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Sample records for 3d feature extraction

  1. 3D Feature Extraction for Unstructured Grids

    NASA Technical Reports Server (NTRS)

    Silver, Deborah

    1996-01-01

    Visualization techniques provide tools that help scientists identify observed phenomena in scientific simulation. To be useful, these tools must allow the user to extract regions, classify and visualize them, abstract them for simplified representations, and track their evolution. Object Segmentation provides a technique to extract and quantify regions of interest within these massive datasets. This article explores basic algorithms to extract coherent amorphous regions from two-dimensional and three-dimensional scalar unstructured grids. The techniques are applied to datasets from Computational Fluid Dynamics and those from Finite Element Analysis.

  2. Feature edge extraction from 3D triangular meshes using a thinning algorithm

    NASA Astrophysics Data System (ADS)

    Nomura, Masaru; Hamada, Nozomu

    2001-11-01

    Highly detailed geometric models, which are represented as dense triangular meshes are becoming popular in computer graphics. Since such 3D meshes often have huge information, we require some methods to treat them efficiently in the 3D mesh processing such as, surface simplification, subdivision surface, curved surface approximation and morphing. In these applications, we often extract features of 3D meshes such as feature vertices and feature edges in preprocessing step. An automatic extraction method of feature edges is treated in this study. In order to realize the feature edge extraction method, we first introduce the concavity and convexity evaluation value. Then the histogram of the concavity and convexity evaluation value is used to separate the feature edge region. We apply a thinning algorithm, which is used in 2D binary image processing. It is shown that the proposed method can extract appropriate feature edges from 3D meshes.

  3. Edge features extraction from 3D laser point cloud based on corresponding images

    NASA Astrophysics Data System (ADS)

    Li, Xin-feng; Zhao, Zi-ming; Xu, Guo-qing; Geng, Yan-long

    2013-09-01

    An extraction method of edge features from 3D laser point cloud based on corresponding images was proposed. After the registration of point cloud and corresponding image, the sub-pixel edge can be extracted from the image using gray moment algorithm. Then project the sub-pixel edge to the point cloud in fitting scan-lines. At last the edge features were achieved by linking the crossing points. The experimental results demonstrate that the method guarantees accurate fine extraction.

  4. Airborne LIDAR and high resolution satellite data for rapid 3D feature extraction

    NASA Astrophysics Data System (ADS)

    Jawak, S. D.; Panditrao, S. N.; Luis, A. J.

    2014-11-01

    This work uses the canopy height model (CHM) based workflow for individual tree crown delineation and 3D feature extraction approach (Overwatch Geospatial's proprietary algorithm) for building feature delineation from high-density light detection and ranging (LiDAR) point cloud data in an urban environment and evaluates its accuracy by using very high-resolution panchromatic (PAN) (spatial) and 8-band (multispectral) WorldView-2 (WV-2) imagery. LiDAR point cloud data over San Francisco, California, USA, recorded in June 2010, was used to detect tree and building features by classifying point elevation values. The workflow employed includes resampling of LiDAR point cloud to generate a raster surface or digital terrain model (DTM), generation of a hill-shade image and an intensity image, extraction of digital surface model, generation of bare earth digital elevation model (DEM) and extraction of tree and building features. First, the optical WV-2 data and the LiDAR intensity image were co-registered using ground control points (GCPs). The WV-2 rational polynomial coefficients model (RPC) was executed in ERDAS Leica Photogrammetry Suite (LPS) using supplementary *.RPB file. In the second stage, ortho-rectification was carried out using ERDAS LPS by incorporating well-distributed GCPs. The root mean square error (RMSE) for the WV-2 was estimated to be 0.25 m by using more than 10 well-distributed GCPs. In the second stage, we generated the bare earth DEM from LiDAR point cloud data. In most of the cases, bare earth DEM does not represent true ground elevation. Hence, the model was edited to get the most accurate DEM/ DTM possible and normalized the LiDAR point cloud data based on DTM in order to reduce the effect of undulating terrain. We normalized the vegetation point cloud values by subtracting the ground points (DEM) from the LiDAR point cloud. A normalized digital surface model (nDSM) or CHM was calculated from the LiDAR data by subtracting the DEM from the DSM

  5. Airborne LIDAR and high resolution satellite data for rapid 3D feature extraction

    NASA Astrophysics Data System (ADS)

    Jawak, S. D.; Panditrao, S. N.; Luis, A. J.

    2014-11-01

    This work uses the canopy height model (CHM) based workflow for individual tree crown delineation and 3D feature extraction approach (Overwatch Geospatial's proprietary algorithm) for building feature delineation from high-density light detection and ranging (LiDAR) point cloud data in an urban environment and evaluates its accuracy by using very high-resolution panchromatic (PAN) (spatial) and 8-band (multispectral) WorldView-2 (WV-2) imagery. LiDAR point cloud data over San Francisco, California, USA, recorded in June 2010, was used to detect tree and building features by classifying point elevation values. The workflow employed includes resampling of LiDAR point cloud to generate a raster surface or digital terrain model (DTM), generation of a hill-shade image and an intensity image, extraction of digital surface model, generation of bare earth digital elevation model (DEM) and extraction of tree and building features. First, the optical WV-2 data and the LiDAR intensity image were co-registered using ground control points (GCPs). The WV-2 rational polynomial coefficients model (RPC) was executed in ERDAS Leica Photogrammetry Suite (LPS) using supplementary *.RPB file. In the second stage, ortho-rectification was carried out using ERDAS LPS by incorporating well-distributed GCPs. The root mean square error (RMSE) for the WV-2 was estimated to be 0.25 m by using more than 10 well-distributed GCPs. In the second stage, we generated the bare earth DEM from LiDAR point cloud data. In most of the cases, bare earth DEM does not represent true ground elevation. Hence, the model was edited to get the most accurate DEM/ DTM possible and normalized the LiDAR point cloud data based on DTM in order to reduce the effect of undulating terrain. We normalized the vegetation point cloud values by subtracting the ground points (DEM) from the LiDAR point cloud. A normalized digital surface model (nDSM) or CHM was calculated from the LiDAR data by subtracting the DEM from the DSM

  6. Bispectrum feature extraction of gearbox faults based on nonnegative Tucker3 decomposition with 3D calculations

    NASA Astrophysics Data System (ADS)

    Wang, Haijun; Xu, Feiyun; Zhao, Jun'ai; Jia, Minping; Hu, Jianzhong; Huang, Peng

    2013-11-01

    Nonnegative Tucker3 decomposition(NTD) has attracted lots of attentions for its good performance in 3D data array analysis. However, further research is still necessary to solve the problems of overfitting and slow convergence under the anharmonic vibration circumstance occurred in the field of mechanical fault diagnosis. To decompose a large-scale tensor and extract available bispectrum feature, a method of conjugating Choi-Williams kernel function with Gauss-Newton Cartesian product based on nonnegative Tucker3 decomposition(NTD_EDF) is investigated. The complexity of the proposed method is reduced from o( n N lg n) in 3D spaces to o( R 1 R 2 nlg n) in 1D vectors due to its low rank form of the Tucker-product convolution. Meanwhile, a simultaneously updating algorithm is given to overcome the overfitting, slow convergence and low efficiency existing in the conventional one-by-one updating algorithm. Furthermore, the technique of spectral phase analysis for quadratic coupling estimation is used to explain the feature spectrum extracted from the gearbox fault data by the proposed method in detail. The simulated and experimental results show that the sparser and more inerratic feature distribution of basis images can be obtained with core tensor by the NTD_EDF method compared with the one by the other methods in bispectrum feature extraction, and a legible fault expression can also be performed by power spectral density(PSD) function. Besides, the deviations of successive relative error(DSRE) of NTD_EDF achieves 81.66 dB against 15.17 dB by beta-divergences based on NTD(NTD_Beta) and the time-cost of NTD_EDF is only 129.3 s, which is far less than 1 747.9 s by hierarchical alternative least square based on NTD (NTD_HALS). The NTD_EDF method proposed not only avoids the data overfitting and improves the computation efficiency but also can be used to extract more inerratic and sparser bispectrum features of the gearbox fault.

  7. Multi-resolution Gabor wavelet feature extraction for needle detection in 3D ultrasound

    NASA Astrophysics Data System (ADS)

    Pourtaherian, Arash; Zinger, Svitlana; Mihajlovic, Nenad; de With, Peter H. N.; Huang, Jinfeng; Ng, Gary C.; Korsten, Hendrikus H. M.

    2015-12-01

    Ultrasound imaging is employed for needle guidance in various minimally invasive procedures such as biopsy guidance, regional anesthesia and brachytherapy. Unfortunately, a needle guidance using 2D ultrasound is very challenging, due to a poor needle visibility and a limited field of view. Nowadays, 3D ultrasound systems are available and more widely used. Consequently, with an appropriate 3D image-based needle detection technique, needle guidance and interventions may significantly be improved and simplified. In this paper, we present a multi-resolution Gabor transformation for an automated and reliable extraction of the needle-like structures in a 3D ultrasound volume. We study and identify the best combination of the Gabor wavelet frequencies. High precision in detecting the needle voxels leads to a robust and accurate localization of the needle for the intervention support. Evaluation in several ex-vivo cases shows that the multi-resolution analysis significantly improves the precision of the needle voxel detection from 0.23 to 0.32 at a high recall rate of 0.75 (gain 40%), where a better robustness and confidence were confirmed in the practical experiments.

  8. Geometric and topological feature extraction of linear segments from 2D cross-section data of 3D point clouds

    NASA Astrophysics Data System (ADS)

    Ramamurthy, Rajesh; Harding, Kevin; Du, Xiaoming; Lucas, Vincent; Liao, Yi; Paul, Ratnadeep; Jia, Tao

    2015-05-01

    Optical measurement techniques are often employed to digitally capture three dimensional shapes of components. The digital data density output from these probes range from a few discrete points to exceeding millions of points in the point cloud. The point cloud taken as a whole represents a discretized measurement of the actual 3D shape of the surface of the component inspected to the measurement resolution of the sensor. Embedded within the measurement are the various features of the part that make up its overall shape. Part designers are often interested in the feature information since those relate directly to part function and to the analytical models used to develop the part design. Furthermore, tolerances are added to these dimensional features, making their extraction a requirement for the manufacturing quality plan of the product. The task of "extracting" these design features from the point cloud is a post processing task. Due to measurement repeatability and cycle time requirements often automated feature extraction from measurement data is required. The presence of non-ideal features such as high frequency optical noise and surface roughness can significantly complicate this feature extraction process. This research describes a robust process for extracting linear and arc segments from general 2D point clouds, to a prescribed tolerance. The feature extraction process generates the topology, specifically the number of linear and arc segments, and the geometry equations of the linear and arc segments automatically from the input 2D point clouds. This general feature extraction methodology has been employed as an integral part of the automated post processing algorithms of 3D data of fine features.

  9. Topology-based Simplification for Feature Extraction from 3D Scalar Fields

    SciTech Connect

    Gyulassy, A; Natarajan, V; Pascucci, V; Bremer, P; Hamann, B

    2005-10-13

    This paper describes a topological approach for simplifying continuous functions defined on volumetric domains. We present a combinatorial algorithm that simplifies the Morse-Smale complex by repeated application of two atomic operations that removes pairs of critical points. The Morse-Smale complex is a topological data structure that provides a compact representation of gradient flows between critical points of a function. Critical points paired by the Morse-Smale complex identify topological features and their importance. The simplification procedure leaves important critical points untouched, and is therefore useful for extracting desirable features. We also present a visualization of the simplified topology.

  10. Classification of Informal Settlements Through the Integration of 2d and 3d Features Extracted from Uav Data

    NASA Astrophysics Data System (ADS)

    Gevaert, C. M.; Persello, C.; Sliuzas, R.; Vosselman, G.

    2016-06-01

    Unmanned Aerial Vehicles (UAVs) are capable of providing very high resolution and up-to-date information to support informal settlement upgrading projects. In order to provide accurate basemaps, urban scene understanding through the identification and classification of buildings and terrain is imperative. However, common characteristics of informal settlements such as small, irregular buildings with heterogeneous roof material and large presence of clutter challenge state-of-the-art algorithms. Especially the dense buildings and steeply sloped terrain cause difficulties in identifying elevated objects. This work investigates how 2D radiometric and textural features, 2.5D topographic features, and 3D geometric features obtained from UAV imagery can be integrated to obtain a high classification accuracy in challenging classification problems for the analysis of informal settlements. It compares the utility of pixel-based and segment-based features obtained from an orthomosaic and DSM with point-based and segment-based features extracted from the point cloud to classify an unplanned settlement in Kigali, Rwanda. Findings show that the integration of 2D and 3D features leads to higher classification accuracies.

  11. Feature extraction algorithm for 3D scene modeling and visualization using monostatic SAR

    NASA Astrophysics Data System (ADS)

    Jackson, Julie A.; Moses, Randolph L.

    2006-05-01

    We present a feature extraction algorithm to detect scattering centers in three dimensions using monostatic synthetic aperture radar imagery. We develop attributed scattering center models that describe the radar response of canonical shapes. We employ these models to characterize a complex target geometry as a superposition of simpler, low-dimensional structures. Such a characterization provides a means for target visualization. Fitting an attributed scattering model to sensed radar data is comprised of two problems: detection and estimation. The detection problem is to find canonical targets in clutter. The estimation problem then fits the detected canonical shape model with parameters, such as size and orientation, that correspond to the measured target response. We present an algorithm to detect canonical scattering structures amidst clutter and to estimate the corresponding model parameters. We employ full-polarimetric imagery to accurately classify canonical shapes. Interformetric processing allows us to estimate scattering center locations in three-dimensions. We apply the algorithm to scattering prediction data of a simple scene comprised of canonical scatterers and to scattering predictions of a backhoe.

  12. Automatic segmentation and 3D feature extraction of protein aggregates in Caenorhabditis elegans

    NASA Astrophysics Data System (ADS)

    Rodrigues, Pedro L.; Moreira, António H. J.; Teixeira-Castro, Andreia; Oliveira, João; Dias, Nuno; Rodrigues, Nuno F.; Vilaça, João L.

    2012-03-01

    In the last years, it has become increasingly clear that neurodegenerative diseases involve protein aggregation, a process often used as disease progression readout and to develop therapeutic strategies. This work presents an image processing tool to automatic segment, classify and quantify these aggregates and the whole 3D body of the nematode Caenorhabditis Elegans. A total of 150 data set images, containing different slices, were captured with a confocal microscope from animals of distinct genetic conditions. Because of the animals' transparency, most of the slices pixels appeared dark, hampering their body volume direct reconstruction. Therefore, for each data set, all slices were stacked in one single 2D image in order to determine a volume approximation. The gradient of this image was input to an anisotropic diffusion algorithm that uses the Tukey's biweight as edge-stopping function. The image histogram median of this outcome was used to dynamically determine a thresholding level, which allows the determination of a smoothed exterior contour of the worm and the medial axis of the worm body from thinning its skeleton. Based on this exterior contour diameter and the medial animal axis, random 3D points were then calculated to produce a volume mesh approximation. The protein aggregations were subsequently segmented based on an iso-value and blended with the resulting volume mesh. The results obtained were consistent with qualitative observations in literature, allowing non-biased, reliable and high throughput protein aggregates quantification. This may lead to a significant improvement on neurodegenerative diseases treatment planning and interventions prevention.

  13. Summary of work on shock wave feature extraction in 3-D datasets

    NASA Technical Reports Server (NTRS)

    Hesselink, Lambertus (Principal Investigator)

    1996-01-01

    A method for extracting and visualizing shock waves from three dimensional data-sets is discussed. Issues concerning computation time, robustness to numerical perturbations, and noise introduction are considered and compared with other methods. Finally, results using this method are discussed.

  14. 3D Object Recognition using Gabor Feature Extraction and PCA-FLD Projections of Holographically Sensed Data

    NASA Astrophysics Data System (ADS)

    Yeom, Seokwon; Javidi, Bahram

    In this research, a 3D object classification technique using a single hologram has been presented. The PCA-FLD classifier with feature vectors based on Gabor wavelets has been utilized for this purpose. Training and test data of the 3D objects were obtained by computational holographic imaging. We were able to classify 3D objects used in the experiments with a few reconstructed planes of the hologram. The Gabor approach appears to be a good feature extractor for hologram-based 3D classification. The FLD combined with the PCA proved to be a very efficient classifier even with a few training data. Substantial dimensionality reduction was achieved by using the proposed technique for 3D classification problem using holographic imaging. As a consequence, we were able to classify different classes of 3D objects using computer-reconstructed holographic images.

  15. Automatic 3D segmentation of the kidney in MR images using wavelet feature extraction and probability shape model

    NASA Astrophysics Data System (ADS)

    Akbari, Hamed; Fei, Baowei

    2012-02-01

    Numerical estimation of the size of the kidney is useful in evaluating conditions of the kidney, especially, when serial MR imaging is performed to evaluate the kidney function. This paper presents a new method for automatic segmentation of the kidney in three-dimensional (3D) MR images, by extracting texture features and statistical matching of geometrical shape of the kidney. A set of Wavelet-based support vector machines (W-SVMs) is trained on the MR images. The W-SVMs capture texture priors of MRI for classification of the kidney and non-kidney tissues in different zones around the kidney boundary. In the segmentation procedure, these W-SVMs are trained to tentatively label each voxel around the kidney model as a kidney or non-kidney voxel by texture matching. A probability kidney model is created using 10 segmented MRI data. The model is initially localized based on the intensity profiles in three directions. The weight functions are defined for each labeled voxel for each Wavelet-based, intensity-based, and model-based label. Consequently, each voxel has three labels and three weights for the Wavelet feature, intensity, and probability model. Using a 3D edge detection method, the model is re-localized and the segmented kidney is modified based on a region growing method in the model region. The probability model is re-localized based on the results and this loop continues until the segmentation converges. Experimental results with mouse MRI data show the good performance of the proposed method in segmenting the kidney in MR images.

  16. 3D Buildings Extraction from Aerial Images

    NASA Astrophysics Data System (ADS)

    Melnikova, O.; Prandi, F.

    2011-09-01

    This paper introduces a semi-automatic method for buildings extraction through multiple-view aerial image analysis. The advantage of the used semi-automatic approach is that it allows processing of each building individually finding the parameters of buildings features extraction more precisely for each area. On the early stage the presented technique uses an extraction of line segments that is done only inside of areas specified manually. The rooftop hypothesis is used further to determine a subset of quadrangles, which could form building roofs from a set of extracted lines and corners obtained on the previous stage. After collecting of all potential roof shapes in all images overlaps, the epipolar geometry is applied to find matching between images. This allows to make an accurate selection of building roofs removing false-positive ones and to identify their global 3D coordinates given camera internal parameters and coordinates. The last step of the image matching is based on geometrical constraints in contrast to traditional correlation. The correlation is applied only in some highly restricted areas in order to find coordinates more precisely, in such a way significantly reducing processing time of the algorithm. The algorithm has been tested on a set of Milan's aerial images and shows highly accurate results.

  17. Learning the spherical harmonic features for 3-D face recognition.

    PubMed

    Liu, Peijiang; Wang, Yunhong; Huang, Di; Zhang, Zhaoxiang; Chen, Liming

    2013-03-01

    In this paper, a competitive method for 3-D face recognition (FR) using spherical harmonic features (SHF) is proposed. With this solution, 3-D face models are characterized by the energies contained in spherical harmonics with different frequencies, thereby enabling the capture of both gross shape and fine surface details of a 3-D facial surface. This is in clear contrast to most 3-D FR techniques which are either holistic or feature based, using local features extracted from distinctive points. First, 3-D face models are represented in a canonical representation, namely, spherical depth map, by which SHF can be calculated. Then, considering the predictive contribution of each SHF feature, especially in the presence of facial expression and occlusion, feature selection methods are used to improve the predictive performance and provide faster and more cost-effective predictors. Experiments have been carried out on three public 3-D face datasets, SHREC2007, FRGC v2.0, and Bosphorus, with increasing difficulties in terms of facial expression, pose, and occlusion, and which demonstrate the effectiveness of the proposed method. PMID:23060332

  18. Automated Recognition of 3D Features in GPIR Images

    NASA Technical Reports Server (NTRS)

    Park, Han; Stough, Timothy; Fijany, Amir

    2007-01-01

    A method of automated recognition of three-dimensional (3D) features in images generated by ground-penetrating imaging radar (GPIR) is undergoing development. GPIR 3D images can be analyzed to detect and identify such subsurface features as pipes and other utility conduits. Until now, much of the analysis of GPIR images has been performed manually by expert operators who must visually identify and track each feature. The present method is intended to satisfy a need for more efficient and accurate analysis by means of algorithms that can automatically identify and track subsurface features, with minimal supervision by human operators. In this method, data from multiple sources (for example, data on different features extracted by different algorithms) are fused together for identifying subsurface objects. The algorithms of this method can be classified in several different ways. In one classification, the algorithms fall into three classes: (1) image-processing algorithms, (2) feature- extraction algorithms, and (3) a multiaxis data-fusion/pattern-recognition algorithm that includes a combination of machine-learning, pattern-recognition, and object-linking algorithms. The image-processing class includes preprocessing algorithms for reducing noise and enhancing target features for pattern recognition. The feature-extraction algorithms operate on preprocessed data to extract such specific features in images as two-dimensional (2D) slices of a pipe. Then the multiaxis data-fusion/ pattern-recognition algorithm identifies, classifies, and reconstructs 3D objects from the extracted features. In this process, multiple 2D features extracted by use of different algorithms and representing views along different directions are used to identify and reconstruct 3D objects. In object linking, which is an essential part of this process, features identified in successive 2D slices and located within a threshold radius of identical features in adjacent slices are linked in a

  19. Feature-Based Quality Evaluation of 3d Point Clouds - Study of the Performance of 3d Registration Algorithms

    NASA Astrophysics Data System (ADS)

    Ridene, T.; Goulette, F.; Chendeb, S.

    2013-08-01

    The production of realistic 3D map databases is continuously growing. We studied an approach of 3D mapping database producing based on the fusion of heterogeneous 3D data. In this term, a rigid registration process was performed. Before starting the modeling process, we need to validate the quality of the registration results, and this is one of the most difficult and open research problems. In this paper, we suggest a new method of evaluation of 3D point clouds based on feature extraction and comparison with a 2D reference model. This method is based on tow metrics: binary and fuzzy.

  20. Feature detection on 3D images of dental imprints

    NASA Astrophysics Data System (ADS)

    Mokhtari, Marielle; Laurendeau, Denis

    1994-09-01

    A computer vision approach for the extraction of feature points on 3D images of dental imprints is presented. The position of feature points are needed for the measurement of a set of parameters for automatic diagnosis of malocclusion problems in orthodontics. The system for the acquisition of the 3D profile of the imprint, the procedure for the detection of the interstices between teeth, and the approach for the identification of the type of tooth are described, as well as the algorithm for the reconstruction of the surface of each type of tooth. A new approach for the detection of feature points, called the watershed algorithm, is described in detail. The algorithm is a two-stage procedure which tracks the position of local minima at four different scales and produces a final map of the position of the minima. Experimental results of the application of the watershed algorithm on actual 3D images of dental imprints are presented for molars, premolars and canines. The segmentation approach for the analysis of the shape of incisors is also described in detail.

  1. THE THOMSON SURFACE. III. TRACKING FEATURES IN 3D

    SciTech Connect

    Howard, T. A.; DeForest, C. E.; Tappin, S. J.; Odstrcil, D.

    2013-03-01

    In this, the final installment in a three-part series on the Thomson surface, we present simulated observations of coronal mass ejections (CMEs) observed by a hypothetical polarizing white light heliospheric imager. Thomson scattering yields a polarization signal that can be exploited to locate observed features in three dimensions relative to the Thomson surface. We consider how the appearance of the CME changes with the direction of trajectory, using simulations of a simple geometrical shape and also of a more realistic CME generated using the ENLIL model. We compare the appearance in both unpolarized B and polarized pB light, and show that there is a quantifiable difference in the measured brightness of a CME between unpolarized and polarized observations. We demonstrate a technique for using this difference to extract the three-dimensional (3D) trajectory of large objects such as CMEs. We conclude with a discussion on how a polarizing heliospheric imager could be used to extract 3D trajectory information about CMEs or other observed features.

  2. Standard Features and Their Impact on 3D Engineering Graphics

    ERIC Educational Resources Information Center

    Waldenmeyer, K. M.; Hartman, N. W.

    2009-01-01

    The prevalence of feature-based 3D modeling in industry has necessitated the accumulation and maintenance of standard feature libraries. Currently, firms who use standard features to design parts are storing and utilizing these libraries through their existing product data management (PDM) systems. Standard features have enabled companies to…

  3. Semantic 3D scene interpretation: A framework combining optimal neighborhood size selection with relevant features

    NASA Astrophysics Data System (ADS)

    Weinmann, M.; Jutzi, B.; Mallet, C.

