zhu, Hongxiao; Pannala, Mittu; Gillani, Uzair S.; Fu, Yanqing; Caspers, Philip; Buck, John R.

2017-04-01

Horseshoe bats have dynamic biosonar systems with interfaces for ultrasonic emission (reception) that change shape while diffracting the outgoing (incoming) sound waves. An information-theoretic analysis based on numerical and physical prototypes shows that these shape changes add sensory information (mutual information between distant shape conformations <20 %), increase the number of resolvable directions of sound incidence, and improve the accuracy of direction finding. These results demonstrate that horseshoe bats have a highly effective substrate for dynamic encoding of sensory information.

Dynamic Substrate for the Physical Encoding of Sensory Information in Bat Biosonar.

PubMed

Müller, Rolf; Gupta, Anupam K; Zhu, Hongxiao; Pannala, Mittu; Gillani, Uzair S; Fu, Yanqing; Caspers, Philip; Buck, John R

2017-04-14

Horseshoe bats have dynamic biosonar systems with interfaces for ultrasonic emission (reception) that change shape while diffracting the outgoing (incoming) sound waves. An information-theoretic analysis based on numerical and physical prototypes shows that these shape changes add sensory information (mutual information between distant shape conformations <20%), increase the number of resolvable directions of sound incidence, and improve the accuracy of direction finding. These results demonstrate that horseshoe bats have a highly effective substrate for dynamic encoding of sensory information.

Testing the Ge Detectors for the MAJORANA DEMONSTRATOR

NASA Astrophysics Data System (ADS)

Xu, W.; Abgrall, N.; Aguayo, E.; Avignone, F. T.; Barabash, A. S.; Bertrand, F. E.; Boswell, M.; Brudanin, V.; Busch, M.; Byram, D.; Caldwell, A. S.; Chan, Y.-D.; Christofferson, C. D.; Combs, D. C.; Cuesta, C.; Detwiler, J. A.; Doe, P. J.; Efremenko, Yu.; Egorov, V.; Ejiri, H.; Elliott, S. R.; Fast, J. E.; Finnerty, P.; Fraenkle, F. M.; Galindo-Uribarri, A.; Giovanetti, G. K.; Goett, J.; Green, M. P.; Gruszko, J.; Guiseppe, V. E.; Gusev, K.; Hallin, A. L.; Hazama, R.; Hegai, A.; Henning, R.; Hoppe, E. W.; Howard, S.; Howe, M. A.; Keeter, K. J.; Kidd, M. F.; Kochetov, O.; Konovalov, S. I.; Kouzes, R. T.; LaFerriere, B. D.; Leon, J.; Leviner, L. E.; Loach, J. C.; MacMullin, J.; MacMullin, S.; Martin, R. D.; Meijer, S.; Mertens, S.; Nomachi, M.; Orrell, J. L.; O'Shaughnessy, C.; Overman, N. R.; Phillips, D. G.; Poon, A. W. P.; Pushkin, K.; Radford, D. C.; Rager, J.; Rielage, K.; Robertson, R. G. H.; Romero-Romero, E.; Ronquest, M. C.; Schubert, A. G.; Shanks, B.; Shima, T.; Shirchenko, M.; Snavely, K. J.; Snyder, N.; Suriano, A. M.; Thompson, J.; Timkin, V.; Tornow, W.; Trimble, J. E.; Varner, R. L.; Vasilyev, S.; Vetter, K.; Vorren, K.; White, B. R.; Wilkerson, J. F.; Wiseman, C.; Yakushev, E.; Young, A. R.; Yu, C.-H.; Yumatov, V.

High purity germanium (HPGe) crystals will be used for the MAJORANA DEMONSTRATOR, where they serve as both the source and the detector for neutrinoless double beta decay. It is crucial for the experiment to understand the performance of the HPGe crystals. A variety of crystal properties are being investigated, including basic properties such as energy resolution, efficiency, uniformity, capacitance, leakage current and crystal axis orientation, as well as more sophisticated properties, e.g. pulse shapes and dead layer and transition layer distributions. In this talk, we will present our measurements that characterize the HPGe crystals. We will also discuss the our simulation package for the detector characterization setup, and show that additional information can be extracted from data-simulation comparisons.

Bilevel thresholding of sliced image of sludge floc.

PubMed

Chu, C P; Lee, D J

2004-02-15

This work examined the feasibility of employing various thresholding algorithms to determining the optimal bilevel thresholding value for estimating the geometric parameters of sludge flocs from the microtome sliced images and from the confocal laser scanning microscope images. Morphological information extracted from images depends on the bilevel thresholding value. According to the evaluation on the luminescence-inverted images and fractal curves (quadric Koch curve and Sierpinski carpet), Otsu's method yields more stable performance than other histogram-based algorithms and is chosen to obtain the porosity. The maximum convex perimeter method, however, can probe the shapes and spatial distribution of the pores among the biomass granules in real sludge flocs. A combined algorithm is recommended for probing the sludge floc structure.

Automatic identification of bullet signatures based on consecutive matching striae (CMS) criteria.

PubMed

Chu, Wei; Thompson, Robert M; Song, John; Vorburger, Theodore V

2013-09-10

The consecutive matching striae (CMS) numeric criteria for firearm and toolmark identifications have been widely accepted by forensic examiners, although there have been questions concerning its observer subjectivity and limited statistical support. In this paper, based on signal processing and extraction, a model for the automatic and objective counting of CMS is proposed. The position and shape information of the striae on the bullet land is represented by a feature profile, which is used for determining the CMS number automatically. Rapid counting of CMS number provides a basis for ballistics correlations with large databases and further statistical and probability analysis. Experimental results in this report using bullets fired from ten consecutively manufactured barrels support this developed model. Published by Elsevier Ireland Ltd.

Antidot shape dependence of switching mechanism in permalloy samples

NASA Astrophysics Data System (ADS)

Yetiş, Hakan; Denizli, Haluk

2017-01-01

We study antidot shape dependence of the switching magnetization for various permalloy samples with square and triangular arrays of nanometer scale antidots. The remnant magnetization, squareness ratio, and coercive fields of the samples are extracted from the hysteresis loops which are obtained by solving the Landau-Lifshitz-Gilbert (LLG) equation numerically. We find several different magnetic spin configurations which reveal the existence of superdomain wall structures. Our results are discussed in terms of the local shape anisotropy, array geometry, and symmetry properties in order to explain the formation of inhomogeneous domain structures.

Morphological feature extraction for the classification of digital images of cancerous tissues.

PubMed

Thiran, J P; Macq, B

1996-10-01

This paper presents a new method for automatic recognition of cancerous tissues from an image of a microscopic section. Based on the shape and the size analysis of the observed cells, this method provides the physician with nonsubjective numerical values for four criteria of malignancy. This automatic approach is based on mathematical morphology, and more specifically on the use of Geodesy. This technique is used first to remove the background noise from the image and then to operate a segmentation of the nuclei of the cells and an analysis of their shape, their size, and their texture. From the values of the extracted criteria, an automatic classification of the image (cancerous or not) is finally operated.

Discriminative Features Mining for Offline Handwritten Signature Verification

NASA Astrophysics Data System (ADS)

Neamah, Karrar; Mohamad, Dzulkifli; Saba, Tanzila; Rehman, Amjad

2014-03-01

Signature verification is an active research area in the field of pattern recognition. It is employed to identify the particular person with the help of his/her signature's characteristics such as pen pressure, loops shape, speed of writing and up down motion of pen, writing speed, pen pressure, shape of loops, etc. in order to identify that person. However, in the entire process, features extraction and selection stage is of prime importance. Since several signatures have similar strokes, characteristics and sizes. Accordingly, this paper presents combination of orientation of the skeleton and gravity centre point to extract accurate pattern features of signature data in offline signature verification system. Promising results have proved the success of the integration of the two methods.

Information extraction from multi-institutional radiology reports.

PubMed

Hassanpour, Saeed; Langlotz, Curtis P

2016-01-01

The radiology report is the most important source of clinical imaging information. It documents critical information about the patient's health and the radiologist's interpretation of medical findings. It also communicates information to the referring physicians and records that information for future clinical and research use. Although efforts to structure some radiology report information through predefined templates are beginning to bear fruit, a large portion of radiology report information is entered in free text. The free text format is a major obstacle for rapid extraction and subsequent use of information by clinicians, researchers, and healthcare information systems. This difficulty is due to the ambiguity and subtlety of natural language, complexity of described images, and variations among different radiologists and healthcare organizations. As a result, radiology reports are used only once by the clinician who ordered the study and rarely are used again for research and data mining. In this work, machine learning techniques and a large multi-institutional radiology report repository are used to extract the semantics of the radiology report and overcome the barriers to the re-use of radiology report information in clinical research and other healthcare applications. We describe a machine learning system to annotate radiology reports and extract report contents according to an information model. This information model covers the majority of clinically significant contents in radiology reports and is applicable to a wide variety of radiology study types. Our automated approach uses discriminative sequence classifiers for named-entity recognition to extract and organize clinically significant terms and phrases consistent with the information model. We evaluated our information extraction system on 150 radiology reports from three major healthcare organizations and compared its results to a commonly used non-machine learning information extraction method. We also evaluated the generalizability of our approach across different organizations by training and testing our system on data from different organizations. Our results show the efficacy of our machine learning approach in extracting the information model's elements (10-fold cross-validation average performance: precision: 87%, recall: 84%, F1 score: 85%) and its superiority and generalizability compared to the common non-machine learning approach (p-value<0.05). Our machine learning information extraction approach provides an effective automatic method to annotate and extract clinically significant information from a large collection of free text radiology reports. This information extraction system can help clinicians better understand the radiology reports and prioritize their review process. In addition, the extracted information can be used by researchers to link radiology reports to information from other data sources such as electronic health records and the patient's genome. Extracted information also can facilitate disease surveillance, real-time clinical decision support for the radiologist, and content-based image retrieval. Copyright © 2015 Elsevier B.V. All rights reserved.

A giant dumbbell shaped vesico-prostatic urethral calculus: a case report and review of literature.

PubMed

Prabhuswamy, Vinod Kumar; Tiwari, Rahul; Krishnamoorthy, Ramakrishnan

2013-01-01

Calculi in the urethra are an uncommon entity. Giant calculi in prostatic urethra are extremely rare. The decision about treatment strategy of calculi depends upon the size, shape, and position of the calculus and the status of the urethra. If the stone is large and immovable, it may be extracted via the perineal or the suprapubic approach. In most of the previous reported cases, giant calculi were extracted via the transvesical approach and external urethrotomy. A 38-year-old male patient presented with complaints of lower urinary tract symptoms. Further investigations showed a giant urethral calculus secondary to stricture of bulbo-membranous part of the urethra. Surgical removal of calculus was done via transvesical approach. Two calculi were found and extracted. One was a huge dumbbell calculus and the other was a smaller round calculus. This case was reported because of the rare size and the dumbbell nature of the stone. Giant urethral calculi are better managed by open surgery.

A Giant Dumbbell Shaped Vesico-Prostatic Urethral Calculus: A Case Report and Review of Literature

PubMed Central

Prabhuswamy, Vinod Kumar; Tiwari, Rahul; Krishnamoorthy, Ramakrishnan

2013-01-01

Calculi in the urethra are an uncommon entity. Giant calculi in prostatic urethra are extremely rare. The decision about treatment strategy of calculi depends upon the size, shape, and position of the calculus and the status of the urethra. If the stone is large and immovable, it may be extracted via the perineal or the suprapubic approach. In most of the previous reported cases, giant calculi were extracted via the transvesical approach and external urethrotomy. A 38-year-old male patient presented with complaints of lower urinary tract symptoms. Further investigations showed a giant urethral calculus secondary to stricture of bulbo-membranous part of the urethra. Surgical removal of calculus was done via transvesical approach. Two calculi were found and extracted. One was a huge dumbbell calculus and the other was a smaller round calculus. This case was reported because of the rare size and the dumbbell nature of the stone. Giant urethral calculi are better managed by open surgery. PMID:23762742

Ion beams extraction and measurements of plasma parameters on a multi-frequencies microwaves large bore ECRIS with permanent magnets

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

Nozaki, Dai; Kiriyama, Ryutaro; Takenaka, Tomoya

2012-11-06

We have developed an all-permanent magnet large bore electron cyclotron resonance ion source (ECRIS) for broad ion beam processing. The cylindrically comb-shaped magnetic field configuration is adopted for efficient plasma production and good magnetic confinement. To compensate for disadvantages of fixed magnetic configuration, a traveling wave tube amplifier (TWTA) is used. In the comb-shaped ECRIS, it is difficult to achieve controlling ion beam profiles in the whole inside the chamber by using even single frequency-controllable TWTA (11-13GHz), because of large bore size with all-magnets. We have tried controlling profiles of plasma parameters and then those of extracted ion beams bymore » launching two largely different frequencies simultaneously, i.e., multi-frequencies microwaves. Here we report ion beam profiles and corresponding plasma parameters under various experimental conditions, dependence of ion beams against extraction voltages, and influence of different electrode positions on the electron density profile.« less

Biosynthesis of silver nanoparticles using aqueous leaf extract of Thevetia peruviana Juss and its antimicrobial activities

NASA Astrophysics Data System (ADS)

Oluwaniyi, Omolara O.; Adegoke, Haleemat I.; Adesuji, Elijah T.; Alabi, Aderemi B.; Bodede, Sunday O.; Labulo, Ayomide H.; Oseghale, Charles O.