    2014-08-01

    3D scene analysis by automatically assigning 3D points a semantic label has become an issue of major interest in recent years. Whereas the tasks of feature extraction and classification have been in the focus of research, the idea of using only relevant and more distinctive features extracted from optimal 3D neighborhoods has only rarely been addressed in 3D lidar data processing. In this paper, we focus on the interleaved issue of extracting relevant, but not redundant features and increasing their distinctiveness by considering the respective optimal 3D neighborhood of each individual 3D point. We present a new, fully automatic and versatile framework consisting of four successive steps: (i) optimal neighborhood size selection, (ii) feature extraction, (iii) feature selection, and (iv) classification. In a detailed evaluation which involves 5 different neighborhood definitions, 21 features, 6 approaches for feature subset selection and 2 different classifiers, we demonstrate that optimal neighborhoods for individual 3D points significantly improve the results of scene interpretation and that the selection of adequate feature subsets may even further increase the quality of the derived results.

  4. Registration of 3D spectral OCT volumes using 3D SIFT feature point matching

    NASA Astrophysics Data System (ADS)

    Niemeijer, Meindert; Garvin, Mona K.; Lee, Kyungmoo; van Ginneken, Bram; Abràmoff, Michael D.; Sonka, Milan

    2009-02-01

    The recent introduction of next generation spectral OCT scanners has enabled routine acquisition of high resolution, 3D cross-sectional volumetric images of the retina. 3D OCT is used in the detection and management of serious eye diseases such as glaucoma and age-related macular degeneration. For follow-up studies, image registration is a vital tool to enable more precise, quantitative comparison of disease states. This work presents a registration method based on a recently introduced extension of the 2D Scale-Invariant Feature Transform (SIFT) framework1 to 3D.2 The SIFT feature extractor locates minima and maxima in the difference of Gaussian scale space to find salient feature points. It then uses histograms of the local gradient directions around each found extremum in 3D to characterize them in a 4096 element feature vector. Matching points are found by comparing the distance between feature vectors. We apply this method to the rigid registration of optic nerve head- (ONH) and macula-centered 3D OCT scans of the same patient that have only limited overlap. Three OCT data set pairs with known deformation were used for quantitative assessment of the method's robustness and accuracy when deformations of rotation and scaling were considered. Three-dimensional registration accuracy of 2.0+/-3.3 voxels was observed. The accuracy was assessed as average voxel distance error in N=1572 matched locations. The registration method was applied to 12 3D OCT scans (200 x 200 x 1024 voxels) of 6 normal eyes imaged in vivo to demonstrate the clinical utility and robustness of the method in a real-world environment.

  5. Medical image retrieval system using multiple features from 3D ROIs

    NASA Astrophysics Data System (ADS)

    Lu, Hongbing; Wang, Weiwei; Liao, Qimei; Zhang, Guopeng; Zhou, Zhiming

    2012-02-01

    Compared to a retrieval using global image features, features extracted from regions of interest (ROIs) that reflect distribution patterns of abnormalities would benefit more for content-based medical image retrieval (CBMIR) systems. Currently, most CBMIR systems have been designed for 2D ROIs, which cannot reflect 3D anatomical features and region distribution of lesions comprehensively. To further improve the accuracy of image retrieval, we proposed a retrieval method with 3D features including both geometric features such as Shape Index (SI) and Curvedness (CV) and texture features derived from 3D Gray Level Co-occurrence Matrix, which were extracted from 3D ROIs, based on our previous 2D medical images retrieval system. The system was evaluated with 20 volume CT datasets for colon polyp detection. Preliminary experiments indicated that the integration of morphological features with texture features could improve retrieval performance greatly. The retrieval result using features extracted from 3D ROIs accorded better with the diagnosis from optical colonoscopy than that based on features from 2D ROIs. With the test database of images, the average accuracy rate for 3D retrieval method was 76.6%, indicating its potential value in clinical application.

  6. Assist feature printability prediction by 3-D resist profile reconstruction

    NASA Astrophysics Data System (ADS)

    Zheng, Xin; Huang, Jensheng; Chin, Fook; Kazarian, Aram; Kuo, Chun-Chieh

    2012-06-01

    properties may then be used to optimize the printability vs. efficacy of an SRAF either prior to or during an Optical Proximity Correction (OPC) run. The process models that are used during OPC have never been able to reliably predict which SRAFs will print. This appears to be due to the fact that OPC process models are generally created using data that does not include printed subresolution patterns. An enhancement to compact modeling capability to predict Assist Features (AF) printability is developed and discussed. A hypsometric map representing 3-D resist profile was built by applying a first principle approximation to estimate the "energy loss" from the resist top to bottom. Such a 3-D resist profile is an extrapolation of a well calibrated traditional OPC model without any additional information. Assist features are detected at either top of resist (dark field) or bottom of resist (bright field). Such detection can be done by just extracting top or bottom resist models from our 3-D resist model. There is no measurement of assist features needed when we build AF but it can be included if interested but focusing on resist calibration to account for both exposure dosage and focus change sensitivities. This approach significantly increases resist model's capability for predicting printed SRAF accuracy. And we don't need to calibrate an SRAF model in addition to the OPC model. Without increase in computation time, this compact model can draw assist feature contour with real placement and size at any vertical plane. The result is compared and validated with 3-D rigorous modeling as well as SEM images. Since this method does not change any form of compact modeling, it can be integrated into current MBAF solutions without any additional work.

  7. Midsagittal plane extraction from brain images based on 3D SIFT

    NASA Astrophysics Data System (ADS)

    Wu, Huisi; Wang, Defeng; Shi, Lin; Wen, Zhenkun; Ming, Zhong

    2014-03-01

    Midsagittal plane (MSP) extraction from 3D brain images is considered as a promising technique for human brain symmetry analysis. In this paper, we present a fast and robust MSP extraction method based on 3D scale-invariant feature transform (SIFT). Unlike the existing brain MSP extraction methods, which mainly rely on the gray similarity, 3D edge registration or parameterized surface matching to determine the fissure plane, our proposed method is based on distinctive 3D SIFT features, in which the fissure plane is determined by parallel 3D SIFT matching and iterative least-median of squares plane regression. By considering the relative scales, orientations and flipped descriptors between two 3D SIFT features, we propose a novel metric to measure the symmetry magnitude for 3D SIFT features. By clustering and indexing the extracted SIFT features using a k-dimensional tree (KD-tree) implemented on graphics processing units, we can match multiple pairs of 3D SIFT features in parallel and solve the optimal MSP on-the-fly. The proposed method is evaluated by synthetic and in vivo datasets, of normal and pathological cases, and validated by comparisons with the state-of-the-art methods. Experimental results demonstrated that our method has achieved a real-time performance with better accuracy yielding an average yaw angle error below 0.91° and an average roll angle error no more than 0.89°.

  8. A practical salient region feature based 3D multi-modality registration method for medical images

    NASA Astrophysics Data System (ADS)

    Hahn, Dieter A.; Wolz, Gabriele; Sun, Yiyong; Hornegger, Joachim; Sauer, Frank; Kuwert, Torsten; Xu, Chenyang

    2006-03-01

    We present a novel representation of 3D salient region features and its integration into a hybrid rigid-body registration framework. We adopt scale, translation and rotation invariance properties of those intrinsic 3D features to estimate a transform between underlying mono- or multi-modal 3D medical images. Our method combines advantageous aspects of both feature- and intensity-based approaches and consists of three steps: an automatic extraction of a set of 3D salient region features on each image, a robust estimation of correspondences and their sub-pixel accurate refinement with outliers elimination. We propose a region-growing based approach for the extraction of 3D salient region features, a solution to the problem of feature clustering and a reduction of the correspondence search space complexity. Results of the developed algorithm are presented for both mono- and multi-modal intra-patient 3D image pairs (CT, PET and SPECT) that have been acquired for change detection, tumor localization, and time based intra-person studies. The accuracy of the method is clinically evaluated by a medical expert with an approach that measures the distance between a set of selected corresponding points consisting of both anatomical and functional structures or lesion sites. This demonstrates the robustness of the proposed method to image overlap, missing information and artefacts. We conclude by discussing potential medical applications and possibilities for integration into a non-rigid registration framework.

  9. Fuzzy zoning for feature matching technique in 3D reconstruction of nasal endoscopic images.

    PubMed

    Rattanalappaiboon, Surapong; Bhongmakapat, Thongchai; Ritthipravat, Panrasee

    2015-12-01

    3D reconstruction from nasal endoscopic images greatly supports an otolaryngologist in examining nasal passages, mucosa, polyps, sinuses, and nasopharyx. In general, structure from motion is a popular technique. It consists of four main steps; (1) camera calibration, (2) feature extraction, (3) feature matching, and (4) 3D reconstruction. Scale Invariant Feature Transform (SIFT) algorithm is normally used for both feature extraction and feature matching. However, SIFT algorithm relatively consumes computational time particularly in the feature matching process because each feature in an image of interest is compared with all features in the subsequent image in order to find the best matched pair. A fuzzy zoning approach is developed for confining feature matching area. Matching between two corresponding features from different images can be efficiently performed. With this approach, it can greatly reduce the matching time. The proposed technique is tested with endoscopic images created from phantoms and compared with the original SIFT technique in terms of the matching time and average errors of the reconstructed models. Finally, original SIFT and the proposed fuzzy-based technique are applied to 3D model reconstruction of real nasal cavity based on images taken from a rigid nasal endoscope. The results showed that the fuzzy-based approach was significantly faster than traditional SIFT technique and provided similar quality of the 3D models. It could be used for creating a nasal cavity taken by a rigid nasal endoscope. PMID:26498516

  10. Dynamical Systems Analysis of Fully 3D Ocean Features

    NASA Astrophysics Data System (ADS)

    Pratt, L. J.

    2011-12-01

    Dynamical systems analysis of transport and stirring processes has been developed most thoroughly for 2D flow fields. The calculation of manifolds, turnstile lobes, transport barriers, etc. based on observations of the ocean is most often conducted near the sea surface, whereas analyses at depth, usually carried out with model output, is normally confined to constant-z surfaces. At the meoscale and larger, ocean flows are quasi 2D, but smaller scale (submesoscale) motions, including mixed layer phenomena with significant vertical velocity, may be predominantly 3D. The zoology of hyperbolic trajectories becomes richer in such cases and their attendant manifolds are much more difficult to calculate. I will describe some of the basic geometrical features and corresponding Lagrangian Coherent Features expected to arise in upper ocean fronts, eddies, and Langmuir circulations. Traditional GFD models such as the rotating can flow may capture the important generic features. The dynamical systems approach is most helpful when these features are coherent and persistent and the implications and difficulties for this requirement in fully 3D flows will also be discussed.

  11. 3D Palmprint Identification Using Block-Wise Features and Collaborative Representation.

    PubMed

    Zhang, Lin; Shen, Ying; Li, Hongyu; Lu, Jianwei

    2015-08-01

    Developing 3D palmprint recognition systems has recently begun to draw attention of researchers. Compared with its 2D counterpart, 3D palmprint has several unique merits. However, most of the existing 3D palmprint matching methods are designed for one-to-one verification and they are not efficient to cope with the one-to-many identification case. In this paper, we fill this gap by proposing a collaborative representation (CR) based framework with l1-norm or l2-norm regularizations for 3D palmprint identification. The effects of different regularization terms have been evaluated in experiments. To use the CR-based classification framework, one key issue is how to extract feature vectors. To this end, we propose a block-wise statistics based feature extraction scheme. We divide a 3D palmprint ROI into uniform blocks and extract a histogram of surface types from each block; histograms from all blocks are then concatenated to form a feature vector. Such feature vectors are highly discriminative and are robust to mere misalignment. Experiments demonstrate that the proposed CR-based framework with an l2-norm regularization term can achieve much better recognition accuracy than the other methods. More importantly, its computational complexity is extremely low, making it quite suitable for the large-scale identification application. Source codes are available at http://sse.tongji.edu.cn/linzhang/cr3dpalm/cr3dpalm.htm. PMID:26353008

  12. Uniform Local Binary Pattern Based Texture-Edge Feature for 3D Human Behavior Recognition

    PubMed Central

    Ming, Yue; Wang, Guangchao; Fan, Chunxiao

    2015-01-01

    With the rapid development of 3D somatosensory technology, human behavior recognition has become an important research field. Human behavior feature analysis has evolved from traditional 2D features to 3D features. In order to improve the performance of human activity recognition, a human behavior recognition method is proposed, which is based on a hybrid texture-edge local pattern coding feature extraction and integration of RGB and depth videos information. The paper mainly focuses on background subtraction on RGB and depth video sequences of behaviors, extracting and integrating historical images of the behavior outlines, feature extraction and classification. The new method of 3D human behavior recognition has achieved the rapid and efficient recognition of behavior videos. A large number of experiments show that the proposed method has faster speed and higher recognition rate. The recognition method has good robustness for different environmental colors, lightings and other factors. Meanwhile, the feature of mixed texture-edge uniform local binary pattern can be used in most 3D behavior recognition. PMID:25942404

  13. Uniform Local Binary Pattern Based Texture-Edge Feature for 3D Human Behavior Recognition.

    PubMed

    Ming, Yue; Wang, Guangchao; Fan, Chunxiao

    2015-01-01

    With the rapid development of 3D somatosensory technology, human behavior recognition has become an important research field. Human behavior feature analysis has evolved from traditional 2D features to 3D features. In order to improve the performance of human activity recognition, a human behavior recognition method is proposed, which is based on a hybrid texture-edge local pattern coding feature extraction and integration of RGB and depth videos information. The paper mainly focuses on background subtraction on RGB and depth video sequences of behaviors, extracting and integrating historical images of the behavior outlines, feature extraction and classification. The new method of 3D human behavior recognition has achieved the rapid and efficient recognition of behavior videos. A large number of experiments show that the proposed method has faster speed and higher recognition rate. The recognition method has good robustness for different environmental colors, lightings and other factors. Meanwhile, the feature of mixed texture-edge uniform local binary pattern can be used in most 3D behavior recognition. PMID:25942404

  14. Bone segmentation and fracture detection in ultrasound using 3D local phase features.

    PubMed

    Hacihaliloglu, Ilker; Abugharbieh, Rafeef; Hodgson, Antony; Rohling, Robert

    2008-01-01

    3D ultrasound (US) is increasingly considered as a viable alternative imaging modality in computer-assisted orthopaedic surgery (CAOS) applications. Automatic bone segmentation from US images, however, remains a challenge due to speckle noise and various other artifacts inherent to US. In this paper, we present intensity invariant three dimensional (3D) local image phase features, obtained using 3D Log-Gabor filter banks, for extracting ridge-like features similar to those that occur at soft tissue/bone interfaces. Our contributions include the novel extension of 2D phase symmetry features to 3D and their use in automatic extraction of bone surfaces and fractured fragments in 3D US. We validate our technique using phantom, in vitro, and in vivo experiments. Qualitative and quantitative results demonstrate remarkably clear segmentations results of bone surfaces with a localization accuracy of better than 0.62 mm and mean errors in estimating fracture displacements below 0.65 mm, which will likely be of strong clinical utility. PMID:18979759

  15. Feature relevance assessment for the semantic interpretation of 3D point cloud data

    NASA Astrophysics Data System (ADS)

    Weinmann, M.; Jutzi, B.; Mallet, C.

    2013-10-01

    The automatic analysis of large 3D point clouds represents a crucial task in photogrammetry, remote sensing and computer vision. In this paper, we propose a new methodology for the semantic interpretation of such point clouds which involves feature relevance assessment in order to reduce both processing time and memory consumption. Given a standard benchmark dataset with 1.3 million 3D points, we first extract a set of 21 geometric 3D and 2D features. Subsequently, we apply a classifier-independent ranking procedure which involves a general relevance metric in order to derive compact and robust subsets of versatile features which are generally applicable for a large variety of subsequent tasks. This metric is based on 7 different feature selection strategies and thus addresses different intrinsic properties of the given data. For the example of semantically interpreting 3D point cloud data, we demonstrate the great potential of smaller subsets consisting of only the most relevant features with 4 different state-of-the-art classifiers. The results reveal that, instead of including as many features as possible in order to compensate for lack of knowledge, a crucial task such as scene interpretation can be carried out with only few versatile features and even improved accuracy.

  16. 3D Actin Network Centerline Extraction with Multiple Active Contours

    PubMed Central

    Xu, Ting; Vavylonis, Dimitrios; Huang, Xiaolei

    2013-01-01

    Fluorescence microscopy is frequently used to study two and three dimensional network structures formed by cytoskeletal polymer fibers such as actin filaments and actin cables. While these cytoskeletal structures are often dilute enough to allow imaging of individual filaments or bundles of them, quantitative analysis of these images is challenging. To facilitate quantitative, reproducible and objective analysis of the image data, we propose a semi-automated method to extract actin networks and retrieve their topology in 3D. Our method uses multiple Stretching Open Active Contours (SOACs) that are automatically initialized at image intensity ridges and then evolve along the centerlines of filaments in the network. SOACs can merge, stop at junctions, and reconfigure with others to allow smooth crossing at junctions of filaments. The proposed approach is generally applicable to images of curvilinear networks with low SNR. We demonstrate its potential by extracting the centerlines of synthetic meshwork images, actin networks in 2D Total Internal Reflection Fluorescence Microscopy images, and 3D actin cable meshworks of live fission yeast cells imaged by spinning disk confocal microscopy. Quantitative evaluation of the method using synthetic images shows that for images with SNR above 5.0, the average vertex error measured by the distance between our result and ground truth is 1 voxel, and the average Hausdorff distance is below 10 voxels. PMID:24316442

  17. Fast 3D Surface Extraction 2 pages (including abstract)

    SciTech Connect

    Sewell, Christopher Meyer; Patchett, John M.; Ahrens, James P.

    2012-06-05

    Ocean scientists searching for isosurfaces and/or thresholds of interest in high resolution 3D datasets required a tedious and time-consuming interactive exploration experience. PISTON research and development activities are enabling ocean scientists to rapidly and interactively explore isosurfaces and thresholds in their large data sets using a simple slider with real time calculation and visualization of these features. Ocean Scientists can now visualize more features in less time, helping them gain a better understanding of the high resolution data sets they work with on a daily basis. Isosurface timings (512{sup 3} grid): VTK 7.7 s, Parallel VTK (48-core) 1.3 s, PISTON OpenMP (48-core) 0.2 s, PISTON CUDA (Quadro 6000) 0.1 s.

  18. 3D transrectal ultrasound (TRUS) prostate segmentation based on optimal feature learning framework

    NASA Astrophysics Data System (ADS)

    Yang, Xiaofeng; Rossi, Peter J.; Jani, Ashesh B.; Mao, Hui; Curran, Walter J.; Liu, Tian

    2016-03-01

    We propose a 3D prostate segmentation method for transrectal ultrasound (TRUS) images, which is based on patch-based feature learning framework. Patient-specific anatomical features are extracted from aligned training images and adopted as signatures for each voxel. The most robust and informative features are identified by the feature selection process to train the kernel support vector machine (KSVM). The well-trained SVM was used to localize the prostate of the new patient. Our segmentation technique was validated with a clinical study of 10 patients. The accuracy of our approach was assessed using the manual segmentations (gold standard). The mean volume Dice overlap coefficient was 89.7%. In this study, we have developed a new prostate segmentation approach based on the optimal feature learning framework, demonstrated its clinical feasibility, and validated its accuracy with manual segmentations.

  19. Extracting, Tracking, and Visualizing Magnetic Flux Vortices in 3D Complex-Valued Superconductor Simulation Data.

    PubMed

    Guo, Hanqi; Phillips, Carolyn L; Peterka, Tom; Karpeyev, Dmitry; Glatz, Andreas

    2016-01-01

    We propose a method for the vortex extraction and tracking of superconducting magnetic flux vortices for both structured and unstructured mesh data. In the Ginzburg-Landau theory, magnetic flux vortices are well-defined features in a complex-valued order parameter field, and their dynamics determine electromagnetic properties in type-II superconductors. Our method represents each vortex line (a 1D curve embedded in 3D space) as a connected graph extracted from the discretized field in both space and time. For a time-varying discrete dataset, our vortex extraction and tracking method is as accurate as the data discretization. We then apply 3D visualization and 2D event diagrams to the extraction and tracking results to help scientists understand vortex dynamics and macroscale superconductor behavior in greater detail than previously possible. PMID:26529730

  20. Extraction of edge feature in cardiovascular image

    NASA Astrophysics Data System (ADS)

    Lu, Jianrong; Chen, Dongqing; Yu, Daoyin; Liu, Xiaojun

    2001-09-01

    Extraction of edge feature and accurate measurement of vascular diameter in cardiovascular image are the bases for labeling the coronary hierarchy, 3D refined reconstruction of the coronary arterial tree and accurate fusion between the calculated 3D vascular trees and other views. In order to extract vessels from the image, the grayscale minimization of the circle template and differential edge detection are put forward. Edge pixels of the coronary artery are set according to maximization of the differential value. The edge lines are determined after the edge pixels are smoothed by B-Spline function. The assessment of feature extraction is demonstrated by the excellent performance in computer simulation and actual application.

  1. A 3D Feature Descriptor Recovered from a Single 2D Palmprint Image.

    PubMed

    Zheng, Qian; Kumar, Ajay; Pan, Gang

    2016-06-01

    Design and development of efficient and accurate feature descriptors is critical for the success of many computer vision applications. This paper proposes a new feature descriptor, referred to as DoN, for the 2D palmprint matching. The descriptor is extracted for each point on the palmprint. It is based on the ordinal measure which partially describes the difference of the neighboring points' normal vectors. DoN has at least two advantages: 1) it describes the 3D information, which is expected to be highly stable under commonly occurring illumination variations during contactless imaging; 2) the size of DoN for each point is only one bit, which is computationally simple to extract, easy to match, and efficient to storage. We show that such 3D information can be extracted from a single 2D palmprint image. The analysis for the effectiveness of ordinal measure for palmprint matching is also provided. Four publicly available 2D palmprint databases are used to evaluate the effectiveness of DoN, both for identification and the verification. Our method on all these databases achieves the state-of-the-art performance. PMID:27164564

  2. Facets : a Cloudcompare Plugin to Extract Geological Planes from Unstructured 3d Point Clouds

    NASA Astrophysics Data System (ADS)

    Dewez, T. J. B.; Girardeau-Montaut, D.; Allanic, C.; Rohmer, J.

    2016-06-01

    Geological planar facets (stratification, fault, joint…) are key features to unravel the tectonic history of rock outcrop or appreciate the stability of a hazardous rock cliff. Measuring their spatial attitude (dip and strike) is generally performed by hand with a compass/clinometer, which is time consuming, requires some degree of censoring (i.e. refusing to measure some features judged unimportant at the time), is not always possible for fractures higher up on the outcrop and is somewhat hazardous. 3D virtual geological outcrop hold the potential to alleviate these issues. Efficiently segmenting massive 3D point clouds into individual planar facets, inside a convenient software environment was lacking. FACETS is a dedicated plugin within CloudCompare v2.6.2 (http://cloudcompare.org/ ) implemented to perform planar facet extraction, calculate their dip and dip direction (i.e. azimuth of steepest decent) and report the extracted data in interactive stereograms. Two algorithms perform the segmentation: Kd-Tree and Fast Marching. Both divide the point cloud into sub-cells, then compute elementary planar objects and aggregate them progressively according to a planeity threshold into polygons. The boundaries of the polygons are adjusted around segmented points with a tension parameter, and the facet polygons can be exported as 3D polygon shapefiles towards third party GIS software or simply as ASCII comma separated files. One of the great features of FACETS is the capability to explore planar objects but also 3D points with normals with the stereogram tool. Poles can be readily displayed, queried and manually segmented interactively. The plugin blends seamlessly into CloudCompare to leverage all its other 3D point cloud manipulation features. A demonstration of the tool is presented to illustrate these different features. While designed for geological applications, FACETS could be more widely applied to any planar

  3. Adaptive feature extraction expert

    SciTech Connect

    Yuschik, M.

    1983-01-01

    The identification of discriminatory features places an upper bound on the recognition rate of any automatic speech recognition (ASR) system. One way to structure the extraction of features is to construct an expert system which applies a set of rules to identify particular properties of the speech patterns. However, these patterns vary for an individual speaker and from speaker to speaker so that another expert is actually needed to learn the new variations. The author investigates the problem by using sets of discriminatory features that are suggested by a feature generation expert, improves the selectivity of these features with a training expert, and finally develops a minimally spanning feature set with a statistical selection expert. 12 references.

  4. Vertical Corner Feature Based Precise Vehicle Localization Using 3D LIDAR in Urban Area.

    PubMed

    Im, Jun-Hyuck; Im, Sung-Hyuck; Jee, Gyu-In

    2016-01-01

    Tall buildings are concentrated in urban areas. The outer walls of buildings are vertically erected to the ground and almost flat. Therefore, the vertical corners that meet the vertical planes are present everywhere in urban areas. These corners act as convenient landmarks, which can be extracted by using the light detection and ranging (LIDAR) sensor. A vertical corner feature based precise vehicle localization method is proposed in this paper and implemented using 3D LIDAR (Velodyne HDL-32E). The vehicle motion is predicted by accumulating the pose increment output from the iterative closest point (ICP) algorithm based on the geometric relations between the scan data of the 3D LIDAR. The vertical corner is extracted using the proposed corner extraction method. The vehicle position is then corrected by matching the prebuilt corner map with the extracted corner. The experiment was carried out in the Gangnam area of Seoul, South Korea. In the experimental results, the maximum horizontal position error is about 0.46 m and the 2D Root Mean Square (RMS) horizontal error is about 0.138 m. PMID:27517936

  5. Indoor Modelling Benchmark for 3D Geometry Extraction

    NASA Astrophysics Data System (ADS)

    Thomson, C.; Boehm, J.

    2014-06-01

    A combination of faster, cheaper and more accurate hardware, more sophisticated software, and greater industry acceptance have all laid the foundations for an increased desire for accurate 3D parametric models of buildings. Pointclouds are the data source of choice currently with static terrestrial laser scanning the predominant tool for large, dense volume measurement. The current importance of pointclouds as the primary source of real world representation is endorsed by CAD software vendor acquisitions of pointcloud engines in 2011. Both the capture and modelling of indoor environments require great effort in time by the operator (and therefore cost). Automation is seen as a way to aid this by reducing the workload of the user and some commercial packages have appeared that provide automation to some degree. In the data capture phase, advances in indoor mobile mapping systems are speeding up the process, albeit currently with a reduction in accuracy. As a result this paper presents freely accessible pointcloud datasets of two typical areas of a building each captured with two different capture methods and each with an accurate wholly manually created model. These datasets are provided as a benchmark for the research community to gauge the performance and improvements of various techniques for indoor geometry extraction. With this in mind, non-proprietary, interoperable formats are provided such as E57 for the scans and IFC for the reference model. The datasets can be found at: http://indoor-bench.github.io/indoor-bench.

  6. Combination of 3D skin surface texture features and 2D ABCD features for improved melanoma diagnosis.

    PubMed

    Ding, Yi; John, Nigel W; Smith, Lyndon; Sun, Jiuai; Smith, Melvyn

    2015-10-01

    Two-dimensional asymmetry, border irregularity, colour variegation and diameter (ABCD) features are important indicators currently used for computer-assisted diagnosis of malignant melanoma (MM); however, they often prove to be insufficient to make a convincing diagnosis. Previous work has demonstrated that 3D skin surface normal features in the form of tilt and slant pattern disruptions are promising new features independent from the existing 2D ABCD features. This work investigates that whether improved lesion classification can be achieved by combining the 3D features with the 2D ABCD features. Experiments using a nonlinear support vector machine classifier show that many combinations of the 2D ABCD features and the 3D features can give substantially better classification accuracy than using (1) single features and (2) many combinations of the 2D ABCD features. The best 2D and 3D feature combination includes the overall 3D skin surface disruption, the asymmetry and all the three colour channel features. It gives an overall 87.8 % successful classification, which is better than the best single feature with 78.0 % and the best 2D feature combination with 83.1 %. These demonstrate that (1) the 3D features have additive values to improve the existing lesion classification and (2) combining the 3D feature with all the 2D features does not lead to the best lesion classification. The two ABCD features not selected by the best 2D and 3D combination, namely (1) the border feature and (2) the diameter feature, were also studied in separate experiments. It found that inclusion of either feature in the 2D and 3D combination can successfully classify 3 out of 4 lesion groups. The only one group not accurately classified by either feature can be classified satisfactorily by the other. In both cases, they have shown better classification performances than those without the 3D feature in the combinations. This further demonstrates that (1) the 3D feature can be used to

  7. Registration of 3-D images using weighted geometrical features

    SciTech Connect

    Maurer, C.R. Jr.; Aboutanos, G.B.; Dawant, B.M.; Maciunas, R.J.; Fitzpatrick, J.M.

    1996-12-01

    In this paper, the authors present a weighted geometrical features (WGF) registration algorithm. Its efficacy is demonstrated by combining points and a surface. The technique is an extension of Besl and McKay`s iterative closest point (ICP) algorithm. The authors use the WGF algorithm to register X-ray computed tomography (CT) and T2-weighted magnetic resonance (MR) volume head images acquired from eleven patients that underwent craniotomies in a neurosurgical clinical trial. Each patient had five external markers attached to transcutaneous posts screwed into the outer table of the skull. The authors define registration error as the distance between positions of corresponding markers that are not used for registration. The CT and MR images are registered using fiducial points (marker positions) only, a surface only, and various weighted combinations of points and a surface. The CT surface is derived from contours corresponding to the inner surface of the skull. The MR surface is derived from contours corresponding to the cerebrospinal fluid (CSF)-dura interface. Registration using points and a surface is found to be significantly more accurate than registration using only points or a surface.

  8. Capacitance extraction from complex 3D interconnect structures

    SciTech Connect

    Cartwright, D.; Csanak, G.; George, D.; Walker, R.; Kuprat, A.; Dengi, A.; Grobman, W.

    1999-06-01

    A new tool has been developed for calculating the capacitance matrix for complex 3D interconnect structures involving multiple layers of irregularly shaped interconnect, imbedded in different dielectric materials. This method utilizes a new 3D adaptive unstructured grid capability, and a linear finite element algorithm. The capacitance is determined from the minimum in the total system energy as the nodes are varied to minimize the error in the electric field in the dielectric(s).

  9. 3D Axon structure extraction and analysis in confocal fluorescence microscopy images.

    PubMed

    Zhang, Yong; Zhou, Xiaobo; Lu, Ju; Lichtman, Jeff; Adjeroh, Donald; Wong, Stephen T C

    2008-08-01

    The morphological properties of axons, such as their branching patterns and oriented structures, are of great interest for biologists in the study of the synaptic connectivity of neurons. In these studies, researchers use triple immunofluorescent confocal microscopy to record morphological changes of neuronal processes. Three-dimensional (3D) microscopy image analysis is then required to extract morphological features of the neuronal structures. In this article, we propose a highly automated 3D centerline extraction tool to assist in this task. For this project, the most difficult part is that some axons are overlapping such that the boundaries distinguishing them are barely visible. Our approach combines a 3D dynamic programming (DP) technique and marker-controlled watershed algorithm to solve this problem. The approach consists of tracking and updating along the navigation directions of multiple axons simultaneously. The experimental results show that the proposed method can rapidly and accurately extract multiple axon centerlines and can handle complicated axon structures such as cross-over sections and overlapping objects. PMID:18336075

  10. 3D facial expression recognition using maximum relevance minimum redundancy geometrical features

    NASA Astrophysics Data System (ADS)

    Rabiu, Habibu; Saripan, M. Iqbal; Mashohor, Syamsiah; Marhaban, Mohd Hamiruce

    2012-12-01

    In recent years, facial expression recognition (FER) has become an attractive research area, which besides the fundamental challenges, it poses, finds application in areas, such as human-computer interaction, clinical psychology, lie detection, pain assessment, and neurology. Generally the approaches to FER consist of three main steps: face detection, feature extraction and expression recognition. The recognition accuracy of FER hinges immensely on the relevance of the selected features in representing the target expressions. In this article, we present a person and gender independent 3D facial expression recognition method, using maximum relevance minimum redundancy geometrical features. The aim is to detect a compact set of features that sufficiently represents the most discriminative features between the target classes. Multi-class one-against-one SVM classifier was employed to recognize the seven facial expressions; neutral, happy, sad, angry, fear, disgust, and surprise. The average recognition accuracy of 92.2% was recorded. Furthermore, inter database homogeneity was investigated between two independent databases the BU-3DFE and UPM-3DFE the results showed a strong homogeneity between the two databases.

  11. 3D-2D Deformable Image Registration Using Feature-Based Nonuniform Meshes

    PubMed Central

    Guo, Xiaohu; Cai, Yiqi; Yang, Yin; Wang, Jing; Jia, Xun

    2016-01-01

    By using prior information of planning CT images and feature-based nonuniform meshes, this paper demonstrates that volumetric images can be efficiently registered with a very small portion of 2D projection images of a Cone-Beam Computed Tomography (CBCT) scan. After a density field is computed based on the extracted feature edges from planning CT images, nonuniform tetrahedral meshes will be automatically generated to better characterize the image features according to the density field; that is, finer meshes are generated for features. The displacement vector fields (DVFs) are specified at the mesh vertices to drive the deformation of original CT images. Digitally reconstructed radiographs (DRRs) of the deformed anatomy are generated and compared with corresponding 2D projections. DVFs are optimized to minimize the objective function including differences between DRRs and projections and the regularity. To further accelerate the above 3D-2D registration, a procedure to obtain good initial deformations by deforming the volume surface to match 2D body boundary on projections has been developed. This complete method is evaluated quantitatively by using several digital phantoms and data from head and neck cancer patients. The feature-based nonuniform meshing method leads to better results than either uniform orthogonal grid or uniform tetrahedral meshes. PMID:27019849

  12. A Multiscale Constraints Method Localization of 3D Facial Feature Points

    PubMed Central

    Li, Hong-an; Zhang, Yongxin; Li, Zhanli; Li, Huilin

    2015-01-01

    It is an important task to locate facial feature points due to the widespread application of 3D human face models in medical fields. In this paper, we propose a 3D facial feature point localization method that combines the relative angle histograms with multiscale constraints. Firstly, the relative angle histogram of each vertex in a 3D point distribution model is calculated; then the cluster set of the facial feature points is determined using the cluster algorithm. Finally, the feature points are located precisely according to multiscale integral features. The experimental results show that the feature point localization accuracy of this algorithm is better than that of the localization method using the relative angle histograms. PMID:26539244

  13. A novel 3D wavelet based filter for visualizing features in noisy biological data

    SciTech Connect

    Moss, W C; Haase, S; Lyle, J M; Agard, D A; Sedat, J W

    2005-01-05

    We have developed a 3D wavelet-based filter for visualizing structural features in volumetric data. The only variable parameter is a characteristic linear size of the feature of interest. The filtered output contains only those regions that are correlated with the characteristic size, thus denoising the image. We demonstrate the use of the filter by applying it to 3D data from a variety of electron microscopy samples including low contrast vitreous ice cryogenic preparations, as well as 3D optical microscopy specimens.

  14. 3D-profile measurement of advanced semiconductor features by reference metrology

    NASA Astrophysics Data System (ADS)

    Takamasu, Kiyoshi; Iwaki, Yuuki; Takahashi, Satoru; Kawada, Hiroki; Ikota, Masami; Lorusso, Gian F.; Horiguchi, Naoto

    2016-03-01

    A method of sub-nanometer uncertainty for the 3D-profile measurement using TEM (Transmission Electron Microscope) images is proposed to standardize 3D-profile measurement through reference metrology. The proposed method has been validated for profiles of Si lines, photoresist features and advanced-FinFET (Fin-shaped Field-Effect Transistor) features in our previous investigations. However, efficiency of 3D-profile measurement using TEM is limited by measurement time including processing of the sample. In this article, we demonstrate a novel on-wafer 3D-profile metrology as "FIB-to-CDSEM method" with FIB (Focused Ion Beam) slope cut and CD-SEM (Critical Dimension Secondary Electron Microscope) measuring. Using the method, a few micrometer wide on a wafer is coated and cut by 45 degree slope using FIB tool. Then, the wafer is transferred to CD-SEM to measure the cross section image by top down CD-SEM measurement. We apply FIB-to-CDSEM method to CMOS sensor device. 3D-profile and 3D-profile parameters such as top line width and side wall angles of CMOS sensor device are evaluated. The 3D-profile parameters also are measured by TEM images as reference metrology. We compare the 3D-profile parameters by TEM method and FIB-to-CDSEM method. The average values and correlations on the wafer are agreed well between TEM and FIB-to- CDSEM methods.

  15. Realistic texture extraction for 3D face models robust to self-occlusion

    NASA Astrophysics Data System (ADS)

    Qu, Chengchao; Monari, Eduardo; Schuchert, Tobias; Beyerer, Jürgen

    2015-02-01

    In the context of face modeling, probably the most well-known approach to represent 3D faces is the 3D Morphable Model (3DMM). When 3DMM is fitted to a 2D image, the shape as well as the texture and illumination parameters are simultaneously estimated. However, if real facial texture is needed, texture extraction from the 2D image is necessary. This paper addresses the possible problems in texture extraction of a single image caused by self-occlusion. Unlike common approaches that leverage the symmetric property of the face by mirroring the visible facial part, which is sensitive to inhomogeneous illumination, this work first generates a virtual texture map for the skin area iteratively by averaging the color of neighbored vertices. Although this step creates unrealistic, overly smoothed texture, illumination stays constant between the real and virtual texture. In the second pass, the mirrored texture is gradually blended with the real or generated texture according to the visibility. This scheme ensures a gentle handling of illumination and yet yields realistic texture. Because the blending area only relates to non-informative area, main facial features still have unique appearance in different face halves. Evaluation results reveal realistic rendering in novel poses robust to challenging illumination conditions and small registration errors.

  16. Recursive Feature Extraction in Graphs

    2014-08-14

    ReFeX extracts recursive topological features from graph data. The input is a graph as a csv file and the output is a csv file containing feature values for each node in the graph. The features are based on topological counts in the neighborhoods of each nodes, as well as recursive summaries of neighbors' features.

  17. 3D automatic liver segmentation using feature-constrained Mahalanobis distance in CT images.

    PubMed

    Salman Al-Shaikhli, Saif Dawood; Yang, Michael Ying; Rosenhahn, Bodo

    2016-08-01

    Automatic 3D liver segmentation is a fundamental step in the liver disease diagnosis and surgery planning. This paper presents a novel fully automatic algorithm for 3D liver segmentation in clinical 3D computed tomography (CT) images. Based on image features, we propose a new Mahalanobis distance cost function using an active shape model (ASM). We call our method MD-ASM. Unlike the standard active shape model (ST-ASM), the proposed method introduces a new feature-constrained Mahalanobis distance cost function to measure the distance between the generated shape during the iterative step and the mean shape model. The proposed Mahalanobis distance function is learned from a public database of liver segmentation challenge (MICCAI-SLiver07). As a refinement step, we propose the use of a 3D graph-cut segmentation. Foreground and background labels are automatically selected using texture features of the learned Mahalanobis distance. Quantitatively, the proposed method is evaluated using two clinical 3D CT scan databases (MICCAI-SLiver07 and MIDAS). The evaluation of the MICCAI-SLiver07 database is obtained by the challenge organizers using five different metric scores. The experimental results demonstrate the availability of the proposed method by achieving an accurate liver segmentation compared to the state-of-the-art methods. PMID:26501155

  18. Building an accurate 3D model of a circular feature for robot vision

    NASA Astrophysics Data System (ADS)

    Li, L.

    2012-06-01

    In this paper, an accurate 3D model analysis of a circular feature is built with error compensation for robot vision. We propose an efficient method of fitting ellipses to data points by minimizing the algebraic distance subject to the constraint that a conic should be an ellipse and solving the ellipse parameters through a direct ellipse fitting method by analysing the 3D geometrical representation in a perspective projection scheme, the 3D position of a circular feature with known radius can be obtained. A set of identical circles, machined on a calibration board whose centres were known, was calibrated with a camera and did the model analysis that our method developed. Experimental results show that our method is more accurate than other methods.

  19. Multi-view alignment with database of features for an improved usage of high-end 3D scanners

    NASA Astrophysics Data System (ADS)

    Bonarrigo, Francesco; Signoroni, Alberto; Leonardi, Riccardo

    2012-12-01

    The usability of high-precision and high-resolution 3D scanners is of crucial importance due to the increasing demand of 3D data in both professional and general-purpose applications. Simplified, intuitive and rapid object modeling requires effective and automated alignment pipelines capable to trace back each independently acquired range image of the scanned object into a common reference system. To this end, we propose a reliable and fast feature-based multiple-view alignment pipeline that allows interactive registration of multiple views according to an unchained acquisition procedure. A robust alignment of each new view is estimated with respect to the previously aligned data through fast extraction, representation and matching of feature points detected in overlapping areas from different views. The proposed pipeline guarantees a highly reliable alignment of dense range image datasets on a variety of objects in few seconds per million of points.

  20. Extracting 3-D information from SEM and TEM images: Approaches and applications in the physical sciences

    SciTech Connect

    L`Esperance, G.; Dionne, M.; Tremblay, S.

    1996-12-31

    Techniques for extracting 3-D information from TEM samples in life sciences have considerably progressed in recent years. One approach has been the use of serial prepared by ultramicrotomy from which the volume of the sample and of various constituents can be reconstructed. In the case of engineering materials, however, ultramicrotomy generally induces severe deformation resulting in a large density of structural defects (dislocations, stacking faults etc.). This leads to significant diffraction contrast effects which mask microstructural features such as second phase particles, precipitates etc. Recently, a series of TEM bright field images taken at different tilts have been used in combination with image analysis to determine the volume fraction (V{sub f}) of second phase particles in thin foils of aluminum alloys. Although the technique was successful to remove most of the diffraction contrast effects and to make the particles visible, the need to acquire and process a large number of images makes the technique laborious and can lead to artefacts.

  1. Algorithm of pulmonary emphysema extraction using thoracic 3D CT images

    NASA Astrophysics Data System (ADS)

    Saita, Shinsuke; Kubo, Mitsuru; Kawata, Yoshiki; Niki, Noboru; Nakano, Yasutaka; Ohmatsu, Hironobu; Tominaga, Keigo; Eguchi, Kenji; Moriyama, Noriyuki

    2007-03-01

    Recently, due to aging and smoking, emphysema patients are increasing. The restoration of alveolus which was destroyed by emphysema is not possible, thus early detection of emphysema is desired. We describe a quantitative algorithm for extracting emphysematous lesions and quantitatively evaluate their distribution patterns using low dose thoracic 3-D CT images. The algorithm identified lung anatomies, and extracted low attenuation area (LAA) as emphysematous lesion candidates. Applying the algorithm to thoracic 3-D CT images and then by follow-up 3-D CT images, we demonstrate its potential effectiveness to assist radiologists and physicians to quantitatively evaluate the emphysematous lesions distribution and their evolution in time interval changes.

  2. Algorithm of pulmonary emphysema extraction using low dose thoracic 3D CT images

    NASA Astrophysics Data System (ADS)

    Saita, S.; Kubo, M.; Kawata, Y.; Niki, N.; Nakano, Y.; Omatsu, H.; Tominaga, K.; Eguchi, K.; Moriyama, N.

    2006-03-01

    Recently, due to aging and smoking, emphysema patients are increasing. The restoration of alveolus which was destroyed by emphysema is not possible, thus early detection of emphysema is desired. We describe a quantitative algorithm for extracting emphysematous lesions and quantitatively evaluate their distribution patterns using low dose thoracic 3-D CT images. The algorithm identified lung anatomies, and extracted low attenuation area (LAA) as emphysematous lesion candidates. Applying the algorithm to 100 thoracic 3-D CT images and then by follow-up 3-D CT images, we demonstrate its potential effectiveness to assist radiologists and physicians to quantitatively evaluate the emphysematous lesions distribution and their evolution in time interval changes.

  3. RELAP5-3D Code Includes Athena Features and Models

    SciTech Connect

    Richard A. Riemke; Cliff B. Davis; Richard R. Schultz

    2006-07-01

    Version 2.3 of the RELAP5-3D computer program includes all features and models previously available only in the ATHENA version of the code. These include the addition of new working fluids (i.e., ammonia, blood, carbon dioxide, glycerol, helium, hydrogen, lead-bismuth, lithium, lithium-lead, nitrogen, potassium, sodium, and sodium-potassium) and a magnetohydrodynamic model that expands the capability of the code to model many more thermal-hydraulic systems. In addition to the new working fluids along with the standard working fluid water, one or more noncondensable gases (e.g., air, argon, carbon dioxide, carbon monoxide, helium, hydrogen, krypton, nitrogen, oxygen, sf6, xenon) can be specified as part of the vapor/gas phase of the working fluid. These noncondensable gases were in previous versions of RELAP5- 3D. Recently four molten salts have been added as working fluids to RELAP5-3D Version 2.4, which has had limited release. These molten salts will be in RELAP5-3D Version 2.5, which will have a general release like RELAP5-3D Version 2.3. Applications that use these new features and models are discussed in this paper.

  4. RELAP5-3D Code Includes ATHENA Features and Models

    SciTech Connect

    Riemke, Richard A.; Davis, Cliff B.; Schultz, Richard R.

    2006-07-01

    Version 2.3 of the RELAP5-3D computer program includes all features and models previously available only in the ATHENA version of the code. These include the addition of new working fluids (i.e., ammonia, blood, carbon dioxide, glycerol, helium, hydrogen, lead-bismuth, lithium, lithium-lead, nitrogen, potassium, sodium, and sodium-potassium) and a magnetohydrodynamic model that expands the capability of the code to model many more thermal-hydraulic systems. In addition to the new working fluids along with the standard working fluid water, one or more noncondensable gases (e.g., air, argon, carbon dioxide, carbon monoxide, helium, hydrogen, krypton, nitrogen, oxygen, SF{sub 6}, xenon) can be specified as part of the vapor/gas phase of the working fluid. These noncondensable gases were in previous versions of RELAP5-3D. Recently four molten salts have been added as working fluids to RELAP5-3D Version 2.4, which has had limited release. These molten salts will be in RELAP5-3D Version 2.5, which will have a general release like RELAP5-3D Version 2.3. Applications that use these new features and models are discussed in this paper. (authors)

  5. Automated extraction and analysis of rock discontinuity characteristics from 3D point clouds

    NASA Astrophysics Data System (ADS)

    Bianchetti, Matteo; Villa, Alberto; Agliardi, Federico; Crosta, Giovanni B.

    2016-04-01

    A reliable characterization of fractured rock masses requires an exhaustive geometrical description of discontinuities, including orientation, spacing, and size. These are required to describe discontinuum rock mass structure, perform Discrete Fracture Network and DEM modelling, or provide input for rock mass classification or equivalent continuum estimate of rock mass properties. Although several advanced methodologies have been developed in the last decades, a complete characterization of discontinuity geometry in practice is still challenging, due to scale-dependent variability of fracture patterns and difficult accessibility to large outcrops. Recent advances in remote survey techniques, such as terrestrial laser scanning and digital photogrammetry, allow a fast and accurate acquisition of dense 3D point clouds, which promoted the development of several semi-automatic approaches to extract discontinuity features. Nevertheless, these often need user supervision on algorithm parameters which can be difficult to assess. To overcome this problem, we developed an original Matlab tool, allowing fast, fully automatic extraction and analysis of discontinuity features with no requirements on point cloud accuracy, density and homogeneity. The tool consists of a set of algorithms which: (i) process raw 3D point clouds, (ii) automatically characterize discontinuity sets, (iii) identify individual discontinuity surfaces, and (iv) analyse their spacing and persistence. The tool operates in either a supervised or unsupervised mode, starting from an automatic preliminary exploration data analysis. The identification and geometrical characterization of discontinuity features is divided in steps. First, coplanar surfaces are identified in the whole point cloud using K-Nearest Neighbor and Principal Component Analysis algorithms optimized on point cloud accuracy and specified typical facet size. Then, discontinuity set orientation is calculated using Kernel Density Estimation and

  6. Process monitor of 3D-device features by using FIB and CD-SEM

    NASA Astrophysics Data System (ADS)

    Kawada, Hiroki; Ikota, Masami; Sakai, Hideo; Torikawa, Shota; Tomimatsu, Satoshi; Onishi, Tsuyoshi

    2016-03-01

    For yield improvement of 3D-device manufacturing, metrology for the variability of individual device-features is on hot issue. Transmission Electron Microscope (TEM) can be used for monitoring the individual cross-section. However, efficiency of process monitoring is limited by the speed of measurement including preparation of lamella sample. In this work we demonstrate speedy 3D-profile measurement of individual line-features without the lamella sampling. For instance, we make a-few-micrometer-wide and 45-degree-descending slope in dense line-features by using Focused Ion Beam (FIB) tool capable of 300mm-wafer. On the descending slope, obliquely cut cross-section of the line features appears. Then, we transfer the wafer to Critical-Dimension Secondary Electron Microscope (CDSEM) to measure the oblique cross-section in normal top-down view. As the descending angle is 45 degrees, the oblique cross-section looks like a cross-section normal to the wafer surface. For every single line-features the 3D dimensions are measured. To the reference metrology of the Scanning TEM (STEM), nanometric linearity and precision are confirmed for the height and the width under the hard mask of the line features. Without cleaving wafer the 60 cells on the wafer can be measured in 3 hours, which allows us of near-line process monitor of in-wafer uniformity.