2016-08-01

Biosynthesizing of silver nanoparticles using microorganisms or various plant parts have proven more environmental friendly, cost-effective, energy saving and reproducible when compared to chemical and physical methods. This investigation demonstrated the plant-mediated synthesis of silver nanoparticles using the aqueous leaf extract of Thevetia peruviana. UV-Visible spectrophotometer was used to measure the surface plasmon resonance of the nanoparticles at 460 nm. Fourier Transform Infrared showed that the glycosidic -OH and carbonyl functional group present in extract were responsible for the reduction and stabilization of the silver nanoparticles. X ray diffraction, Scanning Electron Microscopy, Transmission Electron Microscopy and Selected Area Electron Diffraction analyses were used to confirm the nature, morphology and shape of the nanoparticles. The silver nanoparticles are spherical in shape with average size of 18.1 nm. The synthesized silver nanoparticles showed activity against fungal pathogens and bacteria. The zone of inhibition observed in the antimicrobial study ranged between 10 and 20 mm.

Review of Extracting Information From the Social Web for Health Personalization

PubMed Central

Karlsen, Randi; Bonander, Jason

2011-01-01

In recent years the Web has come into its own as a social platform where health consumers are actively creating and consuming Web content. Moreover, as the Web matures, consumers are gaining access to personalized applications adapted to their health needs and interests. The creation of personalized Web applications relies on extracted information about the users and the content to personalize. The Social Web itself provides many sources of information that can be used to extract information for personalization apart from traditional Web forms and questionnaires. This paper provides a review of different approaches for extracting information from the Social Web for health personalization. We reviewed research literature across different fields addressing the disclosure of health information in the Social Web, techniques to extract that information, and examples of personalized health applications. In addition, the paper includes a discussion of technical and socioethical challenges related to the extraction of information for health personalization. PMID:21278049

Evaluation of Elevation, Slope and Stream Network Quality of SPOT Dems

NASA Astrophysics Data System (ADS)

El Hage, M.; Simonetto, E.; Faour, G.; Polidori, L.

2012-07-01

Digital elevation models are considered the most useful data for dealing with geomorphology. The quality of these models is an important issue for users. This quality concerns position and shape. Vertical accuracy is the most assessed in many studies and shape quality is often neglected. However, both of them have an impact on the quality of the final results for a particular application. For instance, the elevation accuracy is required for orthorectification and the shape quality for geomorphology and hydrology. In this study, we deal with photogrammetric DEMs and show the importance of the quality assessment of both elevation and shape. For this purpose, we produce several SPOT HRV DEMs with the same dataset but with different template size, that is one of the production parameters from optical images. Then, we evaluate both elevation and shape quality. The shape quality is assessed with in situ measurements and analysis of slopes as an elementary shape and stream networks as a complex shape. We use the fractal dimension and sinuosity to evaluate the stream network shape. The results show that the elevation accuracy as well as the slope accuracy are affected by the template size. Indeed, an improvement of 1 m in the elevation accuracy and of 5 degrees in the slope accuracy has been obtained while changing this parameter. The elevation RMSE ranges from 7.6 to 8.6 m, which is smaller than the pixel size (10 m). For slope, the RMSE depends on the sampling distance. With a distance of 10 m, the minimum slope RMSE is 11.4 degrees. The stream networks extracted from these DEMs present a higher fractal dimension than the reference river. Moreover, the fractal dimension of the extracted networks has a negligible change according to the template size. Finally, the sinuosity of the stream networks is slightly affected by the change of the template size.

Union operation image processing of data cubes separately processed by different objective filters and its application to void analysis in an all-solid-state lithium-ion battery.

PubMed

Yamamoto, Yuta; Iriyama, Yasutoshi; Muto, Shunsuke

2016-04-01

In this article, we propose a smart image-analysis method suitable for extracting target features with hierarchical dimension from original data. The method was applied to three-dimensional volume data of an all-solid lithium-ion battery obtained by the automated sequential sample milling and imaging process using a focused ion beam/scanning electron microscope to investigate the spatial configuration of voids inside the battery. To automatically fully extract the shape and location of the voids, three types of filters were consecutively applied: a median blur filter to extract relatively larger voids, a morphological opening operation filter for small dot-shaped voids and a morphological closing operation filter for small voids with concave contrasts. Three data cubes separately processed by the above-mentioned filters were integrated by a union operation to the final unified volume data, which confirmed the correct extraction of the voids over the entire dimension contained in the original data. © The Author 2015. Published by Oxford University Press on behalf of The Japanese Society of Microscopy. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

The minimal local-asperity hypothesis of early retinal lateral inhibition.

PubMed

Balboa, R M; Grzywacz, N M

2000-07-01

Recently we found that the theories related to information theory existent in the literature cannot explain the behavior of the extent of the lateral inhibition mediated by retinal horizontal cells as a function of background light intensity. These theories can explain the fall of the extent from intermediate to high intensities, but not its rise from dim to intermediate intensities. We propose an alternate hypothesis that accounts for the extent's bell-shape behavior. This hypothesis proposes that the lateral-inhibition adaptation in the early retina is part of a system to extract several image attributes, such as occlusion borders and contrast. To do so, this system would use prior probabilistic knowledge about the biological processing and relevant statistics in natural images. A key novel statistic used here is the probability of the presence of an occlusion border as a function of local contrast. Using this probabilistic knowledge, the retina would optimize the spatial profile of lateral inhibition to minimize attribute-extraction error. The two significant errors that this minimization process must reduce are due to the quantal noise in photoreceptors and the straddling of occlusion borders by lateral inhibition.

Small Angle X-Ray Scattering from Lipid-Bound Myelin Basic Protein in Solution

PubMed Central

Haas, H.; Oliveira, C. L. P.; Torriani, I. L.; Polverini, E.; Fasano, A.; Carlone, G.; Cavatorta, P.; Riccio, P.

2004-01-01

The structure of myelin basic protein (MBP), purified from the myelin sheath in both lipid-free (LF-MBP) and lipid-bound (LB-MBP) forms, was investigated in solution by small angle x-ray scattering. The water-soluble LF-MBP, extracted at pH < 3.0 from defatted brain, is the classical preparation of MBP, commonly regarded as an intrinsically unfolded protein. LB-MBP is a lipoprotein-detergent complex extracted from myelin with its native lipidic environment at pH > 7.0. Under all conditions, the scattering from the two protein forms was different, indicating different molecular shapes. For the LB-MBP, well-defined scattering curves were obtained, suggesting that the protein had a unique, compact (but not globular) structure. Furthermore, these data were compatible with earlier results from molecular modeling calculations on the MBP structure which have been refined by us. In contrast, the LF-MBP data were in accordance with the expected open-coil conformation. The results represent the first direct structural information from x-ray scattering measurements on MBP in its native lipidic environment in solution. PMID:14695288

Separation of Ellagitannin-Rich Phenolics from U.S. Pecans and Chinese Hickory Nuts Using Fused-Core HPLC Columns and Their Characterization.

PubMed

Gong, Yi; Pegg, Ronald B

2017-07-19

U.S. pecans and Chinese hickory nuts possess a wide array of phenolic constituents with potential health benefits including phenolic acids and proanthocyanidins. Only limited information is available, however, on their compositions. The present study optimized the separation performance and characterized the low-molecular-weight phenolic fractions of these nuts with C18 and pentafluorophenyl (PFP) fused-core LC columns by employing a kinetic approach. Although both types of reversed-phase columns demonstrated similar performance in general, the PFP column furnished greater plate numbers and superior peak shapes for the low-molecular-weight fractions as well as overall separations of ellagic acid derivatives. The high-molecular-weight fraction of pecans, analyzed by a 3-μm HILIC column, possessed more proanthocyanidins than the Chinese hickory nuts with dimers and trimers (31.4 and 18.34 mg/g crude extract, respectively) being present at the greatest levels. Chinese hickory nuts had lower proanthocyanidin content but possessed tetramers and pentamers at 4.46 and 4.01 mg/g crude extract, respectively.

Behavioural and physiological limits to vision in mammals

PubMed Central

Field, Greg D.

2017-01-01

Human vision is exquisitely sensitive—a dark-adapted observer is capable of reliably detecting the absorption of a few quanta of light. Such sensitivity requires that the sensory receptors of the retina, rod photoreceptors, generate a reliable signal when single photons are absorbed. In addition, the retina must be able to extract this information and relay it to higher visual centres under conditions where very few rods signal single-photon responses while the majority generate only noise. Critical to signal transmission are mechanistic optimizations within rods and their dedicated retinal circuits that enhance the discriminability of single-photon responses by mitigating photoreceptor and synaptic noise. We describe behavioural experiments over the past century that have led to the appreciation of high sensitivity near absolute visual threshold. We further consider mechanisms within rod photoreceptors and dedicated rod circuits that act to extract single-photon responses from cellular noise. We highlight how these studies have shaped our understanding of brain function and point out several unresolved questions in the processing of light near the visual threshold. This article is part of the themed issue ‘Vision in dim light’. PMID:28193817

Bottlenose dolphins perceive object features through echolocation.

PubMed

Harley, Heidi E; Putman, Erika A; Roitblat, Herbert L

2003-08-07

How organisms (including people) recognize distant objects is a fundamental question. The correspondence between object characteristics (distal stimuli), like visual shape, and sensory characteristics (proximal stimuli), like retinal projection, is ambiguous. The view that sensory systems are 'designed' to 'pick up' ecologically useful information is vague about how such mechanisms might work. In echolocating dolphins, which are studied as models for object recognition sonar systems, the correspondence between echo characteristics and object characteristics is less clear. Many cognitive scientists assume that object characteristics are extracted from proximal stimuli, but evidence for this remains ambiguous. For example, a dolphin may store 'sound templates' in its brain and identify whole objects by listening for a particular sound. Alternatively, a dolphin's brain may contain algorithms, derived through natural endowments or experience or both, which allow it to identify object characteristics based on sounds. The standard method used to address this question in many species is indirect and has led to equivocal results with dolphins. Here we outline an appropriate method and test it to show that dolphins extract object characteristics directly from echoes.

Integration of heterogeneous features for remote sensing scene classification

NASA Astrophysics Data System (ADS)

Wang, Xin; Xiong, Xingnan; Ning, Chen; Shi, Aiye; Lv, Guofang

2018-01-01

Scene classification is one of the most important issues in remote sensing (RS) image processing. We find that features from different channels (shape, spectral, texture, etc.), levels (low-level and middle-level), or perspectives (local and global) could provide various properties for RS images, and then propose a heterogeneous feature framework to extract and integrate heterogeneous features with different types for RS scene classification. The proposed method is composed of three modules (1) heterogeneous features extraction, where three heterogeneous feature types, called DS-SURF-LLC, mean-Std-LLC, and MS-CLBP, are calculated, (2) heterogeneous features fusion, where the multiple kernel learning (MKL) is utilized to integrate the heterogeneous features, and (3) an MKL support vector machine classifier for RS scene classification. The proposed method is extensively evaluated on three challenging benchmark datasets (a 6-class dataset, a 12-class dataset, and a 21-class dataset), and the experimental results show that the proposed method leads to good classification performance. It produces good informative features to describe the RS image scenes. Moreover, the integration of heterogeneous features outperforms some state-of-the-art features on RS scene classification tasks.

Hearing Shapes: Event-related Potentials Reveal the Time Course of Auditory-Visual Sensory Substitution.