  7. Quantitative analysis and feature recognition in 3-D microstructural data sets

    NASA Astrophysics Data System (ADS)

    Lewis, A. C.; Suh, C.; Stukowski, M.; Geltmacher, A. B.; Spanos, G.; Rajan, K.

    2006-12-01

    A three-dimensional (3-D) reconstruction of an austenitic stainless-steel microstructure was used as input for an image-based finite-element model to simulate the anisotropic elastic mechanical response of the microstructure. The quantitative data-mining and data-warehousing techniques used to correlate regions of high stress with critical microstructural features are discussed. Initial analysis of elastic stresses near grain boundaries due to mechanical loading revealed low overall correlation with their location in the microstructure. However, the use of data-mining and feature-tracking techniques to identify high-stress outliers revealed that many of these high-stress points are generated near grain boundaries and grain edges (triple junctions). These techniques also allowed for the differentiation between high stresses due to boundary conditions of the finite volume reconstructed, and those due to 3-D microstructural features.

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

    NASA Astrophysics Data System (ADS)

    Sierra, Heidy; Brooks, Dana; Dimarzio, Charles

    2010-07-01

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

  9. Computational Identification of Genomic Features That Influence 3D Chromatin Domain Formation

    PubMed Central

    Mourad, Raphaël; Cuvier, Olivier

    2016-01-01

    Recent advances in long-range Hi-C contact mapping have revealed the importance of the 3D structure of chromosomes in gene expression. A current challenge is to identify the key molecular drivers of this 3D structure. Several genomic features, such as architectural proteins and functional elements, were shown to be enriched at topological domain borders using classical enrichment tests. Here we propose multiple logistic regression to identify those genomic features that positively or negatively influence domain border establishment or maintenance. The model is flexible, and can account for statistical interactions among multiple genomic features. Using both simulated and real data, we show that our model outperforms enrichment test and non-parametric models, such as random forests, for the identification of genomic features that influence domain borders. Using Drosophila Hi-C data at a very high resolution of 1 kb, our model suggests that, among architectural proteins, BEAF-32 and CP190 are the main positive drivers of 3D domain borders. In humans, our model identifies well-known architectural proteins CTCF and cohesin, as well as ZNF143 and Polycomb group proteins as positive drivers of domain borders. The model also reveals the existence of several negative drivers that counteract the presence of domain borders including P300, RXRA, BCL11A and ELK1. PMID:27203237

  10. 3D Point Correspondence by Minimum Description Length in Feature Space.

    PubMed

    Chen, Jiun-Hung; Zheng, Ke Colin; Shapiro, Linda G

    2010-01-01

    Finding point correspondences plays an important role in automatically building statistical shape models from a training set of 3D surfaces. For the point correspondence problem, Davies et al. [1] proposed a minimum-description-length-based objective function to balance the training errors and generalization ability. A recent evaluation study [2] that compares several well-known 3D point correspondence methods for modeling purposes shows that the MDL-based approach [1] is the best method. We adapt the MDL-based objective function for a feature space that can exploit nonlinear properties in point correspondences, and propose an efficient optimization method to minimize the objective function directly in the feature space, given that the inner product of any vector pair can be computed in the feature space. We further employ a Mercer kernel [3] to define the feature space implicitly. A key aspect of our proposed framework is the generalization of the MDL-based objective function to kernel principal component analysis (KPCA) [4] spaces and the design of a gradient-descent approach to minimize such an objective function. We compare the generalized MDL objective function on KPCA spaces with the original one and evaluate their abilities in terms of reconstruction errors and specificity. From our experimental results on different sets of 3D shapes of human body organs, the proposed method performs significantly better than the original method. PMID:25328917

  11. Novel multiresolution mammographic density segmentation using pseudo 3D features and adaptive cluster merging

    NASA Astrophysics Data System (ADS)

    He, Wenda; Juette, Arne; Denton, Erica R. E.; Zwiggelaar, Reyer

    2015-03-01

    Breast cancer is the most frequently diagnosed cancer in women. Early detection, precise identification of women at risk, and application of appropriate disease prevention measures are by far the most effective ways to overcome the disease. Successful mammographic density segmentation is a key aspect in deriving correct tissue composition, ensuring an accurate mammographic risk assessment. However, mammographic densities have not yet been fully incorporated with non-image based risk prediction models, (e.g. the Gail and the Tyrer-Cuzick model), because of unreliable segmentation consistency and accuracy. This paper presents a novel multiresolution mammographic density segmentation, a concept of stack representation is proposed, and 3D texture features were extracted by adapting techniques based on classic 2D first-order statistics. An unsupervised clustering technique was employed to achieve mammographic segmentation, in which two improvements were made; 1) consistent segmentation by incorporating an optimal centroids initialisation step, and 2) significantly reduced the number of missegmentation by using an adaptive cluster merging technique. A set of full field digital mammograms was used in the evaluation. Visual assessment indicated substantial improvement on segmented anatomical structures and tissue specific areas, especially in low mammographic density categories. The developed method demonstrated an ability to improve the quality of mammographic segmentation via clustering, and results indicated an improvement of 26% in segmented image with good quality when compared with the standard clustering approach. This in turn can be found useful in early breast cancer detection, risk-stratified screening, and aiding radiologists in the process of decision making prior to surgery and/or treatment.

  12. The Extraction of 3D Shape from Texture and Shading in the Human Brain

    PubMed Central

    Georgieva, Svetlana S.; Todd, James T.; Peeters, Ronald

    2008-01-01

    We used functional magnetic resonance imaging to investigate the human cortical areas involved in processing 3-dimensional (3D) shape from texture (SfT) and shading. The stimuli included monocular images of randomly shaped 3D surfaces and a wide variety of 2-dimensional (2D) controls. The results of both passive and active experiments reveal that the extraction of 3D SfT involves the bilateral caudal inferior temporal gyrus (caudal ITG), lateral occipital sulcus (LOS) and several bilateral sites along the intraparietal sulcus. These areas are largely consistent with those involved in the processing of 3D shape from motion and stereo. The experiments also demonstrate, however, that the analysis of 3D shape from shading is primarily restricted to the caudal ITG areas. Additional results from psychophysical experiments reveal that this difference in neuronal substrate cannot be explained by a difference in strength between the 2 cues. These results underscore the importance of the posterior part of the lateral occipital complex for the extraction of visual 3D shape information from all depth cues, and they suggest strongly that the importance of shading is diminished relative to other cues for the analysis of 3D shape in parietal regions. PMID:18281304

  13. Changes in quantitative 3D shape features of the optic nerve head associated with age

    NASA Astrophysics Data System (ADS)

    Christopher, Mark; Tang, Li; Fingert, John H.; Scheetz, Todd E.; Abramoff, Michael D.

    2013-02-01

    Optic nerve head (ONH) structure is an important biological feature of the eye used by clinicians to diagnose and monitor progression of diseases such as glaucoma. ONH structure is commonly examined using stereo fundus imaging or optical coherence tomography. Stereo fundus imaging provides stereo views of the ONH that retain 3D information useful for characterizing structure. In order to quantify 3D ONH structure, we applied a stereo correspondence algorithm to a set of stereo fundus images. Using these quantitative 3D ONH structure measurements, eigen structures were derived using principal component analysis from stereo images of 565 subjects from the Ocular Hypertension Treatment Study (OHTS). To evaluate the usefulness of the eigen structures, we explored associations with the demographic variables age, gender, and race. Using regression analysis, the eigen structures were found to have significant (p < 0.05) associations with both age and race after Bonferroni correction. In addition, classifiers were constructed to predict the demographic variables based solely on the eigen structures. These classifiers achieved an area under receiver operating characteristic curve of 0.62 in predicting a binary age variable, 0.52 in predicting gender, and 0.67 in predicting race. The use of objective, quantitative features or eigen structures can reveal hidden relationships between ONH structure and demographics. The use of these features could similarly allow specific aspects of ONH structure to be isolated and associated with the diagnosis of glaucoma, disease progression and outcomes, and genetic factors.

  14. 3D laser scanning microscopy of hypervelocity impact features in metal and aerogel targets

    NASA Astrophysics Data System (ADS)

    Hillier, J. K.; Postberg, F.; Price, M. C.; Trieloff, M.; Li, Y. W.; Srama, R.

    2012-09-01

    We present the results of a study into the mapping of hypervelocity impact features using a Keyence VK-X200 3D laser scanning microscope. The impact features observed are impact craters in a variety of different metal targets (Al, Au and Cu) and impact tracks in aerogel targets, similar to those used in the Stardust mission. Differences in crater morphology between different target materials and impact velocities, as well as differences in track depth and diameter in aerogel, for particles of known constant dimensions, are discussed.

  15. Validate and update of 3D urban features using multi-source fusion

    NASA Astrophysics Data System (ADS)

    Arrington, Marcus; Edwards, Dan; Sengers, Arjan

    2012-06-01

    As forecast by the United Nations in May 2007, the population of the world transitioned from a rural to an urban demographic majority with more than half living in urban areas.1 Modern urban environments are complex 3- dimensional (3D) landscapes with 4-dimensional patterns of activity that challenge various traditional 1-dimensional and 2-dimensional sensors to accurately sample these man-made terrains. Depending on geographic location, data resulting from LIDAR, multi-spectral, electro-optical, thermal, ground-based static and mobile sensors may be available with multiple collects along with more traditional 2D GIS features. Reconciling differing data sources over time to correctly portray the dynamic urban landscape raises significant fusion and representational challenges particularly as higher levels of spatial resolution are available and expected by users. This paper presents a framework for integrating the imperfect answers of our differing sensors and data sources into a powerful representation of the complex urban environment. A case study is presented involving the integration of temporally diverse 2D, 2.5D and 3D spatial data sources over Kandahar, Afghanistan. In this case study we present a methodology for validating and augmenting 2D/2.5D urban feature and attribute data with LIDAR to produce validated 3D objects. We demonstrate that nearly 15% of buildings in Kandahar require understanding nearby vegetation before 3-D validation can be successful. We also address urban temporal change detection at the object level. Finally we address issues involved with increased sampling resolution since urban features are rarely simple cubes but in the case of Kandahar involve balconies, TV dishes, rooftop walls, small rooms, and domes among other things.

  16. Automatic detection of anatomical features on 3D ear impressions for canonical representation.

    PubMed

    Baloch, Sajjad; Melkisetoglu, Rupen; Flöry, Simon; Azernikov, Sergei; Slabaugh, Greg; Zouhar, Alexander; Fang, Tong

    2010-01-01

    We propose a shape descriptor for 3D ear impressions, derived from a comprehensive set of anatomical features. Motivated by hearing aid (HA) manufacturing, the selection of the anatomical features is carried out according to their uniqueness and importance in HA design. This leads to a canonical ear signature that is highly distinctive and potentially well suited for classification. First, the anatomical features are characterized into generic topological and geometric features, namely concavities, elbows, ridges, peaks, and bumps on the surface of the ear. Fast and robust algorithms are then developed for their detection. This indirect approach ensures the generality of the algorithms with potential applications in biomedicine, biometrics, and reverse engineering. PMID:20879444

  17. Avalanche for shape and feature-based virtual screening with 3D alignment.

    PubMed

    Diller, David J; Connell, Nancy D; Welsh, William J

    2015-11-01

    This report introduces a new ligand-based virtual screening tool called Avalanche that incorporates both shape- and feature-based comparison with three-dimensional (3D) alignment between the query molecule and test compounds residing in a chemical database. Avalanche proceeds in two steps. The first step is an extremely rapid shape/feature based comparison which is used to narrow the focus from potentially millions or billions of candidate molecules and conformations to a more manageable number that are then passed to the second step. The second step is a detailed yet still rapid 3D alignment of the remaining candidate conformations to the query conformation. Using the 3D alignment, these remaining candidate conformations are scored, re-ranked and presented to the user as the top hits for further visualization and evaluation. To provide further insight into the method, the results from two prospective virtual screens are presented which show the ability of Avalanche to identify hits from chemical databases that would likely be missed by common substructure-based or fingerprint-based search methods. The Avalanche method is extended to enable patent landscaping, i.e., structural refinements to improve the patentability of hits for deployment in drug discovery campaigns. PMID:26458937

  18. Hand Gesture Spotting Based on 3D Dynamic Features Using Hidden Markov Models

    NASA Astrophysics Data System (ADS)

    Elmezain, Mahmoud; Al-Hamadi, Ayoub; Michaelis, Bernd

    In this paper, we propose an automatic system that handles hand gesture spotting and recognition simultaneously in stereo color image sequences without any time delay based on Hidden Markov Models (HMMs). Color and 3D depth map are used to segment hand regions. The hand trajectory will determine in further step using Mean-shift algorithm and Kalman filter to generate 3D dynamic features. Furthermore, k-means clustering algorithm is employed for the HMMs codewords. To spot meaningful gestures accurately, a non-gesture model is proposed, which provides confidence limit for the calculated likelihood by other gesture models. The confidence measures are used as an adaptive threshold for spotting meaningful gestures. Experimental results show that the proposed system can successfully recognize isolated gestures with 98.33% and meaningful gestures with 94.35% reliability for numbers (0-9).

  19. Recognizing Objects in 3D Point Clouds with Multi-Scale Local Features

    PubMed Central

    Lu, Min; Guo, Yulan; Zhang, Jun; Ma, Yanxin; Lei, Yinjie

    2014-01-01

    Recognizing 3D objects from point clouds in the presence of significant clutter and occlusion is a highly challenging task. In this paper, we present a coarse-to-fine 3D object recognition algorithm. During the phase of offline training, each model is represented with a set of multi-scale local surface features. During the phase of online recognition, a set of keypoints are first detected from each scene. The local surfaces around these keypoints are further encoded with multi-scale feature descriptors. These scene features are then matched against all model features to generate recognition hypotheses, which include model hypotheses and pose hypotheses. Finally, these hypotheses are verified to produce recognition results. The proposed algorithm was tested on two standard datasets, with rigorous comparisons to the state-of-the-art algorithms. Experimental results show that our algorithm was fully automatic and highly effective. It was also very robust to occlusion and clutter. It achieved the best recognition performance on all of these datasets, showing its superiority compared to existing algorithms. PMID:25517694

  20. Recognizing objects in 3D point clouds with multi-scale local features.

    PubMed

    Lu, Min; Guo, Yulan; Zhang, Jun; Ma, Yanxin; Lei, Yinjie

    2014-01-01

    Recognizing 3D objects from point clouds in the presence of significant clutter and occlusion is a highly challenging task. In this paper, we present a coarse-to-fine 3D object recognition algorithm. During the phase of offline training, each model is represented with a set of multi-scale local surface features. During the phase of online recognition, a set of keypoints are first detected from each scene. The local surfaces around these keypoints are further encoded with multi-scale feature descriptors. These scene features are then matched against all model features to generate recognition hypotheses, which include model hypotheses and pose hypotheses. Finally, these hypotheses are verified to produce recognition results. The proposed algorithm was tested on two standard datasets, with rigorous comparisons to the state-of-the-art algorithms. Experimental results show that our algorithm was fully automatic and highly effective. It was also very robust to occlusion and clutter. It achieved the best recognition performance on all of these datasets, showing its superiority compared to existing algorithms. PMID:25517694

  1. Robust extraction of the aorta and pulmonary artery from 3D MDCT image data

    NASA Astrophysics Data System (ADS)

    Taeprasartsit, Pinyo; Higgins, William E.

    2010-03-01

    Accurate definition of the aorta and pulmonary artery from three-dimensional (3D) multi-detector CT (MDCT) images is important for pulmonary applications. This work presents robust methods for defining the aorta and pulmonary artery in the central chest. The methods work on both contrast enhanced and no-contrast 3D MDCT image data. The automatic methods use a common approach employing model fitting and selection and adaptive refinement. During the occasional event that more precise vascular extraction is desired or the method fails, we also have an alternate semi-automatic fail-safe method. The semi-automatic method extracts the vasculature by extending the medial axes into a user-guided direction. A ground-truth study over a series of 40 human 3D MDCT images demonstrates the efficacy, accuracy, robustness, and efficiency of the methods.

  2. Extension of RCC Topological Relations for 3d Complex Objects Components Extracted from 3d LIDAR Point Clouds

    NASA Astrophysics Data System (ADS)

    Xing, Xu-Feng; Abolfazl Mostafavia, Mir; Wang, Chen

    2016-06-01

    Topological relations are fundamental for qualitative description, querying and analysis of a 3D scene. Although topological relations for 2D objects have been extensively studied and implemented in GIS applications, their direct extension to 3D is very challenging and they cannot be directly applied to represent relations between components of complex 3D objects represented by 3D B-Rep models in R3. Herein we present an extended Region Connection Calculus (RCC) model to express and formalize topological relations between planar regions for creating 3D model represented by Boundary Representation model in R3. We proposed a new dimension extended 9-Intersection model to represent the basic relations among components of a complex object, including disjoint, meet and intersect. The last element in 3*3 matrix records the details of connection through the common parts of two regions and the intersecting line of two planes. Additionally, this model can deal with the case of planar regions with holes. Finally, the geometric information is transformed into a list of strings consisting of topological relations between two planar regions and detailed connection information. The experiments show that the proposed approach helps to identify topological relations of planar segments of point cloud automatically.

  3. Fast extraction of minimal paths in 3D images and applications to virtual endoscopy.

    PubMed

    Deschamps, T; Cohen, L D

    2001-12-01

    The aim of this article is to build trajectories for virtual endoscopy inside 3D medical images, using the most automatic way. Usually the construction of this trajectory is left to the clinician who must define some points on the path manually using three orthogonal views. But for a complex structure such as the colon, those views give little information on the shape of the object of interest. The path construction in 3D images becomes a very tedious task and precise a priori knowledge of the structure is needed to determine a suitable trajectory. We propose a more automatic path tracking method to overcome those drawbacks: we are able to build a path, given only one or two end points and the 3D image as inputs. This work is based on previous work by Cohen and Kimmel [Int. J. Comp. Vis. 24 (1) (1997) 57] for extracting paths in 2D images using Fast Marching algorithm. Our original contribution is twofold. On the first hand, we present a general technical contribution which extends minimal paths to 3D images and gives new improvements of the approach that are relevant in 2D as well as in 3D to extract linear structures in images. It includes techniques to make the path extraction scheme faster and easier, by reducing the user interaction. We also develop a new method to extract a centered path in tubular structures. Synthetic and real medical images are used to illustrate each contribution. On the other hand, we show that our method can be efficiently applied to the problem of finding a centered path in tubular anatomical structures with minimum interactivity, and that this path can be used for virtual endoscopy. Results are shown in various anatomical regions (colon, brain vessels, arteries) with different 3D imaging protocols (CT, MR). PMID:11731307

  4. Information based universal feature extraction

    NASA Astrophysics Data System (ADS)

    Amiri, Mohammad; Brause, Rüdiger

    2015-02-01

    In many real world image based pattern recognition tasks, the extraction and usage of task-relevant features are the most crucial part of the diagnosis. In the standard approach, they mostly remain task-specific, although humans who perform such a task always use the same image features, trained in early childhood. It seems that universal feature sets exist, but they are not yet systematically found. In our contribution, we tried to find those universal image feature sets that are valuable for most image related tasks. In our approach, we trained a neural network by natural and non-natural images of objects and background, using a Shannon information-based algorithm and learning constraints. The goal was to extract those features that give the most valuable information for classification of visual objects hand-written digits. This will give a good start and performance increase for all other image learning tasks, implementing a transfer learning approach. As result, in our case we found that we could indeed extract features which are valid in all three kinds of tasks.

  5. The RNA 3D Motif Atlas: Computational methods for extraction, organization and evaluation of RNA motifs.

    PubMed

    Parlea, Lorena G; Sweeney, Blake A; Hosseini-Asanjan, Maryam; Zirbel, Craig L; Leontis, Neocles B

    2016-07-01

    RNA 3D motifs occupy places in structured RNA molecules that correspond to the hairpin, internal and multi-helix junction "loops" of their secondary structure representations. As many as 40% of the nucleotides of an RNA molecule can belong to these structural elements, which are distinct from the regular double helical regions formed by contiguous AU, GC, and GU Watson-Crick basepairs. With the large number of atomic- or near atomic-resolution 3D structures appearing in a steady stream in the PDB/NDB structure databases, the automated identification, extraction, comparison, clustering and visualization of these structural elements presents an opportunity to enhance RNA science. Three broad applications are: (1) identification of modular, autonomous structural units for RNA nanotechnology, nanobiology and synthetic biology applications; (2) bioinformatic analysis to improve RNA 3D structure prediction from sequence; and (3) creation of searchable databases for exploring the binding specificities, structural flexibility, and dynamics of these RNA elements. In this contribution, we review methods developed for computational extraction of hairpin and internal loop motifs from a non-redundant set of high-quality RNA 3D structures. We provide a statistical summary of the extracted hairpin and internal loop motifs in the most recent version of the RNA 3D Motif Atlas. We also explore the reliability and accuracy of the extraction process by examining its performance in clustering recurrent motifs from homologous ribosomal RNA (rRNA) structures. We conclude with a summary of remaining challenges, especially with regard to extraction of multi-helix junction motifs. PMID:27125735

  6. Feature, design intention and constraint preservation for direct modeling of 3D freeform surfaces

    NASA Astrophysics Data System (ADS)

    Fu, Luoting; Kara, Levent Burak; Shimada, Kenji

    2012-06-01

    Direct modeling has recently emerged as a suitable approach for 3D free-form shape modeling in industrial design. It has several advantages over the conventional, parametric modeling techniques, including natural user interactions, as well as the underlying, automatic feature-preserving shape deformation algorithms. However, current direct modeling packages still lack several capabilities critical for product design, such as managing aesthetic design intentions, and enforcing dimensional, geometric constraints. In this paper, we describe a novel 3D surface editing system capable of jointly accommodating aesthetic design intentions expressed in the form of surface painting and color-coded annotations, as well as engineering constraints expressed as dimensions. The proposed system is built upon differential coordinates and constrained least squares, and is intended for conceptual design that involves frequent shape tuning and explorations. We also provide an extensive review of the state-of-the-art direct modeling approaches for 3D mesh-based, freeform surfaces, with an emphasis on the two broad categories of shape deformation algorithms developed in the relevant field of geometric modeling. [Figure not available: see fulltext.

  7. Visual Object Recognition with 3D-Aware Features in KITTI Urban Scenes.

    PubMed

    Yebes, J Javier; Bergasa, Luis M; García-Garrido, Miguel Ángel

    2015-01-01

    Driver assistance systems and autonomous robotics rely on the deployment of several sensors for environment perception. Compared to LiDAR systems, the inexpensive vision sensors can capture the 3D scene as perceived by a driver in terms of appearance and depth cues. Indeed, providing 3D image understanding capabilities to vehicles is an essential target in order to infer scene semantics in urban environments. One of the challenges that arises from the navigation task in naturalistic urban scenarios is the detection of road participants (e.g., cyclists, pedestrians and vehicles). In this regard, this paper tackles the detection and orientation estimation of cars, pedestrians and cyclists, employing the challenging and naturalistic KITTI images. This work proposes 3D-aware features computed from stereo color images in order to capture the appearance and depth peculiarities of the objects in road scenes. The successful part-based object detector, known as DPM, is extended to learn richer models from the 2.5D data (color and disparity), while also carrying out a detailed analysis of the training pipeline. A large set of experiments evaluate the proposals, and the best performing approach is ranked on the KITTI website. Indeed, this is the first work that reports results with stereo data for the KITTI object challenge, achieving increased detection ratios for the classes car and cyclist compared to a baseline DPM. PMID:25903553

  8. Visual Object Recognition with 3D-Aware Features in KITTI Urban Scenes

    PubMed Central

    Yebes, J. Javier; Bergasa, Luis M.; García-Garrido, Miguel Ángel

    2015-01-01

    Driver assistance systems and autonomous robotics rely on the deployment of several sensors for environment perception. Compared to LiDAR systems, the inexpensive vision sensors can capture the 3D scene as perceived by a driver in terms of appearance and depth cues. Indeed, providing 3D image understanding capabilities to vehicles is an essential target in order to infer scene semantics in urban environments. One of the challenges that arises from the navigation task in naturalistic urban scenarios is the detection of road participants (e.g., cyclists, pedestrians and vehicles). In this regard, this paper tackles the detection and orientation estimation of cars, pedestrians and cyclists, employing the challenging and naturalistic KITTI images. This work proposes 3D-aware features computed from stereo color images in order to capture the appearance and depth peculiarities of the objects in road scenes. The successful part-based object detector, known as DPM, is extended to learn richer models from the 2.5D data (color and disparity), while also carrying out a detailed analysis of the training pipeline. A large set of experiments evaluate the proposals, and the best performing approach is ranked on the KITTI website. Indeed, this is the first work that reports results with stereo data for the KITTI object challenge, achieving increased detection ratios for the classes car and cyclist compared to a baseline DPM. PMID:25903553

  9. Non-invasive 3D geometry extraction of a Sea lion foreflipper

    NASA Astrophysics Data System (ADS)

    Friedman, Chen; Watson, Martha; Zhang, Pamela; Leftwich, Megan

    2015-11-01

    We are interested in underwater propulsion that leaves little traceable wake structure while producing high levels of thrust. A potential biological model is the California sea lion, a highly maneuverable aquatic mammal that produces thrust primarily with its foreflippers without a characteristic flapping frequency. The foreflippers are used for thrust, stability, and control during swimming motions. Recently, the flipper's kinematics during the thrust phase was extracted using 2D video tracking. This work extends the tracking ability to 3D using a non-invasive Direct Linear Transformation technique employed on non-research sea lions. marker-less flipper tracking is carried out manually for complete dorsal-ventral flipper motions. Two cameras are used (3840 × 2160 pixels resolution), calibrated in space using a calibration target inserted into the sea lion habitat, and synchronized in time using a simple light flash. The repeatability and objectivity of the tracked data is assessed by having two people tracking the same clap and comparing the results. The number of points required to track a flipper with sufficient detail is also discussed. Changes in the flipper pitch angle during the clap, an important feature for fluid dynamics modeling, will also be presented.

  10. 3D reconstruction for sinusoidal motion based on different feature detection algorithms

    NASA Astrophysics Data System (ADS)

    Zhang, Peng; Zhang, Jin; Deng, Huaxia; Yu, Liandong

    2015-02-01

    The dynamic testing of structures and components is an important area of research. Extensive researches on the methods of using sensors for vibration parameters have been studied for years. With the rapid development of industrial high-speed camera and computer hardware, the method of using stereo vision for dynamic testing has been the focus of the research since the advantages of non-contact, full-field, high resolution and high accuracy. But in the country there is not much research about the dynamic testing based on stereo vision, and yet few people publish articles about the three-dimensional (3D) reconstruction of feature points in the case of dynamic. It is essential to the following analysis whether it can obtain accurate movement of target objects. In this paper, an object with sinusoidal motion is detected by stereo vision and the accuracy with different feature detection algorithms is investigated. Three different marks including dot, square and circle are stuck on the object and the object is doing sinusoidal motion by vibration table. Then use feature detection algorithm speed-up robust feature (SURF) to detect point, detect square corners by Harris and position the center by Hough transform. After obtaining the pixel coordinate values of the feature point, the stereo calibration parameters are used to achieve three-dimensional reconstruction through triangulation principle. The trajectories of the specific direction according to the vibration frequency and the frequency camera acquisition are obtained. At last, the reconstruction accuracy of different feature detection algorithms is compared.

  11. 3D CAD model retrieval method based on hierarchical multi-features

    NASA Astrophysics Data System (ADS)

    An, Ran; Wang, Qingwen

    2015-12-01

    The classical "Shape Distribution D2" algorithm takes the distance between two random points on a surface of CAD model as statistical features, and based on that it generates a feature vector to calculate the dissimilarity and achieve the retrieval goal. This algorithm has a simple principle, high computational efficiency and can get a better retrieval results for the simple shape models. Based on the analysis of D2 algorithm's shape distribution curve, this paper enhances the algorithm's descriptive ability for a model's overall shape through the statistics of the angle between two random points' normal vectors, especially for the distinctions between the model's plane features and curved surface features; meanwhile, introduce the ratio that a line between two random points cut off by the model's surface to enhance the algorithm's descriptive ability for a model's detailed features; finally, integrating the two shape describing methods with the original D2 algorithm, this paper proposes a new method based the hierarchical multi-features. Experimental results showed that this method has bigger improvements and could get a better retrieval results compared with the traditional 3D CAD model retrieval method.

  12. EXTRACTING A RADAR REFLECTION FROM A CLUTTERED ENVIRONMENT USING 3-D INTERPRETATION

    EPA Science Inventory

    A 3-D Ground Penetrating Radar (GPR) survey at 50 MHz center frequency was conducted at Hill Air Force Base, Utah, to define the topography of the base of a shallow aquifer. The site for the survey was Chemical Disposal Pit #2 where there are many man-made features that generate ...

  13. The Wavelet Element Method. Part 2; Realization and Additional Features in 2D and 3D

    NASA Technical Reports Server (NTRS)

    Canuto, Claudio; Tabacco, Anita; Urban, Karsten

    1998-01-01

    The Wavelet Element Method (WEM) provides a construction of multiresolution systems and biorthogonal wavelets on fairly general domains. These are split into subdomains that are mapped to a single reference hypercube. Tensor products of scaling functions and wavelets defined on the unit interval are used on the reference domain. By introducing appropriate matching conditions across the interelement boundaries, a globally continuous biorthogonal wavelet basis on the general domain is obtained. This construction does not uniquely define the basis functions but rather leaves some freedom for fulfilling additional features. In this paper we detail the general construction principle of the WEM to the 1D, 2D and 3D cases. We address additional features such as symmetry, vanishing moments and minimal support of the wavelet functions in each particular dimension. The construction is illustrated by using biorthogonal spline wavelets on the interval.

  14. Combining chemical sequential extractions with 3D fluorescence spectroscopy to characterize sludge organic matter.

    PubMed

    Muller, Mathieu; Jimenez, Julie; Antonini, Maxime; Dudal, Yves; Latrille, Eric; Vedrenne, Fabien; Steyer, Jean-Philippe; Patureau, Dominique

    2014-12-01

    The design and management of anaerobic digestion of sewage sludge (SS) require a relevant characterisation of the sludge organic matter (OM). Methods currently used are time-consuming and often insufficiently informative. A new method combining chemical sequential extractions (CSE) with 3D fluorescence spectroscopy was developed to provide a relevant SS characterisation to assess both OM bioaccessibility and complexity which govern SS biodegradability. CSE fractionates the sludge OM into 5 compartments of decreasing accessibility. First applied on three SS samples with different OM stability, fractionation profiles obtained were in accordance with the latter. 3D fluorescence spectroscopy revealed that the bioaccessible compartments were mainly constituted of simple and easily biodegradable OM while the unaccessible ones were largely made of complex and refractory OM. Then, primary, secondary and anaerobically digested sludge with different biodegradabilities were tested. Complexity revealed by 3D fluorescence spectroscopy was linked with biodegradability and chemical accessibility was correlated with sludge bioaccessibility. PMID:25223440

  15. Evaluation of feature-based 3-d registration of probabilistic volumetric scenes

    NASA Astrophysics Data System (ADS)

    Restrepo, Maria I.; Ulusoy, Ali O.; Mundy, Joseph L.

    2014-12-01

    Automatic estimation of the world surfaces from aerial images has seen much attention and progress in recent years. Among current modeling technologies, probabilistic volumetric models (PVMs) have evolved as an alternative representation that can learn geometry and appearance in a dense and probabilistic manner. Recent progress, in terms of storage and speed, achieved in the area of volumetric modeling, opens the opportunity to develop new frameworks that make use of the PVM to pursue the ultimate goal of creating an entire map of the earth, where one can reason about the semantics and dynamics of the 3-d world. Aligning 3-d models collected at different time-instances constitutes an important step for successful fusion of large spatio-temporal information. This paper evaluates how effectively probabilistic volumetric models can be aligned using robust feature-matching techniques, while considering different scenarios that reflect the kind of variability observed across aerial video collections from different time instances. More precisely, this work investigates variability in terms of discretization, resolution and sampling density, errors in the camera orientation, and changes in illumination and geographic characteristics. All results are given for large-scale, outdoor sites. In order to facilitate the comparison of the registration performance of PVMs to that of other 3-d reconstruction techniques, the registration pipeline is also carried out using Patch-based Multi-View Stereo (PMVS) algorithm. Registration performance is similar for scenes that have favorable geometry and the appearance characteristics necessary for high quality reconstruction. In scenes containing trees, such as a park, or many buildings, such as a city center, registration performance is significantly more accurate when using the PVM.

  16. Galaxy Classification without Feature Extraction

    NASA Astrophysics Data System (ADS)

    Polsterer, K. L.; Gieseke, F.; Kramer, O.

    2012-09-01

    The automatic classification of galaxies according to the different Hubble types is a widely studied problem in the field of astronomy. The complexity of this task led to projects like Galaxy Zoo which try to obtain labeled data based on visual inspection by humans. Many automatic classification frameworks are based on artificial neural networks (ANN) in combination with a feature extraction step in the pre-processing phase. These approaches rely on labeled catalogs for training the models. The small size of the typically used training sets, however, limits the generalization performance of the resulting models. In this work, we present a straightforward application of support vector machines (SVM) for this type of classification tasks. The conducted experiments indicate that using a sufficient number of labeled objects provided by the EFIGI catalog leads to high-quality models. In contrast to standard approaches no additional feature extraction is required.

  17. A stochastic model for automatic extraction of 3D neuronal morphology.

    PubMed

    Basu, Sreetama; Kulikova, Maria; Zhizhina, Elena; Ooi, Wei Tsang; Racoceanu, Daniel

    2013-01-01

    Tubular structures are frequently encountered in bio-medical images. The center-lines of these tubules provide an accurate representation of the topology of the structures. We introduce a stochastic Marked Point Process framework for fully automatic extraction of tubular structures requiring no user interaction or seed points for initialization. Our Marked Point Process model enables unsupervised network extraction by fitting a configuration of objects with globally optimal associated energy to the centreline of the arbors. For this purpose we propose special configurations of marked objects and an energy function well adapted for detection of 3D tubular branches. The optimization of the energy function is achieved by a stochastic, discrete-time multiple birth and death dynamics. Our method finds the centreline, local width and orientation of neuronal arbors and identifies critical nodes like bifurcations and terminals. The proposed model is tested on 3D light microscopy images from the DIADEM data set with promising results. PMID:24505691

  18. Robust method for extracting the pulmonary vascular trees from 3D MDCT images

    NASA Astrophysics Data System (ADS)

    Taeprasartsit, Pinyo; Higgins, William E.

    2011-03-01

    Segmentation of pulmonary blood vessels from three-dimensional (3D) multi-detector CT (MDCT) images is important for pulmonary applications. This work presents a method for extracting the vascular trees of the pulmonary arteries and veins, applicable to both contrast-enhanced and unenhanced 3D MDCT image data. The method finds 2D elliptical cross-sections and evaluates agreement of these cross-sections in consecutive slices to find likely cross-sections. It next employs morphological multiscale analysis to separate vessels from adjoining airway walls. The method then tracks the center of the likely cross-sections to connect them to the pulmonary vessels in the mediastinum and forms connected vascular trees spanning both lungs. A ground-truth study indicates that the method was able to detect on the order of 98% of the vessel branches having diameter >= 3.0 mm. The extracted vascular trees can be utilized for the guidance of safe bronchoscopic biopsy.

  19. Extracting Semantically Annotated 3d Building Models with Textures from Oblique Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Frommholz, D.; Linkiewicz, M.; Meissner, H.; Dahlke, D.; Poznanska, A.

    2015-03-01

    This paper proposes a method for the reconstruction of city buildings with automatically derived textures that can be directly used for façade element classification. Oblique and nadir aerial imagery recorded by a multi-head camera system is transformed into dense 3D point clouds and evaluated statistically in order to extract the hull of the structures. For the resulting wall, roof and ground surfaces high-resolution polygonal texture patches are calculated and compactly arranged in a texture atlas without resampling. The façade textures subsequently get analyzed by a commercial software package to detect possible windows whose contours are projected into the original oriented source images and sparsely ray-casted to obtain their 3D world coordinates. With the windows being reintegrated into the previously extracted hull the final building models are stored as semantically annotated CityGML "LOD-2.5" objects.

  20. The Learner Characteristics, Features of Desktop 3D Virtual Reality Environments, and College Chemistry Instruction: A Structural Equation Modeling Analysis

    ERIC Educational Resources Information Center

    Merchant, Zahira; Goetz, Ernest T.; Keeney-Kennicutt, Wendy; Kwok, Oi-man; Cifuentes, Lauren; Davis, Trina J.

    2012-01-01

    We examined a model of the impact of a 3D desktop virtual reality environment on the learner characteristics (i.e. perceptual and psychological variables) that can enhance chemistry-related learning achievements in an introductory college chemistry class. The relationships between the 3D virtual reality features and the chemistry learning test as…

  1. Registration of Feature-Poor 3D Measurements from Fringe Projection

    PubMed Central

    von Enzberg, Sebastian; Al-Hamadi, Ayoub; Ghoneim, Ahmed

    2016-01-01

    We propose a novel method for registration of partly overlapping three-dimensional surface measurements for stereo-based optical sensors using fringe projection. Based on two-dimensional texture matching, it allows global registration of surfaces with poor and ambiguous three-dimensional features, which are common to surface inspection applications. No prior information about relative sensor position is necessary, which makes our approach suitable for semi-automatic and manual measurement. The algorithm is robust and works with challenging measurements, including uneven illumination, surfaces with specular reflection as well as sparsely textured surfaces. We show that precisions of 1 mm and below can be achieved along the surfaces, which is necessary for further local 3D registration. PMID:26927106

  2. Registration of Feature-Poor 3D Measurements from Fringe Projection.

    PubMed

    von Enzberg, Sebastian; Al-Hamadi, Ayoub; Ghoneim, Ahmed

    2016-01-01

    We propose a novel method for registration of partly overlapping three-dimensional surface measurements for stereo-based optical sensors using fringe projection. Based on two-dimensional texture matching, it allows global registration of surfaces with poor and ambiguous three-dimensional features, which are common to surface inspection applications. No prior information about relative sensor position is necessary, which makes our approach suitable for semi-automatic and manual measurement. The algorithm is robust and works with challenging measurements, including uneven illumination, surfaces with specular reflection as well as sparsely textured surfaces. We show that precisions of 1 mm and below can be achieved along the surfaces, which is necessary for further local 3D registration. PMID:26927106

  3. 3D SMoSIFT: three-dimensional sparse motion scale invariant feature transform for activity recognition from RGB-D videos

    NASA Astrophysics Data System (ADS)

    Wan, Jun; Ruan, Qiuqi; Li, Wei; An, Gaoyun; Zhao, Ruizhen

    2014-03-01

    Human activity recognition based on RGB-D data has received more attention in recent years. We propose a spatiotemporal feature named three-dimensional (3D) sparse motion scale-invariant feature transform (SIFT) from RGB-D data for activity recognition. First, we build pyramids as scale space for each RGB and depth frame, and then use Shi-Tomasi corner detector and sparse optical flow to quickly detect and track robust keypoints around the motion pattern in the scale space. Subsequently, local patches around keypoints, which are extracted from RGB-D data, are used to build 3D gradient and motion spaces. Then SIFT-like descriptors are calculated on both 3D spaces, respectively. The proposed feature is invariant to scale, transition, and partial occlusions. More importantly, the running time of the proposed feature is fast so that it is well-suited for real-time applications. We have evaluated the proposed feature under a bag of words model on three public RGB-D datasets: one-shot learning Chalearn Gesture Dataset, Cornell Activity Dataset-60, and MSR Daily Activity 3D dataset. Experimental results show that the proposed feature outperforms other spatiotemporal features and are comparative to other state-of-the-art approaches, even though there is only one training sample for each class.

  4. 3-D modeling useful tool for planning. [mapping groundwater and soil pollution and subsurface features

    SciTech Connect

    Calmbacher, C.W. )

    1992-12-01

    Visualizing and delineating subsurface geological features, groundwater contaminant plumes, soil contamination, geological faults, shears and other features can prove invaluable to environmental consultants, engineers, geologists and hydrogeologists. Three-dimensional modeling is useful for a variety of applications from planning remediation to site planning design. The problem often is figuring out how to convert drilling logs, map lists or contaminant levels from soil and groundwater into a 3-D model. Three-dimensional subsurface modeling is not a new requirement, but a flexible, easily applied method of developing such models has not always been readily available. LYNX Geosystems Inc. has developed the Geoscience Modeling System (GMS) in answer to the needs of those regularly having to do three-dimensional geostatistical modeling. The GMS program has been designed to allow analysis, interpretation and visualization of complex geological features and soil and groundwater contamination. This is a powerful program driven by a 30 volume modeling technology engine. Data can be entered, stored, manipulated and analyzed in ways that will present very few limitations to the user. The program has selections for Geoscience Data Management, Geoscience Data Analysis, Geological Modeling (interpretation and analysis), Geostatistical Modeling and an optional engineering component.

  5. Visualizing and Tracking Evolving Features in 3D Unstructured and Adaptive Datasets

    SciTech Connect

    Silver, D.; Zabusky, N.

    2002-08-01

    The massive amounts of time-varying datasets being generated demand new visualization and quantification techniques. Visualization alone is not sufficient. Without proper measurement information/computations real science cannot be done. Our focus is this work was to combine visualization with quantification of the data to allow for advanced querying and searching. As part of this proposal, we have developed a feature extraction adn tracking methodology which allows researcher to identify features of interest and follow their evolution over time. The implementation is distributed and operates over data In-situ: where it is stored and when it was computed.

  6. Fully 3D-Printed Preconcentrator for Selective Extraction of Trace Elements in Seawater.

    PubMed

    Su, Cheng-Kuan; Peng, Pei-Jin; Sun, Yuh-Chang

    2015-07-01

    In this study, we used a stereolithographic 3D printing technique and polyacrylate polymers to manufacture a solid phase extraction preconcentrator for the selective extraction of trace elements and the removal of unwanted salt matrices, enabling accurate and rapid analyses of trace elements in seawater samples when combined with a quadrupole-based inductively coupled plasma mass spectrometer. To maximize the extraction efficiency, we evaluated the effect of filling the extraction channel with ordered cuboids to improve liquid mixing. Upon automation of the system and optimization of the method, the device allowed highly sensitive and interference-free determination of Mn, Ni, Zn, Cu, Cd, and Pb, with detection limits comparable with those of most conventional methods. The system's analytical reliability was further confirmed through analyses of reference materials and spike analyses of real seawater samples. This study suggests that 3D printing can be a powerful tool for building multilayer fluidic manipulation devices, simplifying the construction of complex experimental components, and facilitating the operation of sophisticated analytical procedures for most sample pretreatment applications. PMID:26101898

  7. Form feature and tolerance transfer from a 3D model to a setup planning system

    SciTech Connect

    Zhang, Hong-Chao; Zhou, Feng; Kuo, Tsai-Chi; Huang, S.H.

    1996-12-31

    Currently, most CAD systems, even the feature-based design systems which were developed for the need of CAPP, cannot provide exact information of an object (e.g., dimensions and tolerances). Some feature-based design systems can provide product data directly or indirectly; however, most CAPP systems still does not have interface with those CAD systems. The product data required by these CAPP systems usually has a specific format. In the CAPP system, it is essential for setup planning to ensure the precision of machining processes. Therefore, it is necessary to develop an interface with CAD models that the part data file can be obtained directly from CAD representation. This paper proposes an approach to integrate the setup planning system with a feature-based CAD system. By using an object-oriented approach - Product Data Translator (PDT), the compute-automated extraction of geometry and complete tolerance information is achieved; and the automated generation of tool approach direction was developed.

  8. Automated Extraction of Flow Features

    NASA Technical Reports Server (NTRS)

    Dorney, Suzanne (Technical Monitor); Haimes, Robert

    2005-01-01

    Computational Fluid Dynamics (CFD) simulations are routinely performed as part of the design process of most fluid handling devices. In order to efficiently and effectively use the results of a CFD simulation, visualization tools are often used. These tools are used in all stages of the CFD simulation including pre-processing, interim-processing, and post-processing, to interpret the results. Each of these stages requires visualization tools that allow one to examine the geometry of the device, as well as the partial or final results of the simulation. An engineer will typically generate a series of contour and vector plots to better understand the physics of how the fluid is interacting with the physical device. Of particular interest are detecting features such as shocks, re-circulation zones, and vortices (which will highlight areas of stress and loss). As the demand for CFD analyses continues to increase the need for automated feature extraction capabilities has become vital. In the past, feature extraction and identification were interesting concepts, but not required in understanding the physics of a steady flow field. This is because the results of the more traditional tools like; isc-surface, cuts and streamlines, were more interactive and easily abstracted so they could be represented to the investigator. These tools worked and properly conveyed the collected information at the expense of a great deal of interaction. For unsteady flow-fields, the investigator does not have the luxury of spending time scanning only one "snapshot" of the simulation. Automated assistance is required in pointing out areas of potential interest contained within the flow. This must not require a heavy compute burden (the visualization should not significantly slow down the solution procedure for co-processing environments). Methods must be developed to abstract the feature of interest and display it in a manner that physically makes sense.

  9. Automated Extraction of Flow Features

    NASA Technical Reports Server (NTRS)

    Dorney, Suzanne (Technical Monitor); Haimes, Robert

    2004-01-01

    Computational Fluid Dynamics (CFD) simulations are routinely performed as part of the design process of most fluid handling devices. In order to efficiently and effectively use the results of a CFD simulation, visualization tools are often used. These tools are used in all stages of the CFD simulation including pre-processing, interim-processing, and post-processing, to interpret the results. Each of these stages requires visualization tools that allow one to examine the geometry of the device, as well as the partial or final results of the simulation. An engineer will typically generate a series of contour and vector plots to better understand the physics of how the fluid is interacting with the physical device. Of particular interest are detecting features such as shocks, recirculation zones, and vortices (which will highlight areas of stress and loss). As the demand for CFD analyses continues to increase the need for automated feature extraction capabilities has become vital. In the past, feature extraction and identification were interesting concepts, but not required in understanding the physics of a steady flow field. This is because the results of the more traditional tools like; iso-surface, cuts and streamlines, were more interactive and easily abstracted so they could be represented to the investigator. These tools worked and properly conveyed the collected information at the expense of a great deal of interaction. For unsteady flow-fields, the investigator does not have the luxury of spending time scanning only one "snapshot" of the simulation. Automated assistance is required in pointing out areas of potential interest contained within the flow. This must not require a heavy compute burden (the visualization should not significantly slow down the solution procedure for (co-processing environments). Methods must be developed to abstract the feature of interest and display it in a manner that physically makes sense.

  10. Carboxy-Methyl-Cellulose (CMC) hydrogel-filled 3-D scaffold: Preliminary study through a 3-D antiproliferative activity of Centella asiatica extract

    NASA Astrophysics Data System (ADS)

    Aizad, Syazwan; Yahaya, Badrul Hisham; Zubairi, Saiful Irwan

    2015-09-01

    This study focuses on the effects of using the water extract from Centella asiatica on the mortality of human lung cancer cells (A549) with the use of novel 3-D scaffolds infused with CMC hydrogel. A biodegradable polymer, poly (hydroxybutyrate-co-hydroxyvalerate) (PHBV) was used in this study as 3-D scaffolds, with some modifications made by introducing the gel structure on its pore, which provides a great biomimetic microenvironment for cells to grow apart from increasing the interaction between the cells and cell-bioactive extracts. The CMC showed a good hydrophilic characteristic with mean contact angle of 24.30 ± 22.03°. To ensure the CMC gel had good attachments with the scaffolds, a surface treatment was made before the CMC gel was infused into the scaffolds. The results showed that these modified scaffolds contained 42.41 ± 0.14% w/w of CMC gel, which indicated that the gel had already filled up the entire pore of 3-D scaffolds. Besides, the infused hydrogel scaffolds took only 24 hours to be saturated when absorbing the water. The viability of cancer cells by MTS assay after being treated with Centella asiatica showed that the scaffolds infused with CMC hydrogel had the cell viability of 46.89 ± 1.20% followed by porous 3-D model with 57.30 ± 1.60% of cell viability, and the 2-D model with 67.10 ± 1.10% of cell viability. The inhibitory activity in cell viability between 2-D and 3-D models did not differ significantly (p>0.05) due to the limitation of time in incubating the extract with the cell in the 3-D model microenvironment. In conclusion, with the application of 3-D scaffolds infused with CMC hydrogel, the extracts of Centella asiatica has been proven to have the ability to kill cancer cells and have a great potential to become one of the alternative methods in treating cancer patients.

  11. An intelligent recovery progress evaluation system for ACL reconstructed subjects using integrated 3-D kinematics and EMG features.