PubMed

Graulty, Christian; Papaioannou, Orestis; Bauer, Phoebe; Pitts, Michael A; Canseco-Gonzalez, Enriqueta

2018-04-01

In auditory-visual sensory substitution, visual information (e.g., shape) can be extracted through strictly auditory input (e.g., soundscapes). Previous studies have shown that image-to-sound conversions that follow simple rules [such as the Meijer algorithm; Meijer, P. B. L. An experimental system for auditory image representation. Transactions on Biomedical Engineering, 39, 111-121, 1992] are highly intuitive and rapidly learned by both blind and sighted individuals. A number of recent fMRI studies have begun to explore the neuroplastic changes that result from sensory substitution training. However, the time course of cross-sensory information transfer in sensory substitution is largely unexplored and may offer insights into the underlying neural mechanisms. In this study, we recorded ERPs to soundscapes before and after sighted participants were trained with the Meijer algorithm. We compared these posttraining versus pretraining ERP differences with those of a control group who received the same set of 80 auditory/visual stimuli but with arbitrary pairings during training. Our behavioral results confirmed the rapid acquisition of cross-sensory mappings, and the group trained with the Meijer algorithm was able to generalize their learning to novel soundscapes at impressive levels of accuracy. The ERP results revealed an early cross-sensory learning effect (150-210 msec) that was significantly enhanced in the algorithm-trained group compared with the control group as well as a later difference (420-480 msec) that was unique to the algorithm-trained group. These ERP modulations are consistent with previous fMRI results and provide additional insight into the time course of cross-sensory information transfer in sensory substitution.

Research of information classification and strategy intelligence extract algorithm based on military strategy hall

NASA Astrophysics Data System (ADS)

Chen, Lei; Li, Dehua; Yang, Jie

2007-12-01

Constructing virtual international strategy environment needs many kinds of information, such as economy, politic, military, diploma, culture, science, etc. So it is very important to build an information auto-extract, classification, recombination and analysis management system with high efficiency as the foundation and component of military strategy hall. This paper firstly use improved Boost algorithm to classify obtained initial information, then use a strategy intelligence extract algorithm to extract strategy intelligence from initial information to help strategist to analysis information.

Ten-dimensional anthropomorphic arm control in a human brain-machine interface: difficulties, solutions, and limitations

NASA Astrophysics Data System (ADS)

Wodlinger, B.; Downey, J. E.; Tyler-Kabara, E. C.; Schwartz, A. B.; Boninger, M. L.; Collinger, J. L.

2015-02-01

Objective. In a previous study we demonstrated continuous translation, orientation and one-dimensional grasping control of a prosthetic limb (seven degrees of freedom) by a human subject with tetraplegia using a brain-machine interface (BMI). The current study, in the same subject, immediately followed the previous work and expanded the scope of the control signal by also extracting hand-shape commands from the two 96-channel intracortical electrode arrays implanted in the subject’s left motor cortex. Approach. Four new control signals, dictating prosthetic hand shape, replaced the one-dimensional grasping in the previous study, allowing the subject to control the prosthetic limb with ten degrees of freedom (three-dimensional (3D) translation, 3D orientation, four-dimensional hand shaping) simultaneously. Main results. Robust neural tuning to hand shaping was found, leading to ten-dimensional (10D) performance well above chance levels in all tests. Neural unit preferred directions were broadly distributed through the 10D space, with the majority of units significantly tuned to all ten dimensions, instead of being restricted to isolated domains (e.g. translation, orientation or hand shape). The addition of hand shaping emphasized object-interaction behavior. A fundamental component of BMIs is the calibration used to associate neural activity to intended movement. We found that the presence of an object during calibration enhanced successful shaping of the prosthetic hand as it closed around the object during grasping. Significance. Our results show that individual motor cortical neurons encode many parameters of movement, that object interaction is an important factor when extracting these signals, and that high-dimensional operation of prosthetic devices can be achieved with simple decoding algorithms. ClinicalTrials.gov Identifier: NCT01364480.

Focal liver lesions segmentation and classification in nonenhanced T2-weighted MRI.

PubMed

Gatos, Ilias; Tsantis, Stavros; Karamesini, Maria; Spiliopoulos, Stavros; Karnabatidis, Dimitris; Hazle, John D; Kagadis, George C

2017-07-01

To automatically segment and classify focal liver lesions (FLLs) on nonenhanced T2-weighted magnetic resonance imaging (MRI) scans using a computer-aided diagnosis (CAD) algorithm. 71 FLLs (30 benign lesions, 19 hepatocellular carcinomas, and 22 metastases) on T2-weighted MRI scans were delineated by the proposed CAD scheme. The FLL segmentation procedure involved wavelet multiscale analysis to extract accurate edge information and mean intensity values for consecutive edges computed using horizontal and vertical analysis that were fed into the subsequent fuzzy C-means algorithm for final FLL border extraction. Texture information for each extracted lesion was derived using 42 first- and second-order textural features from grayscale value histogram, co-occurrence, and run-length matrices. Twelve morphological features were also extracted to capture any shape differentiation between classes. Feature selection was performed with stepwise multilinear regression analysis that led to a reduced feature subset. A multiclass Probabilistic Neural Network (PNN) classifier was then designed and used for lesion classification. PNN model evaluation was performed using the leave-one-out (LOO) method and receiver operating characteristic (ROC) curve analysis. The mean overlap between the automatically segmented FLLs and the manual segmentations performed by radiologists was 0.91 ± 0.12. The highest classification accuracies in the PNN model for the benign, hepatocellular carcinoma, and metastatic FLLs were 94.1%, 91.4%, and 94.1%, respectively, with sensitivity/specificity values of 90%/97.3%, 89.5%/92.2%, and 90.9%/95.6% respectively. The overall classification accuracy for the proposed system was 90.1%. Our diagnostic system using sophisticated FLL segmentation and classification algorithms is a powerful tool for routine clinical MRI-based liver evaluation and can be a supplement to contrast-enhanced MRI to prevent unnecessary invasive procedures. © 2017 American Association of Physicists in Medicine.

Process monitoring using automatic physical measurement based on electrical and physical variability analysis

NASA Astrophysics Data System (ADS)

Shauly, Eitan N.; Levi, Shimon; Schwarzband, Ishai; Adan, Ofer; Latinsky, Sergey

2015-04-01

A fully automated silicon-based methodology for systematic analysis of electrical features is shown. The system was developed for process monitoring and electrical variability reduction. A mapping step was created by dedicated structures such as static-random-access-memory (SRAM) array or standard cell library, or by using a simple design rule checking run-set. The resulting database was then used as an input for choosing locations for critical dimension scanning electron microscope images and for specific layout parameter extraction then was input to SPICE compact modeling simulation. Based on the experimental data, we identified two items that must be checked and monitored using the method described here: transistor's sensitivity to the distance between the poly end cap and edge of active area (AA) due to AA rounding, and SRAM leakage due to a too close N-well to P-well. Based on this example, for process monitoring and variability analyses, we extensively used this method to analyze transistor gates having different shapes. In addition, analysis for a large area of high density standard cell library was done. Another set of monitoring focused on a high density SRAM array is also presented. These examples provided information on the poly and AA layers, using transistor parameters such as leakage current and drive current. We successfully define "robust" and "less-robust" transistor configurations included in the library and identified unsymmetrical transistors in the SRAM bit-cells. These data were compared to data extracted from the same devices at the end of the line. Another set of analyses was done to samples after Cu M1 etch. Process monitoring information on M1 enclosed contact was extracted based on contact resistance as a feedback. Guidelines for the optimal M1 space for different layout configurations were also extracted. All these data showed the successful in-field implementation of our methodology as a useful process monitoring method.

High-Resolution Remote Sensing Image Building Extraction Based on Markov Model

NASA Astrophysics Data System (ADS)

Zhao, W.; Yan, L.; Chang, Y.; Gong, L.

2018-04-01

With the increase of resolution, remote sensing images have the characteristics of increased information load, increased noise, more complex feature geometry and texture information, which makes the extraction of building information more difficult. To solve this problem, this paper designs a high resolution remote sensing image building extraction method based on Markov model. This method introduces Contourlet domain map clustering and Markov model, captures and enhances the contour and texture information of high-resolution remote sensing image features in multiple directions, and further designs the spectral feature index that can characterize "pseudo-buildings" in the building area. Through the multi-scale segmentation and extraction of image features, the fine extraction from the building area to the building is realized. Experiments show that this method can restrain the noise of high-resolution remote sensing images, reduce the interference of non-target ground texture information, and remove the shadow, vegetation and other pseudo-building information, compared with the traditional pixel-level image information extraction, better performance in building extraction precision, accuracy and completeness.

Manifold Learning for 3D Shape Description and Classification

DTIC Science & Technology

2014-06-09

sportswear, personal protection clothing and equipment, office and health care device, etc. Therefore it is desirable to develop an effective shape...Modeling Figure 2: Toy example for submanifold decomposition. (a) The original data on the top are fused by two uncorrelated manifolds, blue and red... developed which is effective to extract two linear submanifolds. We demonstrated that comparing with existing manifold learning methods that only

Characterization of a penny-shaped reservoir in a hot dry rock

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

Sekine, H.; Mura, T.

1980-07-10

The mechanical stability of a penny-shaped revervoir is characterized by fracture mechanics including thermoelastic effects in connection with research into the extraction of geothermal energy from hot dry rocks. The condition for stability of a reservoir, which is not changing radius by propagating or closing, requires 0m/sub 0/>m/sub asterisk/; and case 3; m/sub 0/=m/sub asterisk/.

Revisiting Frazier's subdeltas: enhancing datasets with dimensionality, better to understand geologic systems

USGS Publications Warehouse

Flocks, James

2006-01-01

Scientific knowledge from the past century is commonly represented by two-dimensional figures and graphs, as presented in manuscripts and maps. Using today's computer technology, this information can be extracted and projected into three- and four-dimensional perspectives. Computer models can be applied to datasets to provide additional insight into complex spatial and temporal systems. This process can be demonstrated by applying digitizing and modeling techniques to valuable information within widely used publications. The seminal paper by D. Frazier, published in 1967, identified 16 separate delta lobes formed by the Mississippi River during the past 6,000 yrs. The paper includes stratigraphic descriptions through geologic cross-sections, and provides distribution and chronologies of the delta lobes. The data from Frazier's publication are extensively referenced in the literature. Additional information can be extracted from the data through computer modeling. Digitizing and geo-rectifying Frazier's geologic cross-sections produce a three-dimensional perspective of the delta lobes. Adding the chronological data included in the report provides the fourth-dimension of the delta cycles, which can be visualized through computer-generated animation. Supplemental information can be added to the model, such as post-abandonment subsidence of the delta-lobe surface. Analyzing the regional, net surface-elevation balance between delta progradations and land subsidence is computationally intensive. By visualizing this process during the past 4,500 yrs through multi-dimensional animation, the importance of sediment compaction in influencing both the shape and direction of subsequent delta progradations becomes apparent. Visualization enhances a classic dataset, and can be further refined using additional data, as well as provide a guide for identifying future areas of study.

Extracting information from S-curves of language change

PubMed Central

Ghanbarnejad, Fakhteh; Gerlach, Martin; Miotto, José M.; Altmann, Eduardo G.

2014-01-01

It is well accepted that adoption of innovations are described by S-curves (slow start, accelerating period and slow end). In this paper, we analyse how much information on the dynamics of innovation spreading can be obtained from a quantitative description of S-curves. We focus on the adoption of linguistic innovations for which detailed databases of written texts from the last 200 years allow for an unprecedented statistical precision. Combining data analysis with simulations of simple models (e.g. the Bass dynamics on complex networks), we identify signatures of endogenous and exogenous factors in the S-curves of adoption. We propose a measure to quantify the strength of these factors and three different methods to estimate it from S-curves. We obtain cases in which the exogenous factors are dominant (in the adoption of German orthographic reforms and of one irregular verb) and cases in which endogenous factors are dominant (in the adoption of conventions for romanization of Russian names and in the regularization of most studied verbs). These results show that the shape of S-curve is not universal and contains information on the adoption mechanism. PMID:25339692

Progress in building a cognitive vision system

NASA Astrophysics Data System (ADS)

Benjamin, D. Paul; Lyons, Damian; Yue, Hong

2016-05-01

We are building a cognitive vision system for mobile robots that works in a manner similar to the human vision system, using saccadic, vergence and pursuit movements to extract information from visual input. At each fixation, the system builds a 3D model of a small region, combining information about distance, shape, texture and motion to create a local dynamic spatial model. These local 3D models are composed to create an overall 3D model of the robot and its environment. This approach turns the computer vision problem into a search problem whose goal is the acquisition of sufficient spatial understanding for the robot to succeed at its tasks. The research hypothesis of this work is that the movements of the robot's cameras are only those that are necessary to build a sufficiently accurate world model for the robot's current goals. For example, if the goal is to navigate through a room, the model needs to contain any obstacles that would be encountered, giving their approximate positions and sizes. Other information does not need to be rendered into the virtual world, so this approach trades model accuracy for speed.

Vibrotactile feedback for conveying object shape information as perceived by artificial sensing of robotic arm.

PubMed

Khasnobish, Anwesha; Pal, Monalisa; Sardar, Dwaipayan; Tibarewala, D N; Konar, Amit

2016-08-01

This work is a preliminary study towards developing an alternative communication channel for conveying shape information to aid in recognition of items when tactile perception is hindered. Tactile data, acquired during object exploration by sensor fitted robot arm, are processed to recognize four basic geometric shapes. Patterns representing each shape, classified from tactile data, are generated using micro-controller-driven vibration motors which vibrotactually stimulate users to convey the particular shape information. These motors are attached on the subject's arm and their psychological (verbal) responses are recorded to assess the competence of the system to convey shape information to the user in form of vibrotactile stimulations. Object shapes are classified from tactile data with an average accuracy of 95.21 %. Three successive sessions of shape recognition from vibrotactile pattern depicted learning of the stimulus from subjects' psychological response which increased from 75 to 95 %. This observation substantiates the learning of vibrotactile stimulation in user over the sessions which in turn increase the system efficacy. The tactile sensing module and vibrotactile pattern generating module are integrated to complete the system whose operation is analysed in real-time. Thus, the work demonstrates a successful implementation of the complete schema of artificial tactile sensing system for object-shape recognition through vibrotactile stimulations.

Robust traffic sign detection using fuzzy shape recognizer

NASA Astrophysics Data System (ADS)

Li, Lunbo; Li, Jun; Sun, Jianhong

2009-10-01

A novel fuzzy approach for the detection of traffic signs in natural environments is presented. More than 3000 road images were collected under different weather conditions by a digital camera, and used for testing this approach. Every RGB image was converted into HSV colour space, and segmented by the hue and saturation thresholds. A symmetrical detector was used to extract the local features of the regions of interest (ROI), and the shape of ROI was determined by a fuzzy shape recognizer which invoked a set of fuzzy rules. The experimental results show that the proposed algorithm is translation, rotation and scaling invariant, and gives reliable shape recognition in complex traffic scenes where clustering and partial occlusion normally occur.

A feed-forward spiking model of shape-coding by IT cells

PubMed Central

Romeo, August; Supèr, Hans

2014-01-01

The ability to recognize a shape is linked to figure-ground (FG) organization. Cell preferences appear to be correlated across contrast-polarity reversals and mirror reversals of polygon displays, but not so much across FG reversals. Here we present a network structure which explains both shape-coding by simulated IT cells and suppression of responses to FG reversed stimuli. In our model FG segregation is achieved before shape discrimination, which is itself evidenced by the difference in spiking onsets of a pair of output cells. The studied example also includes feature extraction and illustrates a classification of binary images depending on the dominance of vertical or horizontal borders. PMID:24904494

Stick or Switch: A Selection Heuristic Predicts when People Take the Perspective of Others or Communicate Egocentrically.

PubMed

Rogers, Shane L; Fay, Nicolas

2016-01-01

This paper examines a cognitive mechanism that drives perspective-taking and egocentrism in interpersonal communication. Using a conceptual referential communication task, in which participants describe a range of abstract geometric shapes, Experiment 1 shows that perspective-taking and egocentric communication are frequent communication strategies. Experiment 2 tests a selection heuristic account of perspective-taking and egocentric communication. It uses participants' shape description ratings to predict their communication strategy. Participants' communication strategy was predicted by how informative they perceived the different shape descriptions to be. When participants' personal shape description was perceived to be more informative than their addressee's shape description, there was a strong bias to communicate egocentrically. By contrast, when their addressee's shape description was perceived to be more informative, there was a strong bias to take their addressee's perspective. When the shape descriptions were perceived to be equally informative, there was a moderate bias to communicate egocentrically. This simple, but powerful, selection heuristic may be critical to the cumulative cultural evolution of human communication systems, and cumulative cultural evolution more generally.

Extracting Metrics for Three-dimensional Root Systems: Volume and Surface Analysis from In-soil X-ray Computed Tomography Data.

PubMed

Suresh, Niraj; Stephens, Sean A; Adams, Lexor; Beck, Anthon N; McKinney, Adriana L; Varga, Tamas

2016-04-26

Plant roots play a critical role in plant-soil-microbe interactions that occur in the rhizosphere, as well as processes with important implications to climate change and crop management. Quantitative size information on roots in their native environment is invaluable for studying root growth and environmental processes involving plants. X-ray computed tomography (XCT) has been demonstrated to be an effective tool for in situ root scanning and analysis. We aimed to develop a costless and efficient tool that approximates the surface and volume of the root regardless of its shape from three-dimensional (3D) tomography data. The root structure of a Prairie dropseed (Sporobolus heterolepis) specimen was imaged using XCT. The root was reconstructed, and the primary root structure was extracted from the data using a combination of licensed and open-source software. An isosurface polygonal mesh was then created for ease of analysis. We have developed the standalone application imeshJ, generated in MATLAB(1), to calculate root volume and surface area from the mesh. The outputs of imeshJ are surface area (in mm(2)) and the volume (in mm(3)). The process, utilizing a unique combination of tools from imaging to quantitative root analysis, is described. A combination of XCT and open-source software proved to be a powerful combination to noninvasively image plant root samples, segment root data, and extract quantitative information from the 3D data. This methodology of processing 3D data should be applicable to other material/sample systems where there is connectivity between components of similar X-ray attenuation and difficulties arise with segmentation.

A Novel Method of Aircraft Detection Based on High-Resolution Panchromatic Optical Remote Sensing Images.

PubMed

Wang, Wensheng; Nie, Ting; Fu, Tianjiao; Ren, Jianyue; Jin, Longxu

2017-05-06

In target detection of optical remote sensing images, two main obstacles for aircraft target detection are how to extract the candidates in complex gray-scale-multi background and how to confirm the targets in case the target shapes are deformed, irregular or asymmetric, such as that caused by natural conditions (low signal-to-noise ratio, illumination condition or swaying photographing) and occlusion by surrounding objects (boarding bridge, equipment). To solve these issues, an improved active contours algorithm, namely region-scalable fitting energy based threshold (TRSF), and a corner-convex hull based segmentation algorithm (CCHS) are proposed in this paper. Firstly, the maximal variance between-cluster algorithm (Otsu's algorithm) and region-scalable fitting energy (RSF) algorithm are combined to solve the difficulty of targets extraction in complex and gray-scale-multi backgrounds. Secondly, based on inherent shapes and prominent corners, aircrafts are divided into five fragments by utilizing convex hulls and Harris corner points. Furthermore, a series of new structure features, which describe the proportion of targets part in the fragment to the whole fragment and the proportion of fragment to the whole hull, are identified to judge whether the targets are true or not. Experimental results show that TRSF algorithm could improve extraction accuracy in complex background, and that it is faster than some traditional active contours algorithms. The CCHS is effective to suppress the detection difficulties caused by the irregular shape.

Transferring of speech movements from video to 3D face space.

PubMed

Pei, Yuru; Zha, Hongbin

2007-01-01

We present a novel method for transferring speech animation recorded in low quality videos to high resolution 3D face models. The basic idea is to synthesize the animated faces by an interpolation based on a small set of 3D key face shapes which span a 3D face space. The 3D key shapes are extracted by an unsupervised learning process in 2D video space to form a set of 2D visemes which are then mapped to the 3D face space. The learning process consists of two main phases: 1) Isomap-based nonlinear dimensionality reduction to embed the video speech movements into a low-dimensional manifold and 2) K-means clustering in the low-dimensional space to extract 2D key viseme frames. Our main contribution is that we use the Isomap-based learning method to extract intrinsic geometry of the speech video space and thus to make it possible to define the 3D key viseme shapes. To do so, we need only to capture a limited number of 3D key face models by using a general 3D scanner. Moreover, we also develop a skull movement recovery method based on simple anatomical structures to enhance 3D realism in local mouth movements. Experimental results show that our method can achieve realistic 3D animation effects with a small number of 3D key face models.

Characterization of Nanoencapsulated Centella asiatica and Zingiber officinale Extract Using Combination of Malto Dextrin and Gum Arabic as Matrix

NASA Astrophysics Data System (ADS)

Meliana, Y.; Harmami, S. B.; Restu, W. K.

2017-02-01

This research investigated nanoencapsulation of Centella asiatica and Zingiber officinale extract. The encapsulated extract was used as a complex matrix of multi-layered interfacial membranes between malto dextrin and gum Arabic. Characterization of nanoencapsulation using Transmission Electron Microscope (TEM), Fourier Transform Infrared Spectroscopy (FTIR) and BET surface area (SA) showed the morphology, functional group and cumulative adsorption in the surface area of pores. The TEM image of the nanoencapsulated powders of Centella asiatica and Zingiber officinale extract showed a nearly spherical shape with the particle size of 664 nm from its average radius.

A rapid extraction of landslide disaster information research based on GF-1 image

NASA Astrophysics Data System (ADS)

Wang, Sai; Xu, Suning; Peng, Ling; Wang, Zhiyi; Wang, Na

2015-08-01

In recent years, the landslide disasters occurred frequently because of the seismic activity. It brings great harm to people's life. It has caused high attention of the state and the extensive concern of society. In the field of geological disaster, landslide information extraction based on remote sensing has been controversial, but high resolution remote sensing image can improve the accuracy of information extraction effectively with its rich texture and geometry information. Therefore, it is feasible to extract the information of earthquake- triggered landslides with serious surface damage and large scale. Taking the Wenchuan county as the study area, this paper uses multi-scale segmentation method to extract the landslide image object through domestic GF-1 images and DEM data, which uses the estimation of scale parameter tool to determine the optimal segmentation scale; After analyzing the characteristics of landslide high-resolution image comprehensively and selecting spectrum feature, texture feature, geometric features and landform characteristics of the image, we can establish the extracting rules to extract landslide disaster information. The extraction results show that there are 20 landslide whose total area is 521279.31 .Compared with visual interpretation results, the extraction accuracy is 72.22%. This study indicates its efficient and feasible to extract earthquake landslide disaster information based on high resolution remote sensing and it provides important technical support for post-disaster emergency investigation and disaster assessment.

Extracellular synthesis of silver nanoparticles using the leaf extract of Coleus amboinicus Lour

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

Narayanan, Kannan Badri; Sakthivel, Natarajan, E-mail: puns2005@gmail.com

2011-10-15

Highlights: {yields} Synthesis of AgNPs using the leaf extract of Coleus amboinicus L. was described. {yields} UV-vis absorption spectra showed the formation of isotrophic AgNPs at 437 nm in 6 h. {yields} XRD analysis showed intense peaks corresponding to fcc structure of AgNPs. {yields} HR-TEM analysis revealed the formation of stable anisotrophic and isotrophic AgNPs. -- Abstract: In the present investigation, Coleus amboinicus Lour. leaf extract-mediated green chemistry approach for the synthesis of silver nanoparticles was described. The nanoparticles were characterized by ultraviolet-visible (UV-Vis) spectroscopy, X-ray diffraction (XRD), energy dispersive X-ray analysis (EDAX), Fourier transform infrared spectroscopy (FTIR) and transmissionmore » electron microscopy (TEM). The influence of leaf extract on the control of size and shape of silver nanoparticles is reported. Upon an increase in the concentration of leaf extract, there was a shift in the shape of nanoparticles from anisotrophic nanostructures like triangle, decahedral and hexagonal to isotrophic spherical nanoparticles. Crystalline nature of fcc structured nanoparticles was confirmed by XRD spectrum with peaks corresponding to (1 1 1), (2 0 0), (2 2 0) and (3 1 1) planes and bright circular spots in the selected-area electron diffraction (SAED). Such environment friendly and sustainable methods are non-toxic, cheap and alternative to hazardous chemical procedures.« less

Extracting hurricane eye morphology from spaceborne SAR images using morphological analysis

NASA Astrophysics Data System (ADS)

Lee, Isabella K.; Shamsoddini, Ali; Li, Xiaofeng; Trinder, John C.; Li, Zeyu

2016-07-01

Hurricanes are among the most destructive global natural disasters. Thus recognizing and extracting their morphology is important for understanding their dynamics. Conventional optical sensors, due to cloud cover associated with hurricanes, cannot reveal the intense air-sea interaction occurring at the sea surface. In contrast, the unique capabilities of spaceborne synthetic aperture radar (SAR) data for cloud penetration, and its backscattering signal characteristics enable the extraction of the sea surface roughness. Therefore, SAR images enable the measurement of the size and shape of hurricane eyes, which reveal their evolution and strength. In this study, using six SAR hurricane images, we have developed a mathematical morphology method for automatically extracting the hurricane eyes from C-band SAR data. Skeleton pruning based on discrete skeleton evolution (DSE) was used to ensure global and local preservation of the hurricane eye shape. This distance weighted algorithm applied in a hierarchical structure for extraction of the edges of the hurricane eyes, can effectively avoid segmentation errors by reducing redundant skeletons attributed to speckle noise along the edges of the hurricane eye. As a consequence, the skeleton pruning has been accomplished without deficiencies in the key hurricane eye skeletons. A morphology-based analyses of the subsequent reconstructions of the hurricane eyes shows a high degree of agreement with the hurricane eye areas derived from reference data based on NOAA manual work.