    PubMed

    Malik, Owais A; Senanayake, S M N Arosha; Zaheer, Dansih

    2015-03-01

    An intelligent recovery evaluation system is presented for objective assessment and performance monitoring of anterior cruciate ligament reconstructed (ACL-R) subjects. The system acquires 3-D kinematics of tibiofemoral joint and electromyography (EMG) data from surrounding muscles during various ambulatory and balance testing activities through wireless body-mounted inertial and EMG sensors, respectively. An integrated feature set is generated based on different features extracted from data collected for each activity. The fuzzy clustering and adaptive neuro-fuzzy inference techniques are applied to these integrated feature sets in order to provide different recovery progress assessment indicators (e.g., current stage of recovery, percentage of recovery progress as compared to healthy group, etc.) for ACL-R subjects. The system was trained and tested on data collected from a group of healthy and ACL-R subjects. For recovery stage identification, the average testing accuracy of the system was found above 95% (95-99%) for ambulatory activities and above 80% (80-84%) for balance testing activities. The overall recovery evaluation performed by the proposed system was found consistent with the assessment made by the physiotherapists using standard subjective/objective scores. The validated system can potentially be used as a decision supporting tool by physiatrists, physiotherapists, and clinicians for quantitative rehabilitation analysis of ACL-R subjects in conjunction with the existing recovery monitoring systems. PMID:24801517

  12. 3-D visualisation and interpretation of seismic attributes extracted from large 3-D seismic datasets: Subregional and prospect evaluation, deepwater Nigeria

    SciTech Connect

    Sola, M.; Haakon Nordby, L.; Dailey, D.V.; Duncan, E.A. )

    1996-01-01

    High resolution 3-D visualization of horizon interpretation and seismic attributes from large 3-D seismic surveys in deepwater Nigeria has greatly enhanced the exploration team's ability to quickly recognize prospective segments of subregional and prospect specific scale areas. Integrated workstation generated structure, isopach and extracted horizon consistent, interval and windowed attributes are particularly useful in illustrating the complex structural and stratigraphical prospectivity of deepwater Nigeria. Large 3-D seismic volumes acquired over 750 square kilometers can be manipulated within the visualization system with attribute tracking capability that allows for real time data interrogation and interpretation. As in classical seismic stratigraphic studies, pattern recognition is fundamental to effective depositions facies interpretation and reservoir model construction. The 3-D perspective enhances the data interpretation through clear representation of relative scale, spatial distribution and magnitude of attributes. In deepwater Nigeria, many prospective traps rely on an interplay between syndepositional structure and slope turbidite depositional systems. Reservoir systems in many prospects appear to be dominated by unconfined to moderately focused slope feeder channel facies. These units have spatially complex facies architecture with feeder channel axes separated by extensive interchannel areas. Structural culminations generally have a history of initial compressional folding with late in extensional collapse and accommodation faulting. The resulting complex trap configurations often have stacked reservoirs over intervals as thick as 1500 meters. Exploration, appraisal and development scenarios in these settings can be optimized by taking full advantage of integrating high resolution 3-D visualization and seismic workstation interpretation.

  13. 3-D visualisation and interpretation of seismic attributes extracted from large 3-D seismic datasets: Subregional and prospect evaluation, deepwater Nigeria

    SciTech Connect

    Sola, M.; Haakon Nordby, L.; Dailey, D.V.; Duncan, E.A.

    1996-12-31

    High resolution 3-D visualization of horizon interpretation and seismic attributes from large 3-D seismic surveys in deepwater Nigeria has greatly enhanced the exploration team`s ability to quickly recognize prospective segments of subregional and prospect specific scale areas. Integrated workstation generated structure, isopach and extracted horizon consistent, interval and windowed attributes are particularly useful in illustrating the complex structural and stratigraphical prospectivity of deepwater Nigeria. Large 3-D seismic volumes acquired over 750 square kilometers can be manipulated within the visualization system with attribute tracking capability that allows for real time data interrogation and interpretation. As in classical seismic stratigraphic studies, pattern recognition is fundamental to effective depositions facies interpretation and reservoir model construction. The 3-D perspective enhances the data interpretation through clear representation of relative scale, spatial distribution and magnitude of attributes. In deepwater Nigeria, many prospective traps rely on an interplay between syndepositional structure and slope turbidite depositional systems. Reservoir systems in many prospects appear to be dominated by unconfined to moderately focused slope feeder channel facies. These units have spatially complex facies architecture with feeder channel axes separated by extensive interchannel areas. Structural culminations generally have a history of initial compressional folding with late in extensional collapse and accommodation faulting. The resulting complex trap configurations often have stacked reservoirs over intervals as thick as 1500 meters. Exploration, appraisal and development scenarios in these settings can be optimized by taking full advantage of integrating high resolution 3-D visualization and seismic workstation interpretation.

  14. Voxel-Based 3-D Tree Modeling from Lidar Images for Extracting Tree Structual Information

    NASA Astrophysics Data System (ADS)

    Hosoi, F.

    2014-12-01

    Recently, lidar (light detection and ranging) has been used to extracting tree structural information. Portable scanning lidar systems can capture the complex shape of individual trees as a 3-D point-cloud image. 3-D tree models reproduced from the lidar-derived 3-D image can be used to estimate tree structural parameters. We have proposed the voxel-based 3-D modeling for extracting tree structural parameters. One of the tree parameters derived from the voxel modeling is leaf area density (LAD). We refer to the method as the voxel-based canopy profiling (VCP) method. In this method, several measurement points surrounding the canopy and optimally inclined laser beams are adopted for full laser beam illumination of whole canopy up to the internal. From obtained lidar image, the 3-D information is reproduced as the voxel attributes in the 3-D voxel array. Based on the voxel attributes, contact frequency of laser beams on leaves is computed and LAD in each horizontal layer is obtained. This method offered accurate LAD estimation for individual trees and woody canopy trees. For more accurate LAD estimation, the voxel model was constructed by combining airborne and portable ground-based lidar data. The profiles obtained by the two types of lidar complemented each other, thus eliminating blind regions and yielding more accurate LAD profiles than could be obtained by using each type of lidar alone. Based on the estimation results, we proposed an index named laser beam coverage index, Ω, which relates to the lidar's laser beam settings and a laser beam attenuation factor. It was shown that this index can be used for adjusting measurement set-up of lidar systems and also used for explaining the LAD estimation error using different types of lidar systems. Moreover, we proposed a method to estimate woody material volume as another application of the voxel tree modeling. In this method, voxel solid model of a target tree was produced from the lidar image, which is composed of

  15. TU-F-12A-05: Sensitivity of Textural Features to 3D Vs. 4D FDG-PET/CT Imaging in NSCLC Patients

    SciTech Connect

    Yang, F; Nyflot, M; Bowen, S; Kinahan, P; Sandison, G

    2014-06-15

    Purpose: Neighborhood Gray-level difference matrices (NGLDM) based texture parameters extracted from conventional (3D) 18F-FDG PET scans in patients with NSCLC have been previously shown to associate with response to chemoradiation and poorer patient outcome. However, the change in these parameters when utilizing respiratory-correlated (4D) FDG-PET scans has not yet been characterized for NSCLC. The Objectives: of this study was to assess the extent to which NGLDM-based texture parameters on 4D PET images vary with reference to values derived from 3D scans in NSCLC. Methods: Eight patients with newly diagnosed NSCLC treated with concomitant chemoradiotherapy were included in this study. 4D PET scans were reconstructed with OSEM-IR in 5 respiratory phase-binned images and corresponding CT data of each phase were employed for attenuation correction. NGLDM-based texture features, consisting of coarseness, contrast, busyness, complexity and strength, were evaluated for gross tumor volumes defined on 3D/4D PET scans by radiation oncologists. Variation of the obtained texture parameters over the respiratory cycle were examined with respect to values extracted from 3D scans. Results: Differences between texture parameters derived from 4D scans at different respiratory phases and those extracted from 3D scans ranged from −30% to 13% for coarseness, −12% to 40% for contrast, −5% to 50% for busyness, −7% to 38% for complexity, and −43% to 20% for strength. Furthermore, no evident correlations were observed between respiratory phase and 4D scan texture parameters. Conclusion: Results of the current study showed that NGLDM-based texture parameters varied considerably based on choice of 3D PET and 4D PET reconstruction of NSCLC patient images, indicating that standardized image acquisition and analysis protocols need to be established for clinical studies, especially multicenter clinical trials, intending to validate prognostic values of texture features for NSCLC.

  16. Vertical Feature Mask Feature Classification Flag Extraction

    Atmospheric Science Data Center

    2013-03-28

    ... flag value. It is written in Interactive Data Language (IDL) as a callable procedure that receives as an argument a 16-bit ... Flag Extraction routine  (5 KB) Interactive Data Language (IDL) is available from  Exelis Visual Information Solutions . ...

  17. Dielectrophoretic isolation of cells using 3D microelectrodes featuring castellated blocks.

    PubMed

    Xing, Xiaoxing; Yobas, Levent

    2015-05-21

    We present 3D microelectrodes featuring castellated blocks for dielectrophoretically isolating cells. These electrodes provide a more effective dielectrophoretic force field than thin-film surface electrodes and yet immobilize cells near stagnation points across a parabolic flow profile for enhanced cell viability and separation efficiency. Unlike known volumetric electrodes with linear profiles, the electrodes with structural variations introduced along their depth scale are versatile for constructing monolithic structures with readily integrated fluidic paths. This is exemplified here in the design of an interdigitated comb array wherein electrodes with castellated surfaces serve as building blocks and form digits with an array of fluidic pores. Activation of the design with low-voltage oscillations (±5 Vp, 400 kHz) is found adequate for retaining most viable cells (90.2% ± 3.5%) while removing nonviable cells (88.5% ± 5%) at an increased throughput (5 × 10(5) cells h(-1)). The electrodes, despite their intricate profile, are structured into single-crystal silicon through a self-aligned etching process without a precision layer-by-layer assembly. PMID:25857455

  18. Algorithms for extraction of structural attitudes from 3D outcrop models

    NASA Astrophysics Data System (ADS)

    Duelis Viana, Camila; Endlein, Arthur; Ademar da Cruz Campanha, Ginaldo; Henrique Grohmann, Carlos

    2016-05-01

    The acquisition of geological attitudes on rock cuts using traditional field compass survey can be a time consuming, dangerous, or even impossible task depending on the conditions and location of outcrops. The importance of this type of data in rock-mass classifications and structural geology has led to the development of new techniques, in which the application of photogrammetric 3D digital models has had an increasing use. In this paper we present two algorithms for extraction of attitudes of geological discontinuities from virtual outcrop models: ply2atti and scanline, implemented with the Python programming language. The ply2atti algorithm allows for the virtual sampling of planar discontinuities appearing on the 3D model as individual exposed surfaces, while the scanline algorithm allows the sampling of discontinuities (surfaces and traces) along a virtual scanline. Application to digital models of a simplified test setup and a rock cut demonstrated a good correlation between the surveys undertaken using traditional field compass reading and virtual sampling on 3D digital models.

  19. Identifying Key Structural Features and Spatial Relationships in Archean Microbialites Using 2D and 3D Visualization Methods

    NASA Astrophysics Data System (ADS)

    Stevens, E. W.; Sumner, D. Y.

    2009-12-01

    Microbialites in the 2521 ± 3 Ma Gamohaan Formation, South Africa, have several different end-member morphologies which show distinct growth structures and spatial relationships. We characterized several growth structures and spatial relationships in two samples (DK20 and 2_06) using a combination of 2D and 3D analytical techniques. There are two main goals in studying complicated microbialites with a combination of 2D and 3D methods. First, one can better understand microbialite growth by identifying important structures and structural relationships. Once structures are identified, the order in which the structures formed and how they are related can be inferred from observations of crosscutting relationships. Second, it is important to use both 2D and 3D methods to correlate 3D observations with those in 2D that are more common in the field. Combining analysis provides significantly more insight into the 3D morphology of microbial structures. In our studies, 2D analysis consisted of describing polished slabs and serial sections created by grinding down the rock 100 microns at a time. 3D analysis was performed on serial sections visualized in 3D using Vrui and 3DVisualizer software developed at KeckCAVES, UCD (http://keckcaves.org). Data were visualized on a laptop and in an immersive cave system. Both samples contain microbial laminae and more vertically orients microbial "walls" called supports. The relationships between these features created voids now filled with herringbone and blocky calcite crystals. DK20, a classic plumose structure, contains two types of support structures. Both are 1st order structures (1st order structures with organic inclusions and 1st without organic inclusions) interpreted as planar features based on 2D analysis. In the 2D analysis the 1st order structures show v branching relationships as well as single cuspate relationships (two 1st order structures with inclusions merging upward), and single tented relationships (three supports

  20. Segmentation of 3D tubular objects with adaptive front propagation and minimal tree extraction for 3D medical imaging.

    PubMed

    Cohen, Laurent D; Deschamps, Thomas

    2007-08-01

    We present a new fast approach for segmentation of thin branching structures, like vascular trees, based on Fast-Marching (FM) and Level Set (LS) methods. FM allows segmentation of tubular structures by inflating a "long balloon" from a user given single point. However, when the tubular shape is rather long, the front propagation may blow up through the boundary of the desired shape close to the starting point. Our contribution is focused on a method to propagate only the useful part of the front while freezing the rest of it. We demonstrate its ability to segment quickly and accurately tubular and tree-like structures. We also develop a useful stopping criterion for the causal front propagation. We finally derive an efficient algorithm for extracting an underlying 1D skeleton of the branching objects, with minimal path techniques. Each branch being represented by its centerline, we automatically detect the bifurcations, leading to the "Minimal Tree" representation. This so-called "Minimal Tree" is very useful for visualization and quantification of the pathologies in our anatomical data sets. We illustrate our algorithms by applying it to several arteries datasets. PMID:17671862

  1. D Feature Point Extraction from LIDAR Data Using a Neural Network

    NASA Astrophysics Data System (ADS)

    Feng, Y.; Schlichting, A.; Brenner, C.

    2016-06-01

    Accurate positioning of vehicles plays an important role in autonomous driving. In our previous research on landmark-based positioning, poles were extracted both from reference data and online sensor data, which were then matched to improve the positioning accuracy of the vehicles. However, there are environments which contain only a limited number of poles. 3D feature points are one of the proper alternatives to be used as landmarks. They can be assumed to be present in the environment, independent of certain object classes. To match the LiDAR data online to another LiDAR derived reference dataset, the extraction of 3D feature points is an essential step. In this paper, we address the problem of 3D feature point extraction from LiDAR datasets. Instead of hand-crafting a 3D feature point extractor, we propose to train it using a neural network. In this approach, a set of candidates for the 3D feature points is firstly detected by the Shi-Tomasi corner detector on the range images of the LiDAR point cloud. Using a back propagation algorithm for the training, the artificial neural network is capable of predicting feature points from these corner candidates. The training considers not only the shape of each corner candidate on 2D range images, but also their 3D features such as the curvature value and surface normal value in z axis, which are calculated directly based on the LiDAR point cloud. Subsequently the extracted feature points on the 2D range images are retrieved in the 3D scene. The 3D feature points extracted by this approach are generally distinctive in the 3D space. Our test shows that the proposed method is capable of providing a sufficient number of repeatable 3D feature points for the matching task. The feature points extracted by this approach have great potential to be used as landmarks for a better localization of vehicles.

  2. Unsupervised Pathological Area Extraction using 3D T2 and FLAIR MR Images

    NASA Astrophysics Data System (ADS)

    Dvořák, Pavel; Bartušek, Karel; Smékal, Zdeněk

    2014-12-01

    This work discusses fully automated extraction of brain tumor and edema in 3D MR volumes. The goal of this work is the extraction of the whole pathological area using such an algorithm that does not require a human intervention. For the good visibility of these kinds of tissues both T2-weighted and FLAIR images were used. The proposed method was tested on 80 MR volumes of publicly available BRATS database, which contains high and low grade gliomas, both real and simulated. The performance was evaluated by the Dice coefficient, where the results were differentiated between high and low grade and real and simulated gliomas. The method reached promising results for all of the combinations of images: real high grade (0.73 ± 0.20), real low grade (0.81 ± 0.06), simulated high grade (0.81 ± 0.14), and simulated low grade (0.81 ± 0.04).

  3. Automatic extraction of insulators from 3D LiDAR data of an electrical substation

    NASA Astrophysics Data System (ADS)

    Arastounia, M.; Lichti, D. D.

    2013-10-01

    A considerable percentage of power outages are caused by animals that come into contact with conductive elements of electrical substations. These can be prevented by insulating conductive electrical objects, for which a 3D as-built plan of the substation is crucial. This research aims to create such a 3D as-built plan using terrestrial LiDAR data while in this paper the aim is to extract insulators, which are key objects in electrical substations. This paper proposes a segmentation method based on a new approach of finding the principle direction of points' distribution. This is done by forming and analysing the distribution matrix whose elements are the range of points in 9 different directions in 3D space. Comparison of the computational performance of our method with PCA (principal component analysis) shows that our approach is 25% faster since it utilizes zero-order moments while PCA computes the first- and second-order moments, which is more time-consuming. A knowledge-based approach has been developed to automatically recognize points on insulators. The method utilizes known insulator properties such as diameter and the number and the spacing of their rings. The results achieved indicate that 24 out of 27 insulators could be recognized while the 3 un-recognized ones were highly occluded. Check point analysis was performed by manually cropping all points on insulators. The results of check point analysis show that the accuracy, precision and recall of insulator recognition are 98%, 86% and 81%, respectively. It is concluded that automatic object extraction from electrical substations using only LiDAR data is not only possible but also promising. Moreover, our developed approach to determine the directional distribution of points is computationally more efficient for segmentation of objects in electrical substations compared to PCA. Finally our knowledge-based method is promising to recognize points on electrical objects as it was successfully applied for

  4. Feasibility study on 3-D shape analysis of high-aspect-ratio features using through-focus scanning optical microscopy

    PubMed Central

    Attota, Ravi Kiran; Weck, Peter; Kramar, John A.; Bunday, Benjamin; Vartanian, Victor

    2016-01-01

    In-line metrologies currently used in the semiconductor industry are being challenged by the aggressive pace of device scaling and the adoption of novel device architectures. Metrology and process control of three-dimensional (3-D) high-aspect-ratio (HAR) features are becoming increasingly important and also challenging. In this paper we present a feasibility study of through-focus scanning optical microscopy (TSOM) for 3-D shape analysis of HAR features. TSOM makes use of 3-D optical data collected using a conventional optical microscope for 3-D shape analysis. Simulation results of trenches and holes down to the 11 nm node are presented. The ability of TSOM to analyze an array of HAR features or a single isolated HAR feature is also presented. This allows for the use of targets with area over 100 times smaller than that of conventional gratings, saving valuable real estate on the wafers. Indications are that the sensitivity of TSOM may match or exceed the International Technology Roadmap for Semiconductors (ITRS) measurement requirements for the next several years. Both simulations and preliminary experimental results are presented. The simplicity, lowcost, high throughput, and nanometer scale 3-D shape sensitivity of TSOM make it an attractive inspection and process monitoring solution for nanomanufacturing. PMID:27464112

  5. Feasibility study on 3-D shape analysis of high-aspect-ratio features using through-focus scanning optical microscopy.

    PubMed

    Attota, Ravi Kiran; Weck, Peter; Kramar, John A; Bunday, Benjamin; Vartanian, Victor

    2016-07-25

    In-line metrologies currently used in the semiconductor industry are being challenged by the aggressive pace of device scaling and the adoption of novel device architectures. Metrology and process control of three-dimensional (3-D) high-aspect-ratio (HAR) features are becoming increasingly important and also challenging. In this paper we present a feasibility study of through-focus scanning optical microscopy (TSOM) for 3-D shape analysis of HAR features. TSOM makes use of 3-D optical data collected using a conventional optical microscope for 3-D shape analysis. Simulation results of trenches and holes down to the 11 nm node are presented. The ability of TSOM to analyze an array of HAR features or a single isolated HAR feature is also presented. This allows for the use of targets with area over 100 times smaller than that of conventional gratings, saving valuable real estate on the wafers. Indications are that the sensitivity of TSOM may match or exceed the International Technology Roadmap for Semiconductors (ITRS) measurement requirements for the next several years. Both simulations and preliminary experimental results are presented. The simplicity, lowcost, high throughput, and nanometer scale 3-D shape sensitivity of TSOM make it an attractive inspection and process monitoring solution for nanomanufacturing. PMID:27464112

  6. Volumetric feature extraction and visualization of tomographic molecular imaging.

    PubMed

    Bajaj, Chandrajit; Yu, Zeyun; Auer, Manfred

    2003-01-01

    Electron tomography is useful for studying large macromolecular complex within their cellular context. The associate problems include crowding and complexity. Data exploration and 3D visualization of complexes require rendering of tomograms as well as extraction of all features of interest. We present algorithms for fully automatic boundary segmentation and skeletonization, and demonstrate their applications in feature extraction and visualization of cell and molecular tomographic imaging. We also introduce an interactive volumetric exploration and visualization tool (Volume Rover), which encapsulates implementations of the above volumetric image processing algorithms, and additionally uses efficient multi-resolution interactive geometry and volume rendering techniques for interactive visualization. PMID:14643216

  7. Towards automated firearm identification based on high resolution 3D data: rotation-invariant features for multiple line-profile-measurement of firing pin shapes

    NASA Astrophysics Data System (ADS)

    Fischer, Robert; Vielhauer, Claus

    2015-03-01

    Understanding and evaluation of potential evidence, as well as evaluation of automated systems for forensic examinations currently play an important role within the domain of digital crime scene analysis. The application of 3D sensing and pattern recognition systems for automatic extraction and comparison of firearm related tool marks is an evolving field of research within this domain. In this context, the design and evaluation of rotation-invariant features for use on topography data play a particular important role. In this work, we propose and evaluate a 3D imaging system along with two novel features based on topography data and multiple profile-measurement-lines for automatic matching of firing pin shapes. Our test set contains 72 cartridges of three manufactures shot by six different 9mm guns. The entire pattern recognition workflow is addressed. This includes the application of confocal microscopy for data acquisition, preprocessing covers outlier handling, data normalization, as well as necessary segmentation and registration. Feature extraction involves the two introduced features for automatic comparison and matching of 3D firing pin shapes. The introduced features are called `Multiple-Circle-Path' (MCP) and `Multiple-Angle-Path' (MAP). Basically both features are compositions of freely configurable amounts of circular or straight path-lines combined with statistical evaluations. During the first part of evaluation (E1), we examine how well it is possible to differentiate between two 9mm weapons of the same mark and model. During second part (E2), we evaluate the discrimination accuracy regarding the set of six different 9mm guns. During the third part (E3), we evaluate the performance of the features in consideration of different rotation angles. In terms of E1, the best correct classification rate is 100% and in terms of E2 the best result is 86%. The preliminary results for E3 indicate robustness of both features regarding rotation. However, in future

  8. Morphological features of the macerated cranial bones registered by the 3D vision system for potential use in forensic anthropology.

    PubMed

    Skrzat, Janusz; Sioma, Andrzej; Kozerska, Magdalena

    2013-01-01

    In this paper we present potential usage of the 3D vision system for registering features of the macerated cranial bones. Applied 3D vision system collects height profiles of the object surface and from that data builds a three-dimensional image of the surface. This method appeared to be accurate enough to capture anatomical details of the macerated bones. With the aid of the 3D vision system we generated images of the surface of the human calvaria which was used for testing the system. Performed reconstruction visualized the imprints of the dural vascular system, cranial sutures, and the three-layer structure of the cranial bones observed in the cross-section. We figure out that the 3D vision system may deliver data which can enhance estimation of sex from the osteological material. PMID:24858457

  9. Automatic extraction of planetary image features

    NASA Technical Reports Server (NTRS)

    LeMoigne-Stewart, Jacqueline J. (Inventor); Troglio, Giulia (Inventor); Benediktsson, Jon A. (Inventor); Serpico, Sebastiano B. (Inventor); Moser, Gabriele (Inventor)

    2013-01-01

    A method for the extraction of Lunar data and/or planetary features is provided. The feature extraction method can include one or more image processing techniques, including, but not limited to, a watershed segmentation and/or the generalized Hough Transform. According to some embodiments, the feature extraction method can include extracting features, such as, small rocks. According to some embodiments, small rocks can be extracted by applying a watershed segmentation algorithm to the Canny gradient. According to some embodiments, applying a watershed segmentation algorithm to the Canny gradient can allow regions that appear as close contours in the gradient to be segmented.