Multi-Filter String Matching and Human-Centric Entity Matching for Information Extraction

ERIC Educational Resources Information Center

Sun, Chong

2012-01-01

More and more information is being generated in text documents, such as Web pages, emails and blogs. To effectively manage this unstructured information, one broadly used approach includes locating relevant content in documents, extracting structured information and integrating the extracted information for querying, mining or further analysis. In…

Extracting Useful Semantic Information from Large Scale Corpora of Text

ERIC Educational Resources Information Center

Mendoza, Ray Padilla, Jr.

2012-01-01

Extracting and representing semantic information from large scale corpora is at the crux of computer-assisted knowledge generation. Semantic information depends on collocation extraction methods, mathematical models used to represent distributional information, and weighting functions which transform the space. This dissertation provides a…

Preparation of polydimethylsiloxane/beta-cyclodextrin/divinylbenzene coated "dumbbell-shaped" stir bar and its application to the analysis of polycyclic aromatic hydrocarbons and polycyclic aromatic sulfur heterocycles compounds in lake water and soil by high performance liquid chromatography.

PubMed

Yu, Chunhe; Yao, Zhimin; Hu, Bin

2009-05-08

A "dumbbell-shaped" stir bar was proposed to prevent the friction loss of coating during the stirring process, and thus prolonged the lifetime of stir bars. The effects of the coating components, including polydimethylsiloxane (PDMS), beta-cyclodextrin (beta-CD) and divinylbenzene (DVB) were investigated according to an orthogonal experimental design, using three polycyclic aromatic hydrocarbons (PAHs) and four polycyclic aromatic sulfur heterocycles (PASHs) as model analytes. Four kinds of stir bars coated with PDMS, PDMS/beta-CD, PDMS/DVB and PDMS/beta-CD/DVB were prepared and their extraction efficiencies for the target compounds were compared. It was demonstrated that PDMS/beta-CD/DVB-coated stir bar showed the best affinity to the studied compounds. The preparation reproducibility of PDMS/beta-CD/DVB-coated stir bar ranged from 3.2% to 15.2% (n = 6) in one batch, and 5.2% to 13.4% (n = 6) among batches. The "dumbbell-shaped" stir bar could be used for about 40 times, which were 10 extractions more than a normal stir bar. The prepared PDMS/beta-CD/DVB-coated "dumbbell-shaped" stir bar was used for stir bar sorptive extraction (SBSE) of PAHs and PASHs and the desorbed solution was introduced into HPLC-UV for subsequent analysis. The limits of detection of the proposed method for seven target analytes ranged from 0.007 to 0.103 microg L(-1), the relative standard deviations were in the range of 6.3-12.9% (n = 6, c = 40 microg L(-1)), and the enrichment factors were 19-86. The proposed method was successfully applied to the analysis of seven target analytes in lake water and soil samples.

Hydrodynamic and sedimentological controls governing formation of fluvial levees

NASA Astrophysics Data System (ADS)

Johnston, G. H.; Edmonds, D. A.; David, S. R.; Czuba, J. A.

2017-12-01

Fluvial levees are familiar features found on the margins of river channels, yet we know little about what controls their presence, height, and shape. These attributes of levees are important because they control sediment transfer from channel to floodplain and flooding patterns along a river system. Despite the familiarity and importance of levees, there is a surprising lack of basic geomorphic data on fluvial levees. Because of this we seek to understand: 1) where along rivers do levees tend to occur?; 2) what geomorphic and hydrodynamic variables control cross-sectional shape of levees? We address these questions by extracting levee shape from LiDAR data and by collecting hydrodynamic and sedimentological data from reaches of the Tippecanoe River, the White River, and the Muscatatuck River, Indiana, USA. Fluvial levees are extracted from a 1.5-m resolution LiDAR bare surface model and compared to hydrological, sedimentological, and geomorphological data from USGS stream gages. We digitized banklines and extracted levee cross-sections to calculate levee slope, taper, height, e-folding length, and e-folding width. To answer the research questions, we performed a multivariable regression between the independent variables—channel geometry, sediment grain size and concentration, flooding conditions, and slope—and the dependent levee variables. We find considerable variation in levee presence and shape in our field data. On the Muscatatuck River levees occur on 30% of the banks compared to 10% on the White River. Moreover, levees on the Muscatatuck are on average 3 times wider than the White River. This is consistent with the observation that the Muscatatuck is finer-grained compared to the White River and points to sedimentology being an important control on levee geomorphology. Future work includes building a morphodynamic model to understand how different hydrodynamic and geomorphic conditions control levee geometry.

Thermal management and light extraction in multi-chip and high-voltage LEDs by cup-shaped copper heat spreader technology

NASA Astrophysics Data System (ADS)

Horng, Ray-Hua; Hu, Hung-Lieh; Tang, Li-Shen; Ou, Sin-Liang

2013-03-01

For LEDs with original structure and copper heat spreader, the highest surface temperatures of 3×3 array LEDs modules were 52.6 and 42.67 °C (with 1050 mA injection current), while the highest surface temperatures of 4×4 array LEDs modules were 58.55 and 48.85 °C (with 1400 mA injection current), respectively. As the 5×5 array LEDs modules with original structure and copper heat spreader were fabricated, the highest surface temperatures at 1750 mA injection current were 68.51 and 56.73 °C, respectively. The thermal resistance of optimal LEDs array module with copper heat spreader on heat sink using compound solder is reduced obviously. On the other hand, the output powers of 3×3, 4×4 and 5×5 array LEDs modules with original structure were 3621.7, 6346.3 and 9760.4 mW at injection currents of 1050, 1400 and 1750 mA, respectively. Meanwhile, the output powers of these samples with copper heat spreader can be improved to 4098.5, 7150.3 and 10919.6 mW, respectively. The optical and thermal characteristics of array LEDs module have been improved significantly using the cup-shaped copper structure. Furthermore, various types of epoxy-packaged LEDs with cup-shaped structure were also fabricated. It is found that the light extraction efficiency of LED with semicircle package has 55% improvement as compared to that of LED with flat package. The cup-shaped copper structure was contacted directly with sapphire to enhance heat dissipation. In addition to efficient heat dissipation, the light extraction of the lateral emitting in high-power LEDs can be improved.

Automated road network extraction from high spatial resolution multi-spectral imagery

NASA Astrophysics Data System (ADS)

Zhang, Qiaoping

For the last three decades, the Geomatics Engineering and Computer Science communities have considered automated road network extraction from remotely-sensed imagery to be a challenging and important research topic. The main objective of this research is to investigate the theory and methodology of automated feature extraction for image-based road database creation, refinement or updating, and to develop a series of algorithms for road network extraction from high resolution multi-spectral imagery. The proposed framework for road network extraction from multi-spectral imagery begins with an image segmentation using the k-means algorithm. This step mainly concerns the exploitation of the spectral information for feature extraction. The road cluster is automatically identified using a fuzzy classifier based on a set of predefined road surface membership functions. These membership functions are established based on the general spectral signature of road pavement materials and the corresponding normalized digital numbers on each multi-spectral band. Shape descriptors of the Angular Texture Signature are defined and used to reduce the misclassifications between roads and other spectrally similar objects (e.g., crop fields, parking lots, and buildings). An iterative and localized Radon transform is developed for the extraction of road centerlines from the classified images. The purpose of the transform is to accurately and completely detect the road centerlines. It is able to find short, long, and even curvilinear lines. The input image is partitioned into a set of subset images called road component images. An iterative Radon transform is locally applied to each road component image. At each iteration, road centerline segments are detected based on an accurate estimation of the line parameters and line widths. Three localization approaches are implemented and compared using qualitative and quantitative methods. Finally, the road centerline segments are grouped into a road network. The extracted road network is evaluated against a reference dataset using a line segment matching algorithm. The entire process is unsupervised and fully automated. Based on extensive experimentation on a variety of remotely-sensed multi-spectral images, the proposed methodology achieves a moderate success in automating road network extraction from high spatial resolution multi-spectral imagery.

Feature precedence in processing multifeature visual information in the human brain: an event-related potential study.

PubMed

Liu, B; Meng, X; Wu, G; Huang, Y

2012-05-17

In this article, we aimed to study whether feature precedence existed in the cognitive processing of multifeature visual information in the human brain. In our experiment, we paid attention to two important visual features as follows: color and shape. In order to avoid the presence of semantic constraints between them and the resulting impact, pure color and simple geometric shape were chosen as the color feature and shape feature of visual stimulus, respectively. We adopted an "old/new" paradigm to study the cognitive processing of color feature, shape feature and the combination of color feature and shape feature, respectively. The experiment consisted of three tasks as follows: Color task, Shape task and Color-Shape task. The results showed that the feature-based pattern would be activated in the human brain in processing multifeature visual information without semantic association between features. Furthermore, shape feature was processed earlier than color feature, and the cognitive processing of color feature was more difficult than that of shape feature. Copyright © 2012 IBRO. Published by Elsevier Ltd. All rights reserved.

Tree detection in orchards from VHR satellite images using scale-space theory

NASA Astrophysics Data System (ADS)

Mahour, Milad; Tolpekin, Valentyn; Stein, Alfred

2016-10-01

This study focused on extracting reliable and detailed information from very High Resolution (VHR) satellite images for the detection of individual trees in orchards. The images contain detailed information on spectral and geometrical properties of trees. Their scale level, however, is insufficient for spectral properties of individual trees, because adjacent tree canopies interlock. We modeled trees using a bell shaped spectral profile. Identifying the brightest peak was challenging due to sun illumination effects caused 1 by differences in positions of the sun and the satellite sensor. Crown boundary detection was solved by using the NDVI from the same image. We used Gaussian scale-space methods that search for extrema in the scale-space domain. The procedures were tested on two orchards with different tree types, tree sizes and tree observation patterns in Iran. Validation was done using reference data derived from an UltraCam digital aerial photo. Local extrema of the determinant of the Hessian corresponded well to the geographical coordinates and the size of individual trees. False detections arising from a slight asymmetry of trees were distinguished from multiple detections of the same tree with different extents. Uncertainty assessment was carried out on the presence and spatial extents of individual trees. The study demonstrated how the suggested approach can be used for image segmentation for orchards with different types of trees. We concluded that Gaussian scale-space theory can be applied to extract information from VHR satellite images for individual tree detection. This may lead to improved decision making for irrigation and crop water requirement purposes in future studies.

Target discrimination of man-made objects using passive polarimetric signatures acquired in the visible and infrared spectral bands

NASA Astrophysics Data System (ADS)

Lavigne, Daniel A.; Breton, Mélanie; Fournier, Georges; Charette, Jean-François; Pichette, Mario; Rivet, Vincent; Bernier, Anne-Pier

2011-10-01

Surveillance operations and search and rescue missions regularly exploit electro-optic imaging systems to detect targets of interest in both the civilian and military communities. By incorporating the polarization of light as supplementary information to such electro-optic imaging systems, it is possible to increase their target discrimination capabilities, considering that man-made objects are known to depolarized light in different manner than natural backgrounds. As it is known that electro-magnetic radiation emitted and reflected from a smooth surface observed near a grazing angle becomes partially polarized in the visible and infrared wavelength bands, additional information about the shape, roughness, shading, and surface temperatures of difficult targets can be extracted by processing effectively such reflected/emitted polarized signatures. This paper presents a set of polarimetric image processing algorithms devised to extract meaningful information from a broad range of man-made objects. Passive polarimetric signatures are acquired in the visible, shortwave infrared, midwave infrared, and longwave infrared bands using a fully automated imaging system developed at DRDC Valcartier. A fusion algorithm is used to enable the discrimination of some objects lying in shadowed areas. Performance metrics, derived from the computed Stokes parameters, characterize the degree of polarization of man-made objects. Field experiments conducted during winter and summer time demonstrate: 1) the utility of the imaging system to collect polarized signatures of different objects in the visible and infrared spectral bands, and 2) the enhanced performance of target discrimination and fusion algorithms to exploit the polarized signatures of man-made objects against cluttered backgrounds.

Microbial genotype-phenotype mapping by class association rule mining.

PubMed

Tamura, Makio; D'haeseleer, Patrik

2008-07-01

Microbial phenotypes are typically due to the concerted action of multiple gene functions, yet the presence of each gene may have only a weak correlation with the observed phenotype. Hence, it may be more appropriate to examine co-occurrence between sets of genes and a phenotype (multiple-to-one) instead of pairwise relations between a single gene and the phenotype. Here, we propose an efficient class association rule mining algorithm, netCAR, in order to extract sets of COGs (clusters of orthologous groups of proteins) associated with a phenotype from COG phylogenetic profiles and a phenotype profile. netCAR takes into account the phylogenetic co-occurrence graph between COGs to restrict hypothesis space, and uses mutual information to evaluate the biconditional relation. We examined the mining capability of pairwise and multiple-to-one association by using netCAR to extract COGs relevant to six microbial phenotypes (aerobic, anaerobic, facultative, endospore, motility and Gram negative) from 11,969 unique COG profiles across 155 prokaryotic organisms. With the same level of false discovery rate, multiple-to-one association can extract about 10 times more relevant COGs than one-to-one association. We also reveal various topologies of association networks among COGs (modules) from extracted multiple-to-one correlation rules relevant with the six phenotypes; including a well-connected network for motility, a star-shaped network for aerobic and intermediate topologies for the other phenotypes. netCAR outperforms a standard CAR mining algorithm, CARapriori, while requiring several orders of magnitude less computational time for extracting 3-COG sets. Source code of the Java implementation is available as Supplementary Material at the Bioinformatics online website, or upon request to the author. Supplementary data are available at Bioinformatics online.

[Skeleton extractions and applications].

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

Quadros, William Roshan

2010-05-01

This paper focuses on the extraction of skeletons of CAD models and its applications in finite element (FE) mesh generation. The term 'skeleton of a CAD model' can be visualized as analogous to the 'skeleton of a human body'. The skeletal representations covered in this paper include medial axis transform (MAT), Voronoi diagram (VD), chordal axis transform (CAT), mid surface, digital skeletons, and disconnected skeletons. In the literature, the properties of a skeleton have been utilized in developing various algorithms for extracting skeletons. Three main approaches include: (1) the bisection method where the skeleton exists at equidistant from at leastmore » two points on boundary, (2) the grassfire propagation method in which the skeleton exists where the opposing fronts meet, and (3) the duality method where the skeleton is a dual of the object. In the last decade, the author has applied different skeletal representations in all-quad meshing, hex meshing, mid-surface meshing, mesh size function generation, defeaturing, and decomposition. A brief discussion on the related work from other researchers in the area of tri meshing, tet meshing, and anisotropic meshing is also included. This paper concludes by summarizing the strengths and weaknesses of the skeleton-based approaches in solving various geometry-centered problems in FE mesh generation. The skeletons have proved to be a great shape abstraction tool in analyzing the geometric complexity of CAD models as they are symmetric, simpler (reduced dimension), and provide local thickness information. However, skeletons generally require some cleanup, and stability and sensitivity of the skeletons should be controlled during extraction. Also, selecting a suitable application-specific skeleton and a computationally efficient method of extraction is critical.« less

Phytofabrication and characterization of monodisperse copper oxide nanoparticles using Albizia lebbeck leaf extract

NASA Astrophysics Data System (ADS)

Jayakumarai, G.; Gokulpriya, C.; Sudhapriya, R.; Sharmila, G.; Muthukumaran, C.

2015-12-01

Simple effective and rapid approach for the green synthesis of copper oxide nanoparticles (CONPs) using of Albizia lebbeck leaf extract was investigated in this study. Various instrumental techniques were adopted to characterize the synthesized CONPs, viz. UV-Vis spectroscopy, SEM, TEM, EDS and XRD. The synthesized CONPs were found to be spherical in shape and size less than 100 nm. It could be concluded that A. lebbeck leaf extract can be used as a cheap and effective reducing agent for CONPs production in large scale.

Soft lithography microlens fabrication and array for enhanced light extraction from organic light emitting diodes (OLEDs)

DOEpatents

Leung, Wai Y.; Park, Joong-Mok; Gan, Zhengqing; Constant, Kristen P.; Shinar, Joseph; Shinar, Ruth; ho, Kai-Ming

2014-06-03

Provided are microlens arrays for use on the substrate of OLEDs to extract more light that is trapped in waveguided modes inside the devices and methods of manufacturing same. Light extraction with microlens arrays is not limited to the light emitting area, but is also efficient in extracting light from the whole microlens patterned area where waveguiding occurs. Large microlens array, compared to the size of the light emitting area, extract more light and result in over 100% enhancement. Such a microlens array is not limited to (O)LEDs of specific emission, configuration, pixel size, or pixel shape. It is suitable for all colors, including white, for microcavity OLEDs, and OLEDs fabricated directly on the (modified) microlens array.

Characterization of the shape and line-edge roughness of polymer gratings with grazing incidence small-angle X-ray scattering and atomic force microscopy

DOE PAGES

Suh, Hyo Seon; Chen, Xuanxuan; Rincon-Delgadillo, Paulina A.; ...

2016-04-22

Grazing-incidence small-angle X-ray scattering (GISAXS) is increasingly used for the metrology of substrate-supported nanoscale features and nanostructured films. In the case of line gratings, where long objects are arranged with a nanoscale periodicity perpendicular to the beam, a series of characteristic spots of high-intensity (grating truncation rods, GTRs) are recorded on a two-dimensional detector. The intensity of the GTRs is modulated by the three-dimensional shape and arrangement of the lines. Previous studies aimed to extract an average cross-sectional profile of the gratings, attributing intensity loss at GTRs to sample imperfections. Such imperfections are just as important as the average shapemore » when employing soft polymer gratings which display significant line-edge roughness. Herein are reported a series of GISAXS measurements of polymer line gratings over a range of incident angles. Both an average shape and fluctuations contributing to the intensity in between the GTRs are extracted. Lastly, the results are critically compared with atomic force microscopy (AFM) measurements, and it is found that the two methods are in good agreement if appropriate corrections for scattering from the substrate (GISAXS) and contributions from the probe shape (AFM) are accounted for.« less

Green synthesis and characterization of Carica papaya leaf extract coated silver nanoparticles through X-ray diffraction, electron microscopy and evaluation of bactericidal properties

PubMed Central

Banala, Rajkiran Reddy; Nagati, Veera Babu; Karnati, Pratap Reddy

2015-01-01

The evolution of nanotechnology and the production of nanomedicine from various sources had proven to be of intense value in the field of biomedicine. The smaller size of nanoparticles is gaining importance in research for the treatment of various diseases. Moreover the production of nanoparticles is eco-friendly and cost effective. In the present study silver nanoparticles were synthesized from Carica papaya leaf extract (CPL) and characterized for their size and shape using scanning electron microscopy and transmission electron microscopy, respectively. Fourier transform infrared spectroscopy (FTIR), Energy dispersive X-ray spectroscopy (EDS/EDX) and X-ray diffraction spectroscopy (XRD) were conducted to determine the concentration of metal ions, the shape of molecules. The bactericidal activity was evaluated using Luria Bertani broth cultures and the minimum inhibition concentration (MIC) and minimum bactericidal concentration (MBC) were estimated using turbidimetry. The data analysis showed size of 50–250 nm spherical shaped nanoparticles. The turbidimetry analysis showed MIC and MBC was >25 μg/mL against both Gram positive and Gram negative bacteria in Luria Bertani broth cultures. In summary the synthesized silver nanoparticles from CPL showed acceptable size and shape of nanoparticles and effective bactericidal activity. PMID:26288570

Green synthesis and characterization of Carica papaya leaf extract coated silver nanoparticles through X-ray diffraction, electron microscopy and evaluation of bactericidal properties.

PubMed

Banala, Rajkiran Reddy; Nagati, Veera Babu; Karnati, Pratap Reddy

2015-09-01

The evolution of nanotechnology and the production of nanomedicine from various sources had proven to be of intense value in the field of biomedicine. The smaller size of nanoparticles is gaining importance in research for the treatment of various diseases. Moreover the production of nanoparticles is eco-friendly and cost effective. In the present study silver nanoparticles were synthesized from Carica papaya leaf extract (CPL) and characterized for their size and shape using scanning electron microscopy and transmission electron microscopy, respectively. Fourier transform infrared spectroscopy (FTIR), Energy dispersive X-ray spectroscopy (EDS/EDX) and X-ray diffraction spectroscopy (XRD) were conducted to determine the concentration of metal ions, the shape of molecules. The bactericidal activity was evaluated using Luria Bertani broth cultures and the minimum inhibition concentration (MIC) and minimum bactericidal concentration (MBC) were estimated using turbidimetry. The data analysis showed size of 50-250 nm spherical shaped nanoparticles. The turbidimetry analysis showed MIC and MBC was >25 μg/mL against both Gram positive and Gram negative bacteria in Luria Bertani broth cultures. In summary the synthesized silver nanoparticles from CPL showed acceptable size and shape of nanoparticles and effective bactericidal activity.

Active vibration damping using smart material

NASA Technical Reports Server (NTRS)

Baras, John S.; Yan, Zhuang

1994-01-01

We consider the modeling and active damping of an elastic beam using distributed actuators and sensors. The piezoelectric ceramic material (PZT) is used to build the actuator. The sensor is made of the piezoelectric polymer polyvinylidene fluoride (PVDF). These materials are glued on both sides of the beam. For the simple clamped beam, the closed loop controller has been shown to be able to extract energy from the beam. The shape of the actuator and its influence on the closed loop system performance are discussed. It is shown that it is possible to suppress the selected mode by choosing the appropriate actuator layout. It is also shown that by properly installing the sensor and determining the sensor shape we can further extract and manipulate the sensor signal for our control need.

Increased Alpha-Band Power during the Retention of Shapes and Shape-Location Associations in Visual Short-Term Memory

PubMed Central

Johnson, Jeffrey S.; Sutterer, David W.; Acheson, Daniel J.; Lewis-Peacock, Jarrod A.; Postle, Bradley R.

2011-01-01

Studies exploring the role of neural oscillations in cognition have revealed sustained increases in alpha-band (~8–14 Hz) power during the delay period of delayed-recognition short-term memory tasks. These increases have been proposed to reflect the inhibition, for example, of cortical areas representing task-irrelevant information, or of potentially interfering representations from previous trials. Another possibility, however, is that elevated delay-period alpha-band power (DPABP) reflects the selection and maintenance of information, rather than, or in addition to, the inhibition of task-irrelevant information. In the present study, we explored these possibilities using a delayed-recognition paradigm in which the presence and task relevance of shape information was systematically manipulated across trial blocks and electroencephalographic was used to measure alpha-band power. In the first trial block, participants remembered locations marked by identical black circles. The second block featured the same instructions, but locations were marked by unique shapes. The third block featured the same stimulus presentation as the second, but with pretrial instructions indicating, on a trial-by-trial basis, whether memory for shape or location was required, the other dimension being irrelevant. In the final block, participants remembered the unique pairing of shape and location for each stimulus. Results revealed minimal DPABP in each of the location-memory conditions, whether locations were marked with identical circles or with unique task-irrelevant shapes. In contrast, alpha-band power increases were observed in both the shape-memory condition, in which location was task irrelevant, and in the critical final condition, in which both shape and location were task relevant. These results provide support for the proposal that alpha-band oscillations reflect the retention of shape information and/or shape–location associations in short-term memory. PMID:21713012

Nanopipettes as Monitoring Probes for the Single Living Cell: State of the Art and Future Directions in Molecular Biology.

PubMed

Bulbul, Gonca; Chaves, Gepoliano; Olivier, Joseph; Ozel, Rifat Emrah; Pourmand, Nader

2018-06-06

Examining the behavior of a single cell within its natural environment is valuable for understanding both the biological processes that control the function of cells and how injury or disease lead to pathological change of their function. Single-cell analysis can reveal information regarding the causes of genetic changes, and it can contribute to studies on the molecular basis of cell transformation and proliferation. By contrast, whole tissue biopsies can only yield information on a statistical average of several processes occurring in a population of different cells. Electrowetting within a nanopipette provides a nanobiopsy platform for the extraction of cellular material from single living cells. Additionally, functionalized nanopipette sensing probes can differentiate analytes based on their size, shape or charge density, making the technology uniquely suited to sensing changes in single-cell dynamics. In this review, we highlight the potential of nanopipette technology as a non-destructive analytical tool to monitor single living cells, with particular attention to integration into applications in molecular biology.

Ship detection from high-resolution imagery based on land masking and cloud filtering

NASA Astrophysics Data System (ADS)

Jin, Tianming; Zhang, Junping

2015-12-01

High resolution satellite images play an important role in target detection application presently. This article focuses on the ship target detection from the high resolution panchromatic images. Taking advantage of geographic information such as the coastline vector data provided by NOAA Medium Resolution Coastline program, the land region is masked which is a main noise source in ship detection process. After that, the algorithm tries to deal with the cloud noise which appears frequently in the ocean satellite images, which is another reason for false alarm. Based on the analysis of cloud noise's feature in frequency domain, we introduce a windowed noise filter to get rid of the cloud noise. With the help of morphological processing algorithms adapted to target detection, we are able to acquire ship targets in fine shapes. In addition, we display the extracted information such as length and width of ship targets in a user-friendly way i.e. a KML file interpreted by Google Earth.