  10. NCC-RANSAC: A Fast Plane Extraction Method for 3-D Range Data Segmentation

    PubMed Central

    Qian, Xiangfei; Ye, Cang

    2015-01-01

    This paper presents a new plane extraction (PE) method based on the random sample consensus (RANSAC) approach. The generic RANSAC-based PE algorithm may over-extract a plane, and it may fail in case of a multistep scene where the RANSAC procedure results in multiple inlier patches that form a slant plane straddling the steps. The CC-RANSAC PE algorithm successfully overcomes the latter limitation if the inlier patches are separate. However, it fails if the inlier patches are connected. A typical scenario is a stairway with a stair wall where the RANSAC plane-fitting procedure results in inliers patches in the tread, riser, and stair wall planes. They connect together and form a plane. The proposed method, called normal-coherence CC-RANSAC (NCC-RANSAC), performs a normal coherence check to all data points of the inlier patches and removes the data points whose normal directions are contradictory to that of the fitted plane. This process results in separate inlier patches, each of which is treated as a candidate plane. A recursive plane clustering process is then executed to grow each of the candidate planes until all planes are extracted in their entireties. The RANSAC plane-fitting and the recursive plane clustering processes are repeated until no more planes are found. A probabilistic model is introduced to predict the success probability of the NCC-RANSAC algorithm and validated with real data of a 3-D time-of-flight camera–SwissRanger SR4000. Experimental results demonstrate that the proposed method extracts more accurate planes with less computational time than the existing RANSAC-based methods. PMID:24771605

  11. Integration of a 3D perspective view in the navigation display: featuring pilot's mental model

    NASA Astrophysics Data System (ADS)

    Ebrecht, L.; Schmerwitz, S.

    2015-05-01

    Synthetic vision systems (SVS) appear as spreading technology in the avionic domain. Several studies prove enhanced situational awareness when using synthetic vision. Since the introduction of synthetic vision a steady change and evolution started concerning the primary flight display (PFD) and the navigation display (ND). The main improvements of the ND comprise the representation of colored ground proximity warning systems (EGPWS), weather radar, and TCAS information. Synthetic vision seems to offer high potential to further enhance cockpit display systems. Especially, concerning the current trend having a 3D perspective view in a SVS-PFD while leaving the navigational content as well as methods of interaction unchanged the question arouses if and how the gap between both displays might evolve to a serious problem. This issue becomes important in relation to the transition and combination of strategic and tactical flight guidance. Hence, pros and cons of 2D and 3D views generally as well as the gap between the egocentric perspective 3D view of the PFD and the exocentric 2D top and side view of the ND will be discussed. Further a concept for the integration of a 3D perspective view, i.e., bird's eye view, in synthetic vision ND will be presented. The combination of 2D and 3D views in the ND enables a better correlation of the ND and the PFD. Additionally, this supports the building of pilot's mental model. The authors believe it will improve the situational and spatial awareness. It might prove to further raise the safety margin when operating in mountainous areas.

  12. A Novel Medical Freehand Sketch 3D Model Retrieval Method by Dimensionality Reduction and Feature Vector Transformation

    PubMed Central

    Jing, Zhang; Sheng, Kang Bao

    2016-01-01

    To assist physicians to quickly find the required 3D model from the mass medical model, we propose a novel retrieval method, called DRFVT, which combines the characteristics of dimensionality reduction (DR) and feature vector transformation (FVT) method. The DR method reduces the dimensionality of feature vector; only the top M low frequency Discrete Fourier Transform coefficients are retained. The FVT method does the transformation of the original feature vector and generates a new feature vector to solve the problem of noise sensitivity. The experiment results demonstrate that the DRFVT method achieves more effective and efficient retrieval results than other proposed methods. PMID:27293478

  13. Coherent vortex extraction in 3D homogeneous turbulence: comparison between orthogonal and biorthogonal wavelet decompositions

    NASA Astrophysics Data System (ADS)

    Roussel, O.; Schneider, K.; Farge, M.

    A comparison between two different ways of extracting coherent vortices in three-dimensional (3D) homogeneous isotropic turbulence is performed, using either orthogonal or biorthogonal wavelets. The method is based on a wavelet decomposition of the vorticity field and a subsequent thresholding of the wavelet coefficients. The coherent vorticity is reconstructed from a few strong wavelet coefficients, while the incoherent vorticity is reconstructed from the remaining weak coefficients. The choice of the threshold, which has no adjustable parameters, is motivated for the orthogonal case from the denoising theory. Using only 3 % of the coefficients we show that both decompositions, that is orthogonal and biorthogonal, extract the coherent vortices. They contain most of the energy (around 99 % in both cases) and retain 74 % and 68 % of the enstrophy in the orthogonal and biorthogonal cases, respectively. The incoherent background flow for the orthogonal decomposition, which corresponds to 97 % of the wavelet coefficients, is structureless, decorrelated, and has a Gaussian velocity probability distribution function (PDF). In contrast, for the biorthogonal decomposition, the background flow exhibits quasi-two-dimensional (2D) structures and yields an exponential velocity PDF. Moreover, the biorthogonal decomposition loses 3.7% of both enstrophy and helicity, while they are conserved by the orthogonal decomposition.

  14. Extraction and refinement of building faces in 3D point clouds

    NASA Astrophysics Data System (ADS)

    Pohl, Melanie; Meidow, Jochen; Bulatov, Dimitri

    2013-10-01

    In this paper, we present an approach to generate a 3D model of an urban scene out of sensor data. The first milestone on that way is to classify the sensor data into the main parts of a scene, such as ground, vegetation, buildings and their outlines. This has already been accomplished within our previous work. Now, we propose a four-step algorithm to model the building structure, which is assumed to consist of several dominant planes. First, we extract small elevated objects, like chimneys, using a hot-spot detector and handle the detected regions separately. In order to model the variety of roof structures precisely, we split up complex building blocks into parts. Two different approaches are used: To act on the assumption of underlying 2D ground polygons, we use geometric methods to divide them into sub-polygons. Without polygons, we use morphological operations and segmentation methods. In the third step, extraction of dominant planes takes place, by using either RANSAC or J-linkage algorithm. They operate on point clouds of sufficient confidence within the previously separated building parts and give robust results even with noisy, outlier-rich data. Last, we refine the previously determined plane parameters using geometric relations of the building faces. Due to noise, these expected properties of roofs and walls are not fulfilled. Hence, we enforce them as hard constraints and use the previously extracted plane parameters as initial values for an optimization method. To test the proposed workflow, we use both several data sets, including noisy data from depth maps and data computed by laser scanning.

  15. Automatic 3D Extraction of Buildings, Vegetation and Roads from LIDAR Data

    NASA Astrophysics Data System (ADS)

    Bellakaout, A.; Cherkaoui, M.; Ettarid, M.; Touzani, A.

    2016-06-01

    Aerial topographic surveys using Light Detection and Ranging (LiDAR) technology collect dense and accurate information from the surface or terrain; it is becoming one of the important tools in the geosciences for studying objects and earth surface. Classification of Lidar data for extracting ground, vegetation, and buildings is a very important step needed in numerous applications such as 3D city modelling, extraction of different derived data for geographical information systems (GIS), mapping, navigation, etc... Regardless of what the scan data will be used for, an automatic process is greatly required to handle the large amount of data collected because the manual process is time consuming and very expensive. This paper is presenting an approach for automatic classification of aerial Lidar data into five groups of items: buildings, trees, roads, linear object and soil using single return Lidar and processing the point cloud without generating DEM. Topological relationship and height variation analysis is adopted to segment, preliminary, the entire point cloud preliminarily into upper and lower contours, uniform and non-uniform surface, non-uniform surfaces, linear objects, and others. This primary classification is used on the one hand to know the upper and lower part of each building in an urban scene, needed to model buildings façades; and on the other hand to extract point cloud of uniform surfaces which contain roofs, roads and ground used in the second phase of classification. A second algorithm is developed to segment the uniform surface into buildings roofs, roads and ground, the second phase of classification based on the topological relationship and height variation analysis, The proposed approach has been tested using two areas : the first is a housing complex and the second is a primary school. The proposed approach led to successful classification results of buildings, vegetation and road classes.

  16. Segmentation of 3D EBSD data for subgrain boundary identification and feature characterization.

    PubMed

    Loeb, Andrew; Ferry, Michael; Bassman, Lori

    2016-02-01

    Subgrain structures formed during plastic deformation of metals can be observed by electron backscatter diffraction (EBSD) but are challenging to identify automatically. We have adapted a 2D image segmentation technique, fast multiscale clustering (FMC), to 3D EBSD data using a novel variance function to accommodate quaternion data. This adaptation, which has been incorporated into the free open source texture analysis software package MTEX, is capable of segmenting based on subtle and gradual variation as well as on sharp boundaries within the data. FMC has been further modified to group the resulting closed 3D segment boundaries into distinct coherent surfaces based on local normals of a triangulated surface. We demonstrate the excellent capabilities of this technique with application to 3D EBSD data sets generated from cold rolled aluminum containing well-defined microbands, cold rolled and partly recrystallized extra low carbon steel microstructure containing three magnitudes of boundary misorientations, and channel-die plane strain compressed Goss-oriented nickel crystal containing microbands with very subtle changes in orientation. PMID:26630071

  17. Individual 3D region-of-interest atlas of the human brain: neural-network-based tissue classification with automatic training point extraction

    NASA Astrophysics Data System (ADS)

    Wagenknecht, Gudrun; Kaiser, Hans-Juergen; Obladen, Thorsten; Sabri, Osama; Buell, Udalrich

    2000-06-01

    The purpose of individual 3D region-of-interest atlas extraction is to automatically define anatomically meaningful regions in 3D MRI images for quantification of functional parameters (PET, SPECT: rMRGlu, rCBF). The first step of atlas extraction is to automatically classify brain tissue types into gray matter (GM), white matter (WM), cerebrospinal fluid (CSF), scalp/bone (SB) and background (BG). A feed-forward neural network with back-propagation training algorithm is used and compared to other numerical classifiers. It can be trained by a sample from the individual patient data set in question. Classification is done by a 'winner takes all' decision. Automatic extraction of a user-specified number of training points is done in a cross-sectional slice. Background separation is done by simple region growing. The most homogeneous voxels define the region for WM training point extraction (TPE). Non-white-matter and nonbackground regions are analyzed for GM and CSF training points. For SB TPE, the distance from the BG region is one feature. For each class, spatially uniformly distributed training points are extracted by a random generator from these regions. Simulated and real 3D MRI images are analyzed and error rates for TPE and classification calculated. The resulting class images can be analyzed for extraction of anatomical ROIs.

  18. Interpretation and mapping of geological features using mobile devices for 3D outcrop modelling

    NASA Astrophysics Data System (ADS)

    Buckley, Simon J.; Kehl, Christian; Mullins, James R.; Howell, John A.

    2016-04-01

    Advances in 3D digital geometric characterisation have resulted in widespread adoption in recent years, with photorealistic models utilised for interpretation, quantitative and qualitative analysis, as well as education, in an increasingly diverse range of geoscience applications. Topographic models created using lidar and photogrammetry, optionally combined with imagery from sensors such as hyperspectral and thermal cameras, are now becoming commonplace in geoscientific research. Mobile devices (tablets and smartphones) are maturing rapidly to become powerful field computers capable of displaying and interpreting 3D models directly in the field. With increasingly high-quality digital image capture, combined with on-board sensor pose estimation, mobile devices are, in addition, a source of primary data, which can be employed to enhance existing geological models. Adding supplementary image textures and 2D annotations to photorealistic models is therefore a desirable next step to complement conventional field geoscience. This contribution reports on research into field-based interpretation and conceptual sketching on images and photorealistic models on mobile devices, motivated by the desire to utilise digital outcrop models to generate high quality training images (TIs) for multipoint statistics (MPS) property modelling. Representative training images define sedimentological concepts and spatial relationships between elements in the system, which are subsequently modelled using artificial learning to populate geocellular models. Photorealistic outcrop models are underused sources of quantitative and qualitative information for generating TIs, explored further in this research by linking field and office workflows through the mobile device. Existing textured models are loaded to the mobile device, allowing rendering in a 3D environment. Because interpretation in 2D is more familiar and comfortable for users, the developed application allows new images to be captured

  19. 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.

  20. Guidance in feature extraction to resolve uncertainty

    NASA Astrophysics Data System (ADS)

    Kovalerchuk, Boris; Kovalerchuk, Michael; Streltsov, Simon; Best, Matthew

    2013-05-01

    Automated Feature Extraction (AFE) plays a critical role in image understanding. Often the imagery analysts extract features better than AFE algorithms do, because analysts use additional information. The extraction and processing of this information can be more complex than the original AFE task, and that leads to the "complexity trap". This can happen when the shadow from the buildings guides the extraction of buildings and roads. This work proposes an AFE algorithm to extract roads and trails by using the GMTI/GPS tracking information and older inaccurate maps of roads and trails as AFE guides.

  1. Fully automatic detection of salient features in 3-d transesophageal images.

    PubMed

    Curiale, Ariel H; Haak, Alexander; Vegas-Sánchez-Ferrero, Gonzalo; Ren, Ben; Aja-Fernández, Santiago; Bosch, Johan G

    2014-12-01

    Most automated segmentation approaches to the mitral valve and left ventricle in 3-D echocardiography require a manual initialization. In this article, we propose a fully automatic scheme to initialize a multicavity segmentation approach in 3-D transesophageal echocardiography by detecting the left ventricle long axis, the mitral valve and the aortic valve location. Our approach uses a probabilistic and structural tissue classification to find structures such as the mitral and aortic valves; the Hough transform for circles to find the center of the left ventricle; and multidimensional dynamic programming to find the best position for the left ventricle long axis. For accuracy and agreement assessment, the proposed method was evaluated in 19 patients with respect to manual landmarks and as initialization of a multicavity segmentation approach for the left ventricle, the right ventricle, the left atrium, the right atrium and the aorta. The segmentation results revealed no statistically significant differences between manual and automated initialization in a paired t-test (p > 0.05). Additionally, small biases between manual and automated initialization were detected in the Bland-Altman analysis (bias, variance) for the left ventricle (-0.04, 0.10); right ventricle (-0.07, 0.18); left atrium (-0.01, 0.03); right atrium (-0.04, 0.13); and aorta (-0.05, 0.14). These results indicate that the proposed approach provides robust and accurate detection to initialize a multicavity segmentation approach without any user interaction. PMID:25308940

  2. Radiometric and geometric evaluation of GeoEye-1, WorldView-2 and Pléiades-1A stereo images for 3D information extraction

    NASA Astrophysics Data System (ADS)

    Poli, D.; Remondino, F.; Angiuli, E.; Agugiaro, G.

    2015-02-01

    Today the use of spaceborne Very High Resolution (VHR) optical sensors for automatic 3D information extraction is increasing in the scientific and civil communities. The 3D Optical Metrology (3DOM) unit of the Bruno Kessler Foundation (FBK) in Trento (Italy) has collected VHR satellite imagery, as well as aerial and terrestrial data over Trento for creating a complete testfield for investigations on image radiometry, geometric accuracy, automatic digital surface model (DSM) generation, 2D/3D feature extraction, city modelling and data fusion. This paper addresses the radiometric and the geometric aspects of the VHR spaceborne imagery included in the Trento testfield and their potential for 3D information extraction. The dataset consist of two stereo-pairs acquired by WorldView-2 and by GeoEye-1 in panchromatic and multispectral mode, and a triplet from Pléiades-1A. For reference and validation, a DSM from airborne LiDAR acquisition is used. The paper gives details on the project, dataset characteristics and achieved results.

  3. FDSOI bottom MOSFETs stability versus top transistor thermal budget featuring 3D monolithic integration

    NASA Astrophysics Data System (ADS)

    Fenouillet-Beranger, C.; Previtali, B.; Batude, P.; Nemouchi, F.; Cassé, M.; Garros, X.; Tosti, L.; Rambal, N.; Lafond, D.; Dansas, H.; Pasini, L.; Brunet, L.; Deprat, F.; Grégoire, M.; Mellier, M.; Vinet, M.

    2015-11-01

    To set up specification for 3D monolithic integration, for the first time, the thermal stability of state-of-the-art FDSOI (Fully Depleted SOI) transistors electrical performance is quantified. Post fabrication annealings are performed on FDSOI transistors to mimic the thermal budget associated to top layer processing. Degradation of the silicide for thermal treatments beyond 400 °C is identified as the main responsible for performance degradation for PMOS devices. For the NMOS transistors, arsenic (As) and phosphorus (P) dopants deactivation adds up to this effect. By optimizing both the n-type extension implantations and the bottom silicide process, thermal stability of FDSOI can be extended to allow relaxing upwards the thermal budget authorized for top transistors processing.

  4. Electronic Nose Feature Extraction Methods: A Review

    PubMed Central

    Yan, Jia; Guo, Xiuzhen; Duan, Shukai; Jia, Pengfei; Wang, Lidan; Peng, Chao; Zhang, Songlin

    2015-01-01

    Many research groups in academia and industry are focusing on the performance improvement of electronic nose (E-nose) systems mainly involving three optimizations, which are sensitive material selection and sensor array optimization, enhanced feature extraction methods and pattern recognition method selection. For a specific application, the feature extraction method is a basic part of these three optimizations and a key point in E-nose system performance improvement. The aim of a feature extraction method is to extract robust information from the sensor response with less redundancy to ensure the effectiveness of the subsequent pattern recognition algorithm. Many kinds of feature extraction methods have been used in E-nose applications, such as extraction from the original response curves, curve fitting parameters, transform domains, phase space (PS) and dynamic moments (DM), parallel factor analysis (PARAFAC), energy vector (EV), power density spectrum (PSD), window time slicing (WTS) and moving window time slicing (MWTS), moving window function capture (MWFC), etc. The object of this review is to provide a summary of the various feature extraction methods used in E-noses in recent years, as well as to give some suggestions and new inspiration to propose more effective feature extraction methods for the development of E-nose technology. PMID:26540056

  5. Optimization of a 3D Dynamic Culturing System for In Vitro Modeling of Frontotemporal Neurodegeneration-Relevant Pathologic Features.

    PubMed

    Tunesi, Marta; Fusco, Federica; Fiordaliso, Fabio; Corbelli, Alessandro; Biella, Gloria; Raimondi, Manuela T

    2016-01-01

    Frontotemporal lobar degeneration (FTLD) is a severe neurodegenerative disorder that is diagnosed with increasing frequency in clinical setting. Currently, no therapy is available and in addition the molecular basis of the disease are far from being elucidated. Consequently, it is of pivotal importance to develop reliable and cost-effective in vitro models for basic research purposes and drug screening. To this respect, recent results in the field of Alzheimer's disease have suggested that a tridimensional (3D) environment is an added value to better model key pathologic features of the disease. Here, we have tried to add complexity to the 3D cell culturing concept by using a microfluidic bioreactor, where cells are cultured under a continuous flow of medium, thus mimicking the interstitial fluid movement that actually perfuses the body tissues, including the brain. We have implemented this model using a neuronal-like cell line (SH-SY5Y), a widely exploited cell model for neurodegenerative disorders that shows some basic features relevant for FTLD modeling, such as the release of the FTLD-related protein progranulin (PRGN) in specific vesicles (exosomes). We have efficiently seeded the cells on 3D scaffolds, optimized a disease-relevant oxidative stress experiment (by targeting mitochondrial function that is one of the possible FTLD-involved pathological mechanisms) and evaluated cell metabolic activity in dynamic culture in comparison to static conditions, finding that SH-SY5Y cells cultured in 3D scaffold are susceptible to the oxidative damage triggered by a mitochondrial-targeting toxin (6-OHDA) and that the same cells cultured in dynamic conditions kept their basic capacity to secrete PRGN in exosomes once recovered from the bioreactor and plated in standard 2D conditions. We think that a further improvement of our microfluidic system may help in providing a full device where assessing basic FTLD-related features (including PRGN dynamic secretion) that may be

  6. Efficient feature-based 2D/3D registration of transesophageal echocardiography to x-ray fluoroscopy for cardiac interventions

    NASA Astrophysics Data System (ADS)

    Hatt, Charles R.; Speidel, Michael A.; Raval, Amish N.

    2014-03-01

    We present a novel 2D/ 3D registration algorithm for fusion between transesophageal echocardiography (TEE) and X-ray fluoroscopy (XRF). The TEE probe is modeled as a subset of 3D gradient and intensity point features, which facilitates efficient 3D-to-2D perspective projection. A novel cost-function, based on a combination of intensity and edge features, evaluates the registration cost value without the need for time-consuming generation of digitally reconstructed radiographs (DRRs). Validation experiments were performed with simulations and phantom data. For simulations, in silica XRF images of a TEE probe were generated in a number of different pose configurations using a previously acquired CT image. Random misregistrations were applied and our method was used to recover the TEE probe pose and compare the result to the ground truth. Phantom experiments were performed by attaching fiducial markers externally to a TEE probe, imaging the probe with an interventional cardiac angiographic x-ray system, and comparing the pose estimated from the external markers to that estimated from the TEE probe using our algorithm. Simulations found a 3D target registration error of 1.08(1.92) mm for biplane (monoplane) geometries, while the phantom experiment found a 2D target registration error of 0.69mm. For phantom experiments, we demonstrated a monoplane tracking frame-rate of 1.38 fps. The proposed feature-based registration method is computationally efficient, resulting in near real-time, accurate image based registration between TEE and XRF.

  7. Deep MRI brain extraction: A 3D convolutional neural network for skull stripping.

    PubMed

    Kleesiek, Jens; Urban, Gregor; Hubert, Alexander; Schwarz, Daniel; Maier-Hein, Klaus; Bendszus, Martin; Biller, Armin

    2016-04-01

    Brain extraction from magnetic resonance imaging (MRI) is crucial for many neuroimaging workflows. Current methods demonstrate good results on non-enhanced T1-weighted images, but struggle when confronted with other modalities and pathologically altered tissue. In this paper we present a 3D convolutional deep learning architecture to address these shortcomings. In contrast to existing methods, we are not limited to non-enhanced T1w images. When trained appropriately, our approach handles an arbitrary number of modalities including contrast-enhanced scans. Its applicability to MRI data, comprising four channels: non-enhanced and contrast-enhanced T1w, T2w and FLAIR contrasts, is demonstrated on a challenging clinical data set containing brain tumors (N=53), where our approach significantly outperforms six commonly used tools with a mean Dice score of 95.19. Further, the proposed method at least matches state-of-the-art performance as demonstrated on three publicly available data sets: IBSR, LPBA40 and OASIS, totaling N=135 volumes. For the IBSR (96.32) and LPBA40 (96.96) data set the convolutional neuronal network (CNN) obtains the highest average Dice scores, albeit not being significantly different from the second best performing method. For the OASIS data the second best Dice (95.02) results are achieved, with no statistical difference in comparison to the best performing tool. For all data sets the highest average specificity measures are evaluated, whereas the sensitivity displays about average results. Adjusting the cut-off threshold for generating the binary masks from the CNN's probability output can be used to increase the sensitivity of the method. Of course, this comes at the cost of a decreased specificity and has to be decided application specific. Using an optimized GPU implementation predictions can be achieved in less than one minute. The proposed method may prove useful for large-scale studies and clinical trials. PMID:26808333

  8. ECG Feature Extraction using Time Frequency Analysis

    NASA Astrophysics Data System (ADS)

    Nair, Mahesh A.

    The proposed algorithm is a novel method for the feature extraction of ECG beats based on Wavelet Transforms. A combination of two well-accepted methods, Pan Tompkins algorithm and Wavelet decomposition, this system is implemented with the help of MATLAB. The focus of this work is to implement the algorithm, which can extract the features of ECG beats with high accuracy. The performance of this system is evaluated in a pilot study using the MIT-BIH Arrhythmia database.

  9. Surface processes on the asteroid deduced from the external 3D shapes and surface features of Itokawa particles

    NASA Astrophysics Data System (ADS)

    Tsuchiyama, A.; Matsumoto, T.

    2015-10-01

    Particles on the surface of S-type Asteroid 25143 Itokawa were successfully recovered by the Hayabusa mission of JAXA (e.g., [1,2]). They are not only the first samples recovered from an asteroid, but also the second extraterrestrial regolith to have been sampled, the first being the Moon by Apollo and Luna missions. The analysis of tiny sample particles (20-200 μm) shows that the Itokawa surface material is consistent with LL chondrites suffered by space weathering as expected and brought an end to the origin of meteorites (e.g., [2-4]). In addition, the examination of Itokawa particles allow studies of surface processes on the asteroid because regolith particles can be regarded as an interface with the space environment, where the impacts of small objects and irradiation by the solar wind and galactic cosmic rays should have been recorded. External 3D shapes and surface features of Itokawa regolith particles were examined. Two kinds of surface modification, formation of space-weathering rims mainly by solar wind implantation and surface abrasion by grain migration, were recognized. Spectral change of the asteroid proceeded by formation of space-weathering rims and refreshment of the regolith surfaces. External 3D shapes and surface morphologies of the regolith particles can provide information about formation and evolution history of regolith particles in relation to asteroidal surface processes. 3D shapes of Itokawa regolith particles were obtained using microtomography [3]. The surface nanomiromorpholgy of Itokawa particles were also observed using FE-SEM [5]. However, the number of particles was limited and genial feature on the surface morphology has not been understood. In this study, the surface morphology of Itokawa regolith particles was systematically investigated together with their 3D structures.