Automatic Recognition of Indoor Navigation Elements from Kinect Point Clouds

NASA Astrophysics Data System (ADS)

Zeng, L.; Kang, Z.

2017-09-01

This paper realizes automatically the navigating elements defined by indoorGML data standard - door, stairway and wall. The data used is indoor 3D point cloud collected by Kinect v2 launched in 2011 through the means of ORB-SLAM. By contrast, it is cheaper and more convenient than lidar, but the point clouds also have the problem of noise, registration error and large data volume. Hence, we adopt a shape descriptor - histogram of distances between two randomly chosen points, proposed by Osada and merges with other descriptor - in conjunction with random forest classifier to recognize the navigation elements (door, stairway and wall) from Kinect point clouds. This research acquires navigation elements and their 3-d location information from each single data frame through segmentation of point clouds, boundary extraction, feature calculation and classification. Finally, this paper utilizes the acquired navigation elements and their information to generate the state data of the indoor navigation module automatically. The experimental results demonstrate a high recognition accuracy of the proposed method.

Material and shape perception based on two types of intensity gradient information

PubMed Central

Nishida, Shin'ya

2018-01-01

Visual estimation of the material and shape of an object from a single image includes a hard ill-posed computational problem. However, in our daily life we feel we can estimate both reasonably well. The neural computation underlying this ability remains poorly understood. Here we propose that the human visual system uses different aspects of object images to separately estimate the contributions of the material and shape. Specifically, material perception relies mainly on the intensity gradient magnitude information, while shape perception relies mainly on the intensity gradient order information. A clue to this hypothesis was provided by the observation that luminance-histogram manipulation, which changes luminance gradient magnitudes but not the luminance-order map, effectively alters the material appearance but not the shape of an object. In agreement with this observation, we found that the simulated physical material changes do not significantly affect the intensity order information. A series of psychophysical experiments further indicate that human surface shape perception is robust against intensity manipulations provided they do not disturb the intensity order information. In addition, we show that the two types of gradient information can be utilized for the discrimination of albedo changes from highlights. These findings suggest that the visual system relies on these diagnostic image features to estimate physical properties in a distal world. PMID:29702644

The mammalian bony labyrinth reconsidered, introducing a comprehensive geometric morphometric approach

PubMed Central

Gunz, Philipp; Ramsier, Marissa; Kuhrig, Melanie; Hublin, Jean-Jacques; Spoor, Fred

2012-01-01

The bony labyrinth in the temporal bone houses the sensory systems of balance and hearing. While the overall structure of the semicircular canals and cochlea is similar across therian mammals, their detailed morphology varies even among closely related groups. As such, the shape of the labyrinth carries valuable functional and phylogenetic information. Here we introduce a new, semilandmark-based three-dimensional geometric morphometric approach to shape analysis of the labyrinth, as a major improvement upon previous metric studies based on linear measurements and angles. We first provide a detailed, step-by-step description of the measurement protocol. Subsequently, we test our approach using a geographically diverse sample of 50 recent modern humans and 30 chimpanzee specimens belonging to Pan troglodytes troglodytes and P. t. verus. Our measurement protocol can be applied to CT scans of different spatial resolutions because it primarily quantifies the midline skeleton of the bony labyrinth. Accurately locating the lumen centre of the semicircular canals and the cochlea is not affected by the partial volume and thresholding effects that can make the comparison of the outer border problematic. After virtually extracting the bony labyrinth from CT scans of the temporal bone, we computed its midline skeleton by thinning the encased volume. On the resulting medial axes of the semicircular canals and cochlea we placed a sequence of semilandmarks. After Procrustes superimposition, the shape coordinates were analysed using multivariate statistics. We found statistically significant shape differences between humans and chimpanzees which corroborate previous analyses of the labyrinth based on traditional measurements. As the geometric relationship among the semilandmark coordinates was preserved throughout the analysis, we were able to quantify and visualize even small-scale shape differences. Notably, our approach made it possible to detect and visualize subtle, yet statistically significant (P = 0.009), differences between two chimpanzee subspecies in the shape of their semicircular canals. The ability to discriminate labyrinth shape at the subspecies level demonstrates that the approach presented here has great potential in future taxonomic studies of fossil specimens. PMID:22404255

The Future of Informal Learning

ERIC Educational Resources Information Center

Taylor, Richard

2008-01-01

"Informal Adult Learning: Shaping the Way Ahead," the Government's consultation on the future of informal adult learning in England, was launched by Secretary of State for Innovation, Universities and Skills, John Denham, on January 15, 2007. The consultation invites respondents to help shape "a new vision for informal adult…

A extract method of mountainous area settlement place information from GF-1 high resolution optical remote sensing image under semantic constraints

NASA Astrophysics Data System (ADS)

Guo, H., II

2016-12-01

Spatial distribution information of mountainous area settlement place is of great significance to the earthquake emergency work because most of the key earthquake hazardous areas of china are located in the mountainous area. Remote sensing has the advantages of large coverage and low cost, it is an important way to obtain the spatial distribution information of mountainous area settlement place. At present, fully considering the geometric information, spectral information and texture information, most studies have applied object-oriented methods to extract settlement place information, In this article, semantic constraints is to be added on the basis of object-oriented methods. The experimental data is one scene remote sensing image of domestic high resolution satellite (simply as GF-1), with a resolution of 2 meters. The main processing consists of 3 steps, the first is pretreatment, including ortho rectification and image fusion, the second is Object oriented information extraction, including Image segmentation and information extraction, the last step is removing the error elements under semantic constraints, in order to formulate these semantic constraints, the distribution characteristics of mountainous area settlement place must be analyzed and the spatial logic relation between settlement place and other objects must be considered. The extraction accuracy calculation result shows that the extraction accuracy of object oriented method is 49% and rise up to 86% after the use of semantic constraints. As can be seen from the extraction accuracy, the extract method under semantic constraints can effectively improve the accuracy of mountainous area settlement place information extraction. The result shows that it is feasible to extract mountainous area settlement place information form GF-1 image, so the article proves that it has a certain practicality to use domestic high resolution optical remote sensing image in earthquake emergency preparedness.

Green synthesis of gold and silver nanoparticles using Hibiscus rosa sinensis

NASA Astrophysics Data System (ADS)

Philip, Daizy

2010-03-01

Biological synthesis of gold and silver nanoparticles of various shapes using the leaf extract of Hibiscus rosa sinensis is reported. This is a simple, cost-effective, stable for long time and reproducible aqueous room temperature synthesis method to obtain a self-assembly of Au and Ag nanoparticles. The size and shape of Au nanoparticles are modulated by varying the ratio of metal salt and extract in the reaction medium. Variation of pH of the reaction medium gives silver nanoparticles of different shapes. The nanoparticles obtained are characterized by UV-vis, transmission electron microscopy (TEM), X-ray diffraction (XRD) and FTIR spectroscopy. Crystalline nature of the nanoparticles in the fcc structure are confirmed by the peaks in the XRD pattern corresponding to (1 1 1), (2 0 0), (2 2 0) and (3 1 1) planes, bright circular spots in the selected area electron diffraction (SAED) and clear lattice fringes in the high-resolution TEM image. From FTIR spectra it is found that the Au nanoparticles are bound to amine groups and the Ag nanoparticles to carboxylate ion groups.

Single-Rooted Extraction Sockets: Classification and Treatment Protocol.

PubMed

El Chaar, Edgar; Oshman, Sarah; Fallah Abed, Pooria

2016-09-01

Clinicians have many treatment techniques from which to choose when extracting a failing tooth and replacing it with an implant-supported restoration and when successful management of an extraction socket during the course of tooth replacement is necessary to achieve predictable and esthetic outcomes. This article presents a straightforward, yet thorough, classification for extraction sockets of single-rooted teeth and provides guidance to clinicians in the selection of appropriate and predictable treatment. The presented classification of extraction sockets for single-rooted teeth focuses on the topography of the extraction socket, while the protocol for treatment of each socket type factors in the shape of the remaining bone, the biotype, and the location of the socket whether it be in the mandible or maxilla. This system is based on the biologic foundations of wound healing and can help guide clinicians to successful treatment outcomes.

Autism, Context/Noncontext Information Processing, and Atypical Development

PubMed Central

Skoyles, John R.

2011-01-01

Autism has been attributed to a deficit in contextual information processing. Attempts to understand autism in terms of such a defect, however, do not include more recent computational work upon context. This work has identified that context information processing depends upon the extraction and use of the information hidden in higher-order (or indirect) associations. Higher-order associations underlie the cognition of context rather than that of situations. This paper starts by examining the differences between higher-order and first-order (or direct) associations. Higher-order associations link entities not directly (as with first-order ones) but indirectly through all the connections they have via other entities. Extracting this information requires the processing of past episodes as a totality. As a result, this extraction depends upon specialised extraction processes separate from cognition. This information is then consolidated. Due to this difference, the extraction/consolidation of higher-order information can be impaired whilst cognition remains intact. Although not directly impaired, cognition will be indirectly impaired by knock on effects such as cognition compensating for absent higher-order information with information extracted from first-order associations. This paper discusses the implications of this for the inflexible, literal/immediate, and inappropriate information processing of autistic individuals. PMID:22937255

Extraction of the respiratory signal from small-animal CT projections for a retrospective gating method

NASA Astrophysics Data System (ADS)

Chavarrías, C.; Vaquero, J. J.; Sisniega, A.; Rodríguez-Ruano, A.; Soto-Montenegro, M. L.; García-Barreno, P.; Desco, M.

2008-09-01

We propose a retrospective respiratory gating algorithm to generate dynamic CT studies. To this end, we compared three different methods of extracting the respiratory signal from the projections of small-animal cone-beam computed tomography (CBCT) scanners. Given a set of frames acquired from a certain axial angle, subtraction of their average image from each individual frame produces a set of difference images. Pixels in these images have positive or negative values (according to the respiratory phase) in those areas where there is lung movement. The respiratory signals were extracted by analysing the shape of the histogram of these difference images: we calculated the first four central and non-central moments. However, only odd-order moments produced the desired breathing signal, as the even-order moments lacked information about the phase. Each of these curves was compared to a reference signal recorded by means of a pneumatic pillow. Given the similar correlation coefficients yielded by all of them, we selected the mean to implement our retrospective protocol. Respiratory phase bins were separated, reconstructed independently and included in a dynamic sequence, suitable for cine playback. We validated our method in five adult rat studies by comparing profiles drawn across the diaphragm dome, with and without retrospective respiratory gating. Results showed a sharper transition in the gated reconstruction, with an average slope improvement of 60.7%.

Mode extraction on wind turbine blades via phase-based video motion estimation

NASA Astrophysics Data System (ADS)

Sarrafi, Aral; Poozesh, Peyman; Niezrecki, Christopher; Mao, Zhu

2017-04-01

In recent years, image processing techniques are being applied more often for structural dynamics identification, characterization, and structural health monitoring. Although as a non-contact and full-field measurement method, image processing still has a long way to go to outperform other conventional sensing instruments (i.e. accelerometers, strain gauges, laser vibrometers, etc.,). However, the technologies associated with image processing are developing rapidly and gaining more attention in a variety of engineering applications including structural dynamics identification and modal analysis. Among numerous motion estimation and image-processing methods, phase-based video motion estimation is considered as one of the most efficient methods regarding computation consumption and noise robustness. In this paper, phase-based video motion estimation is adopted for structural dynamics characterization on a 2.3-meter long Skystream wind turbine blade, and the modal parameters (natural frequencies, operating deflection shapes) are extracted. Phase-based video processing adopted in this paper provides reliable full-field 2-D motion information, which is beneficial for manufacturing certification and model updating at the design stage. The phase-based video motion estimation approach is demonstrated through processing data on a full-scale commercial structure (i.e. a wind turbine blade) with complex geometry and properties, and the results obtained have a good correlation with the modal parameters extracted from accelerometer measurements, especially for the first four bending modes, which have significant importance in blade characterization.

Light-extraction enhancement for light-emitting diodes: a firefly-inspired structure refined by the genetic algorithm

NASA Astrophysics Data System (ADS)

Bay, Annick; Mayer, Alexandre

2014-09-01

The efficiency of light-emitting diodes (LED) has increased significantly over the past few years, but the overall efficiency is still limited by total internal reflections due to the high dielectric-constant contrast between the incident and emergent media. The bioluminescent organ of fireflies gave incentive for light-extraction enhance-ment studies. A specific factory-roof shaped structure was shown, by means of light-propagation simulations and measurements, to enhance light extraction significantly. In order to achieve a similar effect for light-emitting diodes, the structure needs to be adapted to the specific set-up of LEDs. In this context simulations were carried out to determine the best geometrical parameters. In the present work, the search for a geometry that maximizes the extraction of light has been conducted by using a genetic algorithm. The idealized structure considered previously was generalized to a broader variety of shapes. The genetic algorithm makes it possible to search simultaneously over a wider range of parameters. It is also significantly less time-consuming than the previous approach that was based on a systematic scan on parameters. The results of the genetic algorithm show that (1) the calculations can be performed in a smaller amount of time and (2) the light extraction can be enhanced even more significantly by using optimal parameters determined by the genetic algorithm for the generalized structure. The combination of the genetic algorithm with the Rigorous Coupled Waves Analysis method constitutes a strong simulation tool, which provides us with adapted designs for enhancing light extraction from light-emitting diodes.

Prediction of individual brain maturity using fMRI.

PubMed

Dosenbach, Nico U F; Nardos, Binyam; Cohen, Alexander L; Fair, Damien A; Power, Jonathan D; Church, Jessica A; Nelson, Steven M; Wig, Gagan S; Vogel, Alecia C; Lessov-Schlaggar, Christina N; Barnes, Kelly Anne; Dubis, Joseph W; Feczko, Eric; Coalson, Rebecca S; Pruett, John R; Barch, Deanna M; Petersen, Steven E; Schlaggar, Bradley L

2010-09-10

Group functional connectivity magnetic resonance imaging (fcMRI) studies have documented reliable changes in human functional brain maturity over development. Here we show that support vector machine-based multivariate pattern analysis extracts sufficient information from fcMRI data to make accurate predictions about individuals' brain maturity across development. The use of only 5 minutes of resting-state fcMRI data from 238 scans of typically developing volunteers (ages 7 to 30 years) allowed prediction of individual brain maturity as a functional connectivity maturation index. The resultant functional maturation curve accounted for 55% of the sample variance and followed a nonlinear asymptotic growth curve shape. The greatest relative contribution to predicting individual brain maturity was made by the weakening of short-range functional connections between the adult brain's major functional networks.

Waveform shape analysis: extraction of physiologically relevant information from Doppler recordings.

PubMed

Ramsay, M M; Broughton Pipkin, F; Rubin, P C; Skidmore, R

1994-05-01

1. Doppler recordings were made from the brachial artery of healthy female subjects during a series of manoeuvres which altered the pressure-flow characteristics of the vessel. 2. Changes were induced in the peripheral circulation of the forearm by the application of heat or ice-packs. A sphygmomanometer cuff was used to create graded occlusion of the vessel above and below the point of measurement. Recordings were also made whilst the subjects performed a standardized Valsalva manoeuvre. 3. The Doppler recordings were analysed both with the standard waveform indices (systolic/diastolic ratio, pulsatility index and resistance index) and by the method of Laplace transform analysis. 4. The waveform parameters obtained by Laplace transform analysis distinguished the different changes in flow conditions; they thus had direct physiological relevance, unlike the standard waveform indices.

Estimation of Operating Condition of Appliances Using Circuit Current Data on Electric Distribution Boards

NASA Astrophysics Data System (ADS)

Iwafune, Yumiko; Ogimoto, Kazuhiko; Yagita, Yoshie

The Energy management systems (EMS) on demand sides are expected as a method to enhance the capability of supply and demand balancing of a power system under the anticipated penetration of renewable energy generation such as Photovoltaics (PV). Elucidation of energy consumption structure in a building is one of important elements for realization of EMS and contributes to the extraction of potential energy saving. In this paper, we propose the estimation method of operating condition of household appliances using circuit current data on an electric distribution board. Circuit current data are broken down by their shape using a self-organization map method and aggregated by appliance based on customers' information of appliance possessed. Proposed method is verified using residential energy consumption measurement survey data.

A novel shape-changing haptic table-top display

NASA Astrophysics Data System (ADS)

Wang, Jiabin; Zhao, Lu; Liu, Yue; Wang, Yongtian; Cai, Yi

2018-01-01

A shape-changing table-top display with haptic feedback allows its users to perceive 3D visual and texture displays interactively. Since few existing devices are developed as accurate displays with regulatory haptic feedback, a novel attentive and immersive shape changing mechanical interface (SCMI) consisting of image processing unit and transformation unit was proposed in this paper. In order to support a precise 3D table-top display with an offset of less than 2 mm, a custommade mechanism was developed to form precise surface and regulate the feedback force. The proposed image processing unit was capable of extracting texture data from 2D picture for rendering shape-changing surface and realizing 3D modeling. The preliminary evaluation result proved the feasibility of the proposed system.

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

Ginsz, M.; Duchene, G.; Didierjean, F.

The state-of-the art gamma-ray spectrometers such as AGATA and GRETA are using position sensitive multi-segmented HPGe crystals. Pulse-shape analysis (PSA) allows to retrieve the localisation of the gamma interactions and to perform gamma-ray tracking within germanium. The precision of the localisation depends on the quality of the pulse-shape database used for comparison. The IPHC laboratory developed a new fast scanning table allowing to measure experimental pulse shapes in the whole volume of any crystal. The results of the scan of an AGATA 36-fold segmented tapered coaxial detector are shown here, 48580 experimental pulse shapes are extracted within 2 weeks ofmore » scanning. These data will contribute to AGATA PSA performances, but have also applications for gamma cameras or Compton-suppressed detectors. (authors)« less

Computational fluid dynamics simulation of airflow in the trachea and main bronchi for the subjects with left pulmonary artery sling

PubMed Central

2014-01-01

Background Left pulmonary artery sling (LPAS) is a rare but severe congenital anomaly, in which the stenoses are formed in the trachea and/or main bronchi. Multi-detector computed tomography (MDCT) provides useful anatomical images, but does not offer functional information. The objective of the present study is to quantitatively analyze the airflow in the trachea and main bronchi of LPAS subjects through computational fluid dynamics (CFD) simulation. Methods Five subjects (four LPAS patients, one normal control) aging 6-19 months are analyzed. The geometric model of the trachea and the two main bronchi is extracted from the MDCT images. The inlet velocity is determined based on the body weight and the inlet area. Both the geometric model and personalized inflow conditions are imported into CFD software, ANSYS. The pressure drop, mass flow ratio through two bronchi, wall pressure, flow velocity and wall shear stress (WSS) are obtained, and compared to the normal control. Results Due to the tracheal and/or bronchial stenosis, the pressure drop for the LPAS patients ranges 78.9 - 914.5 Pa, much higher than for the normal control (0.7 Pa). The mass flow ratio through the two bronchi does not correlate with the sectional area ratio if the anomalous left pulmonary artery compresses the trachea or bronchi. It is suggested that the C-shaped trachea plays an important role on facilitating the air flow into the left bronchus with the inertia force. For LPAS subjects, the distributions of velocities, wall pressure and WSS are less regular than for the normal control. At the stenotic site, high velocity, low wall pressure and high WSS are observed. Conclusions Using geometric models extracted from CT images and the patient-specified inlet boundary conditions, CFD simulation can provide vital quantitative flow information for LPAS. Due to the stenosis, high pressure drops, inconsistent distributions of velocities, wall pressure and WSS are observed. The C-shaped trachea may facilitate a larger flow of air into the left bronchus under the inertial force, and decrease the ventilation of the right lung. Quantitative and personalized information may help understand the mechanism of LPAS and the correlations between stenosis and dyspnea, and facilitate the structural and functional assessment of LPAS. PMID:24957947

Identifying the Critical Time Period for Information Extraction when Recognizing Sequences of Play

ERIC Educational Resources Information Center

North, Jamie S.; Williams, A. Mark

2008-01-01

The authors attempted to determine the critical time period for information extraction when recognizing play sequences in soccer. Although efforts have been made to identify the perceptual information underpinning such decisions, no researchers have attempted to determine "when" this information may be extracted from the display. The authors…

Can we replace curation with information extraction software?

PubMed

Karp, Peter D

2016-01-01

Can we use programs for automated or semi-automated information extraction from scientific texts as practical alternatives to professional curation? I show that error rates of current information extraction programs are too high to replace professional curation today. Furthermore, current IEP programs extract single narrow slivers of information, such as individual protein interactions; they cannot extract the large breadth of information extracted by professional curators for databases such as EcoCyc. They also cannot arbitrate among conflicting statements in the literature as curators can. Therefore, funding agencies should not hobble the curation efforts of existing databases on the assumption that a problem that has stymied Artificial Intelligence researchers for more than 60 years will be solved tomorrow. Semi-automated extraction techniques appear to have significantly more potential based on a review of recent tools that enhance curator productivity. But a full cost-benefit analysis for these tools is lacking. Without such analysis it is possible to expend significant effort developing information-extraction tools that automate small parts of the overall curation workflow without achieving a significant decrease in curation costs.Database URL. © The Author(s) 2016. Published by Oxford University Press.

Recognizing an individual face: 3D shape contributes earlier than 2D surface reflectance information.

PubMed

Caharel, Stéphanie; Jiang, Fang; Blanz, Volker; Rossion, Bruno

2009-10-01

The human brain recognizes faces by means of two main diagnostic sources of information: three-dimensional (3D) shape and two-dimensional (2D) surface reflectance. Here we used event-related potentials (ERPs) in a face adaptation paradigm to examine the time-course of processing for these two types of information. With a 3D morphable model, we generated pairs of faces that were either identical, varied in 3D shape only, in 2D surface reflectance only, or in both. Sixteen human observers discriminated individual faces in these 4 types of pairs, in which a first (adapting) face was followed shortly by a second (test) face. Behaviorally, observers were as accurate and as fast for discriminating individual faces based on either 3D shape or 2D surface reflectance alone, but were faster when both sources of information were present. As early as the face-sensitive N170 component (approximately 160 ms following the test face), there was larger amplitude for changes in 3D shape relative to the repetition of the same face, especially over the right occipito-temporal electrodes. However, changes in 2D reflectance between the adapter and target face did not increase the N170 amplitude. At about 250 ms, both 3D shape and 2D reflectance contributed equally, and the largest difference in amplitude compared to the repetition of the same face was found when both 3D shape and 2D reflectance were combined, in line with observers' behavior. These observations indicate that evidence to recognize individual faces accumulate faster in the right hemisphere human visual cortex from diagnostic 3D shape information than from 2D surface reflectance information.

Corrected Integral Shape Averaging Applied to Obstructive Sleep Apnea Detection from the Electrocardiogram

NASA Astrophysics Data System (ADS)

Boudaoud, S.; Rix, H.; Meste, O.; Heneghan, C.; O'Brien, C.

2007-12-01

We present a technique called corrected integral shape averaging (CISA) for quantifying shape and shape differences in a set of signals. CISA can be used to account for signal differences which are purely due to affine time warping (jitter and dilation/compression), and hence provide access to intrinsic shape fluctuations. CISA can also be used to define a distance between shapes which has useful mathematical properties; a mean shape signal for a set of signals can be defined, which minimizes the sum of squared shape distances of the set from the mean. The CISA procedure also allows joint estimation of the affine time parameters. Numerical simulations are presented to support the algorithm for obtaining the CISA mean and parameters. Since CISA provides a well-defined shape distance, it can be used in shape clustering applications based on distance measures such as[InlineEquation not available: see fulltext.]-means. We present an application in which CISA shape clustering is applied to P-waves extracted from the electrocardiogram of subjects suffering from sleep apnea. The resulting shape clustering distinguishes ECG segments recorded during apnea from those recorded during normal breathing with a sensitivity of[InlineEquation not available: see fulltext.] and specificity of[InlineEquation not available: see fulltext.].

Combining color and shape information for illumination-viewpoint invariant object recognition.

PubMed

Diplaros, Aristeidis; Gevers, Theo; Patras, Ioannis

2006-01-01

In this paper, we propose a new scheme that merges color- and shape-invariant information for object recognition. To obtain robustness against photometric changes, color-invariant derivatives are computed first. Color invariance is an important aspect of any object recognition scheme, as color changes considerably with the variation in illumination, object pose, and camera viewpoint. These color invariant derivatives are then used to obtain similarity invariant shape descriptors. Shape invariance is equally important as, under a change in camera viewpoint and object pose, the shape of a rigid object undergoes a perspective projection on the image plane. Then, the color and shape invariants are combined in a multidimensional color-shape context which is subsequently used as an index. As the indexing scheme makes use of a color-shape invariant context, it provides a high-discriminative information cue robust against varying imaging conditions. The matching function of the color-shape context allows for fast recognition, even in the presence of object occlusion and cluttering. From the experimental results, it is shown that the method recognizes rigid objects with high accuracy in 3-D complex scenes and is robust against changing illumination, camera viewpoint, object pose, and noise.