  10. SU-E-J-245: Sensitivity of FDG PET Feature Analysis in Multi-Plane Vs. Single-Plane Extraction

    SciTech Connect

    Harmon, S; Jeraj, R; Galavis, P

    2015-06-15

    Purpose: Sensitivity of PET-derived texture features to reconstruction methods has been reported for features extracted from axial planes; however, studies often utilize three dimensional techniques. This work aims to quantify the impact of multi-plane (3D) vs. single-plane (2D) feature extraction on radiomics-based analysis, including sensitivity to reconstruction parameters and potential loss of spatial information. Methods: Twenty-three patients with solid tumors underwent [{sup 18}F]FDG PET/CT scans under identical protocols. PET data were reconstructed using five sets of reconstruction parameters. Tumors were segmented using an automatic, in-house algorithm robust to reconstruction variations. 50 texture features were extracted using two Methods: 2D patches along axial planes and 3D patches. For each method, sensitivity of features to reconstruction parameters was calculated as percent difference relative to the average value across reconstructions. Correlations between feature values were compared when using 2D and 3D extraction. Results: 21/50 features showed significantly different sensitivity to reconstruction parameters when extracted in 2D vs 3D (wilcoxon α<0.05), assessed by overall range of variation, Rangevar(%). Eleven showed greater sensitivity to reconstruction in 2D extraction, primarily first-order and co-occurrence features (average Rangevar increase 83%). The remaining ten showed higher variation in 3D extraction (average Range{sub var}increase 27%), mainly co-occurence and greylevel run-length features. Correlation of feature value extracted in 2D and feature value extracted in 3D was poor (R<0.5) in 12/50 features, including eight co-occurrence features. Feature-to-feature correlations in 2D were marginally higher than 3D, ∣R∣>0.8 in 16% and 13% of all feature combinations, respectively. Larger sensitivity to reconstruction parameters were seen for inter-feature correlation in 2D(σ=6%) than 3D (σ<1%) extraction. Conclusion: Sensitivity

  11. Impact of the biophysical features of a 3D gelatin microenvironment on glioblastoma malignancy.

    PubMed

    Pedron, S; Harley, B A C

    2013-12-01

    Three-dimensional tissue engineered constructs provide a platform to examine how the local extracellular matrix (ECM) contributes to the malignancy of cancers such as human glioblastoma multiforme. Improved resolution of how local matrix biophysical features impact glioma proliferation, genomic and signal transduction paths, as well as phenotypic malignancy markers would complement recent improvements in our understanding of molecular mechanisms associated with enhanced malignancy. Here, we report the use of a gelatin methacrylate (GelMA) platform to create libraries of three-dimensional biomaterials to identify combinations of biophysical features that promote malignant phenotypes of human U87MG glioma cells. We noted key biophysical properties, namely matrix density, crosslinking density, and biodegradability, that significantly impact glioma cell morphology, proliferation, and motility. Gene expression profiles and secreted markers of increased malignancy, notably VEGF, MMP-2, MMP-9, HIF-1, and the ECM protein fibronectin, were also significantly impacted by the local biophysical environment as well as matrix-induced deficits in diffusion-mediated oxygen and nutrient biotransport. Overall, this biomaterial system provides a flexible platform to explore the role biophysical factors play in the etiology, growth, and subsequent invasive spreading of gliomas. PMID:23559545

  12. Shape-based 3D vascular tree extraction for perforator flaps

    NASA Astrophysics Data System (ADS)

    Wen, Quan; Gao, Jean

    2005-04-01

    Perforator flaps have been increasingly used in the past few years for trauma and reconstructive surgical cases. With the thinned perforated flaps, greater survivability and decrease in donor site morbidity have been reported. Knowledge of the 3D vascular tree will provide insight information about the dissection region, vascular territory, and fascia levels. This paper presents a scheme of shape-based 3D vascular tree reconstruction of perforator flaps for plastic surgery planning, which overcomes the deficiencies of current existing shape-based interpolation methods by applying rotation and 3D repairing. The scheme has the ability to restore the broken parts of the perforator vascular tree by using a probability-based adaptive connection point search (PACPS) algorithm with minimum human intervention. The experimental results evaluated by both synthetic and 39 harvested cadaver perforator flaps show the promise and potential of proposed scheme for plastic surgery planning.

  13. Stereo 3-D Imagery Uses for Definition of Geologic Structures and Geomorphic Features (Anaglyph colored glasses employed)

    NASA Astrophysics Data System (ADS)

    Hicks, B. G.; Fuente, J. D.

    2008-12-01

    Recently completed projects incorporating TopoMorpher* digital images as adjuncts to commonly employed tools has emphasized the distinct advantage gained with STEREO 3-D DIGITAL IMAGERY. By manipulating scale, relief (four types of digital shading), sun angle, direction of viewing and tilt of scene, etc. -- to produce differing views of the same terrain -- aids in identifying, tracing, and interpreting ground surface anomalies. *TopoMorpher is a digital software product of Eighteen Software (18 software.com). The advantage of Stereo 3-D views combined with digital removal of vegetation which blocked interpretation (commonly called 'bare earth/naked' views) cannot be over-emphasized. The TopoMorpher program creates scenes transferable to disk for printing at any size. Included is with computer projector which allows large display and discussion ease for groups. The examples include (1) fault systems for targeting water well locations in bedrock and (2) delineation of debris slide and avalanche terrain. Combining geologic mapping and spring locations with Stereo 3-D TopoMorpher tracing of fault lineaments has allowed targeting of water well drilling sites. Selection of geophysical study areas for well siting has been simplified. Stereo 3-D TopoMorpher has a specific "relief/terrain setting" to define potential failure sites by producing detailed colored slope maps keyed to field-data derived parameters. Posters display individual project images and large scale overviews for identifying unusual major terrain features. Images at scales using 10 and 30 meter digital data as well as Lidar (< 1 meter) will be shown.

  14. High Resolution Prediction of Calcium-Binding Sites in 3D Protein Structures Using FEATURE

    PubMed Central

    2015-01-01

    Metal-binding proteins are ubiquitous in biological systems ranging from enzymes to cell surface receptors. Among the various biologically active metal ions, calcium plays a large role in regulating cellular and physiological changes. With the increasing number of high-quality crystal structures of proteins associated with their metal ion ligands, many groups have built models to identify Ca2+ sites in proteins, utilizing information such as structure, geometry, or homology to do the inference. We present a FEATURE-based approach in building such a model and show that our model is able to discriminate between nonsites and calcium-binding sites with a very high precision of more than 98%. We demonstrate the high specificity of our model by applying it to test sets constructed from other ions. We also introduce an algorithm to convert high scoring regions into specific site predictions and demonstrate the usage by scanning a test set of 91 calcium-binding protein structures (190 calcium sites). The algorithm has a recall of more than 93% on the test set with predictions found within 3 Å of the actual sites. PMID:26226489

  15. Optimization of a 3D Dynamic Culturing System for In Vitro Modeling of Frontotemporal Neurodegeneration-Relevant Pathologic Features

    PubMed Central

    Tunesi, Marta; Fusco, Federica; Fiordaliso, Fabio; Corbelli, Alessandro; Biella, Gloria; Raimondi, Manuela T.

    2016-01-01

    Frontotemporal lobar degeneration (FTLD) is a severe neurodegenerative disorder that is diagnosed with increasing frequency in clinical setting. Currently, no therapy is available and in addition the molecular basis of the disease are far from being elucidated. Consequently, it is of pivotal importance to develop reliable and cost-effective in vitro models for basic research purposes and drug screening. To this respect, recent results in the field of Alzheimer’s disease have suggested that a tridimensional (3D) environment is an added value to better model key pathologic features of the disease. Here, we have tried to add complexity to the 3D cell culturing concept by using a microfluidic bioreactor, where cells are cultured under a continuous flow of medium, thus mimicking the interstitial fluid movement that actually perfuses the body tissues, including the brain. We have implemented this model using a neuronal-like cell line (SH-SY5Y), a widely exploited cell model for neurodegenerative disorders that shows some basic features relevant for FTLD modeling, such as the release of the FTLD-related protein progranulin (PRGN) in specific vesicles (exosomes). We have efficiently seeded the cells on 3D scaffolds, optimized a disease-relevant oxidative stress experiment (by targeting mitochondrial function that is one of the possible FTLD-involved pathological mechanisms) and evaluated cell metabolic activity in dynamic culture in comparison to static conditions, finding that SH-SY5Y cells cultured in 3D scaffold are susceptible to the oxidative damage triggered by a mitochondrial-targeting toxin (6-OHDA) and that the same cells cultured in dynamic conditions kept their basic capacity to secrete PRGN in exosomes once recovered from the bioreactor and plated in standard 2D conditions. We think that a further improvement of our microfluidic system may help in providing a full device where assessing basic FTLD-related features (including PRGN dynamic secretion) that may

  16. Generated 3D-common feature hypotheses using the HipHop method for developing new topoisomerase I inhibitors.

    PubMed

    Ataei, Sanaz; Yilmaz, Serap; Ertan-Bolelli, Tugba; Yildiz, Ilkay

    2015-07-01

    The continued interest in designing novel topoisomerase I (Topo I) inhibitors and the lack of adequate ligand-based computer-aided drug discovery efforts combined with the drawbacks of structure-based design prompted us to explore the possibility of developing ligand-based three-dimensional (3D) pharmacophore(s). This approach avoids the pitfalls of structure-based techniques because it only focuses on common features among known ligands; furthermore, the pharmacophore model can be used as 3D search queries to discover new Topo I inhibitory scaffolds. In this article, we employed the HipHop module using Discovery Studio to construct plausible binding hypotheses for clinically used Topo I inhibitors, such as camptothecin, topotecan, belotecan, and SN-38, which is an active metabolite of irinotecan. The docked pose of topotecan was selected as a reference compound. The first hypothesis (Hypo 01) among the obtained 10 hypotheses was chosen for further analysis. Hypo 01 had six features, which were two hydrogen-bond acceptors, one hydrogen-bond donor, one hydrophob aromatic and one hydrophob aliphatic, and one ring aromatic. Our obtained hypothesis was checked by using some of the aromathecin derivatives which were published for their Topo I inhibitory potency. Moreover, five structures were found to be possible anti-Topo I compounds from the DruglikeDiverse database. From this research, it can be suggested that our model could be useful for further studies in order to design new potent Topo I-targeting antitumor drugs. PMID:25914208

  17. Obtaining 3d models of surface snow and ice features (penitentes) with a Xbox Kinect

    NASA Astrophysics Data System (ADS)

    Nicholson, Lindsey; Partan, Benjamin; Pętlicki, Michał; MacDonell, Shelley

    2014-05-01

    Penitentes are snow or ice spikes that can reach several metres in height. They are a common feature of snow and ice surfaces in the semi-arid Andes as their formation is favoured by very low humidity, persistently low temperatures and sustained high solar radiation. While the conditions of their formation are relatively well constrained it is not yet clear how their presence influences the rate of mass loss and meltwater production from the mountain cryosphere and there is a need for accurate measurements of ablation within penitente fields through time in order to evaluate how well existing energy balance models perform for surfaces with penitentes. The complex surface morphology poses a challenge to measuring the mass loss at snow or glacier surfaces as (i) the spatial distribution of surface lowering within a penitente field is very heterogeneous, and (ii) the steep walls and sharp edges of the penitentes limit the line of sight view for surveying from fixed positions. In this work we explored whether these problems can be solved by using the Xbox Kinect sensor to generate small scale digital terrain models (DTMs) of sample areas of snow and ice penitentes. The study site was Glaciar Tapado in Chile (30°08'S; 69°55'W) where three sample sites were monitored from November 2013 to January 2014. The range of the Kinect sensor was found to be restricted to about 1 m over snow and ice, and scanning was only possible after dusk. Moving the sensor around the penitente field was challenging and often resulted in fragmented scans. However, despite these challenges, the scans obtained could be successfully combined in MeshLab software to produce good surface representations of the penitentes. GPS locations of target stakes in the sample plots allow the DTMs to be orientated correctly in space so the morphology of the penitente field and the volume loss through time can be fully described. At the study site in snow penitentes the Kinect DTM was compared with the quality

  18. Extracting the inclination angle of nerve fibers within the human brain with 3D-PLI independent of system properties

    NASA Astrophysics Data System (ADS)

    Reckfort, Julia; Wiese, Hendrik; Dohmen, Melanie; Grässel, David; Pietrzyk, Uwe; Zilles, Karl; Amunts, Katrin; Axer, Markus

    2013-09-01

    The neuroimaging technique 3D-polarized light imaging (3D-PLI) has opened up new avenues to study the complex nerve fiber architecture of the human brain at sub-millimeter spatial resolution. This polarimetry technique is applicable to histological sections of postmortem brains utilizing the birefringence of nerve fibers caused by the regular arrangement of lipids and proteins in the myelin sheaths surrounding axons. 3D-PLI provides a three-dimensional description of the anatomical wiring scheme defined by the in-section direction angle and the out-of-section inclination angle. To date, 3D-PLI is the only available method that allows bridging the microscopic and the macroscopic description of the fiber architecture of the human brain. Here we introduce a new approach to retrieve the inclination angle of the fibers independently of the properties of the used polarimeters. This is relevant because the image resolution and the signal transmission inuence the measured birefringent signal (retardation) significantly. The image resolution was determined using the USAF- 1951 testchart applying the Rayleigh criterion. The signal transmission was measured by elliptical polarizers applying the Michelson contrast and histological slices of the optic tract of a postmortem brain. Based on these results, a modified retardation-inclination transfer function was proposed to extract the fiber inclination. The comparison of the actual and the inclination angles calculated with the theoretically proposed and the modified transfer function revealed a significant improvement in the extraction of the fiber inclinations.

  19. Techniques for Revealing 3d Hidden Archeological Features: Morphological Residual Models as Virtual-Polynomial Texture Maps

    NASA Astrophysics Data System (ADS)

    Pires, H.; Martínez Rubio, J.; Elorza Arana, A.

    2015-02-01

    The recent developments in 3D scanning technologies are not been accompanied by visualization interfaces. We are still using the same types of visual codes as when maps and drawings were made by hand. The available information in 3D scanning data sets is not being fully exploited by current visualization techniques. In this paper we present recent developments regarding the use of 3D scanning data sets for revealing invisible information from archaeological sites. These sites are affected by a common problem, decay processes, such as erosion, that never ceases its action and endangers the persistence of last vestiges of some peoples and cultures. Rock art engravings, or epigraphical inscriptions, are among the most affected by these processes because they are, due to their one nature, carved at the surface of rocks often exposed to climatic agents. The study and interpretation of these motifs and texts is strongly conditioned by the degree of conservation of the imprints left by our ancestors. Every single detail in the remaining carvings can make a huge difference in the conclusions taken by specialists. We have selected two case-studies severely affected by erosion to present the results of the on-going work dedicated to explore in new ways the information contained in 3D scanning data sets. A new method for depicting subtle morphological features in the surface of objects or sites has been developed. It allows to contrast human patterns still present at the surface but invisible to naked eye or by any other archaeological inspection technique. It was called Morphological Residual Model (MRM) because of its ability to contrast the shallowest morphological details, to which we refer as residuals, contained in the wider forms of the backdrop. Afterwards, we have simulated the process of building Polynomial Texture Maps - a widespread technique that as been contributing to archaeological studies for some years - in a 3D virtual environment using the results of MRM

  20. Automatic Extraction of Planetary Image Features

    NASA Technical Reports Server (NTRS)

    Troglio, G.; LeMoigne, J.; Moser, G.; Serpico, S. B.; Benediktsson, J. A.

    2009-01-01

    With the launch of several Lunar missions such as the Lunar Reconnaissance Orbiter (LRO) and Chandrayaan-1, a large amount of Lunar images will be acquired and will need to be analyzed. Although many automatic feature extraction methods have been proposed and utilized for Earth remote sensing images, these methods are not always applicable to Lunar data that often present low contrast and uneven illumination characteristics. In this paper, we propose a new method for the extraction of Lunar features (that can be generalized to other planetary images), based on the combination of several image processing techniques, a watershed segmentation and the generalized Hough Transform. This feature extraction has many applications, among which image registration.

  1. The effects of extracellular sugar extraction on the 3D-structure of biological soil crusts from different ecosystems

    NASA Astrophysics Data System (ADS)

    Felde, Vincent; Rossi, Federico; Colesie, Claudia; Uteau-Puschmann, Daniel; Felix-Henningsen, Peter; Peth, Stephan; De Philippis, Roberto

    2015-04-01

    Biological soil crusts (BSCs) play important roles in the hydrological cycles of many different ecosystems around the world. In arid and semi-arid regions, they alter the availability and redistribution of water. Especially in early successional stage BSCs, this feature can be attributed to the presence and characteristics of extracellular polymeric substances (EPS) that are excreted by the crusts' organisms. In a previous study, the extraction of EPS from BSCs of the SW United States lead to a significant change in their hydrological behavior, namely the sorptivity of water (Rossi et al. 2012). This was concluded to be the effect of a change in the pore structure of these crusts, which is why in this work we investigated the effect of the EPS-extraction on soil structure using 3D-computed micro-tomography (µCT). We studied different types of BSCs from Svalbard, Germany, Israel and South Africa with varying grain sizes and species compositions (from green algae to light and dark cyanobacterial crusts with and without lichens and/or mosses). Unlike other EPS-extraction methods, the one utilized here is aimed at removing the extracellular matrix from crust samples whilst acting non-destructively (Rossi et al. 2012). For every crust sample, we physically cut out a small piece (1cm) from a larger sample contained in Petri dish, and scanned it in a CT at a high resolution (voxel edge length: 7µm). After putting it back in the dish, approximately in the same former position, it was treated for EPS-extraction and then removed and scanned again in order to check for a possible effect of the EPS-extraction. Our results show that the utilized EPS-extraction method had varying extraction efficiencies: while in some cases the amount removed was barely significant, in other cases up to 50% of the total content was recovered. Notwithstanding, no difference in soil micro-structure could be detected, neither in total porosity, nor in the distribution of pore sizes, the

  2. Large datasets: Segmentation, feature extraction, and compression

    SciTech Connect

    Downing, D.J.; Fedorov, V.; Lawkins, W.F.; Morris, M.D.; Ostrouchov, G.

    1996-07-01

    Large data sets with more than several mission multivariate observations (tens of megabytes or gigabytes of stored information) are difficult or impossible to analyze with traditional software. The amount of output which must be scanned quickly dilutes the ability of the investigator to confidently identify all the meaningful patterns and trends which may be present. The purpose of this project is to develop both a theoretical foundation and a collection of tools for automated feature extraction that can be easily customized to specific applications. Cluster analysis techniques are applied as a final step in the feature extraction process, which helps make data surveying simple and effective.

  3. HS3D, A Dataset of Homo Sapiens Splice Regions, and its Extraction Procedure from a Major Public Database

    NASA Astrophysics Data System (ADS)

    Pollastro, Pasquale; Rampone, Salvatore

    The aim of this work is to describe a cleaning procedure of GenBank data, producing material to train and to assess the prediction accuracy of computational approaches for gene characterization. A procedure (GenBank2HS3D) has been defined, producing a dataset (HS3D - Homo Sapiens Splice Sites Dataset) of Homo Sapiens Splice regions extracted from GenBank (Rel.123 at this time). It selects, from the complete GenBank Primate Division, entries of Human Nuclear DNA according with several assessed criteria; then it extracts exons and introns from these entries (actually 4523 + 3802). Donor and acceptor sites are then extracted as windows of 140 nucleotides around each splice site (3799 + 3799). After discarding windows not including canonical GT-AG junctions (65 + 74), including insufficient data (not enough material for a 140 nucleotide window) (686 + 589), including not AGCT bases (29 + 30), and redundant (218 + 226), the remaining windows (2796 + 2880) are reported in the dataset. Finally, windows of false splice sites are selected by searching canonical GT-AG pairs in not splicing positions (271 937 + 332 296). The false sites in a range +/- 60 from a true splice site are marked as proximal. HS3D, release 1.2 at this time, is available at the Web server of the University of Sannio: http://www.sci.unisannio.it/docenti/rampone/.

  4. Semi-automated extraction and delineation of 3D roads of street scene from mobile laser scanning point clouds

    NASA Astrophysics Data System (ADS)

    Yang, Bisheng; Fang, Lina; Li, Jonathan

    2013-05-01

    Accurate 3D road information is important for applications such as road maintenance and virtual 3D modeling. Mobile laser scanning (MLS) is an efficient technique for capturing dense point clouds that can be used to construct detailed road models for large areas. This paper presents a method for extracting and delineating roads from large-scale MLS point clouds. The proposed method partitions MLS point clouds into a set of consecutive "scanning lines", which each consists of a road cross section. A moving window operator is used to filter out non-ground points line by line, and curb points are detected based on curb patterns. The detected curb points are tracked and refined so that they are both globally consistent and locally similar. To evaluate the validity of the proposed method, experiments were conducted using two types of street-scene point clouds captured by Optech's Lynx Mobile Mapper System. The completeness, correctness, and quality of the extracted roads are over 94.42%, 91.13%, and 91.3%, respectively, which proves the proposed method is a promising solution for extracting 3D roads from MLS point clouds.

  5. Tracking naturally occurring indoor features in 2-D and 3-D with lidar range/amplitude data

    SciTech Connect

    Adams, M.D.; Kerstens, A.

    1998-09-01

    Sensor-data processing for the interpretation of a mobile robot`s indoor environment, and the manipulation of this data for reliable localization, are still some of the most important issues in robotics. This article presents algorithms that determine the true position of a mobile robot, based on real 2-D and 3-D optical range and intensity data. The authors start with the physics of the particular type of sensor used, so that the extraction of reliable and repeatable information (namely, edge coordinates) can be determined, taking into account the noise associated with each range sample and the possibility of optical multiple-path effects. Again, applying the physical model of the sensor, the estimated positions of the mobile robot and the uncertainty in these positions are determined. They demonstrate real experiments using 2-D and 3-D scan data taken in indoor environments. To update the robot`s position reliably, the authors address the problem of matching the information recorded in a scan to, first, an a priori map, and second, to information recorded in previous scans, eliminating the need for an a priori map.

  6. Generalized feature extraction using expansion matching.

    PubMed

    Nandy, D; Ben-Arie, J

    1999-01-01

    A novel generalized feature extraction method based on the expansion matching (EXM) method and on the Karhunen-Loeve transform (KLT) is presented. The method provides an efficient way to locate complex features of interest like corners and junctions with reduced number of filtering operations. The EXM method is used to design optimal detectors for a set of model elementary features. The KL representation of these model EXM detectors is used to filter the image and detect candidate interest points from the energy peaks of the eigen coefficients. The KL coefficients at these candidate points are then used to efficiently reconstruct the response and differentiate real junctions and corners from arbitrary features in the image. The method is robust to additive noise and is able to successfully extract, classify, and find the myriad compositions of corner and junction features formed by combinations of two or more edges or lines. This method differs from previous works in several aspects. First, it treats the features not as distinct entities, but as combinations of elementary features. Second, it employs an optimal set of elementary feature detectors based on the EM approach. Third, the method incorporates a significant reduction in computational complexity by representing a large set of EXM filters by a relatively small number of eigen filters derived by the KL transform of the basic EXM filter set. This is a novel application of the KL transform, which is usually employed to represent signals and not impulse responses as in our present work. PMID:18262862

  7. Continuous section extraction and over-underbreak detection of tunnel based on 3D laser technology and image analysis

    NASA Astrophysics Data System (ADS)

    Wang, Weixing; Wang, Zhiwei; Han, Ya; Li, Shuang; Zhang, Xin

    2015-03-01

    Over Underbreak detection of road and solve the problemof the roadway data collection difficulties, this paper presents a new method of continuous section extraction and Over Underbreak detection of road based on 3D laser scanning technology and image processing, the method is divided into the following three steps: based on Canny edge detection, local axis fitting, continuous extraction section and Over Underbreak detection of section. First, after Canny edge detection, take the least-squares curve fitting method to achieve partial fitting in axis. Then adjust the attitude of local roadway that makes the axis of the roadway be consistent with the direction of the extraction reference, and extract section along the reference direction. Finally, we compare the actual cross-sectional view and the cross-sectional design to complete Overbreak detected. Experimental results show that the proposed method have a great advantage in computing costs and ensure cross-section orthogonal intercept terms compared with traditional detection methods.

  8. Sub-100 nm biodegradable nanoparticles: in vitro release features and toxicity testing in 2D and 3D cell cultures

    NASA Astrophysics Data System (ADS)

    Biondi, Marco; Guarnieri, Daniela; Yu, Hui; Belli, Valentina; Netti, Paolo Antonio

    2013-02-01

    A big challenge in tumor targeting by nanoparticles (NPs), taking advantage of the enhanced permeability and retention effect, is the fabrication of small size devices for enhanced tumor penetration, which is considered fundamental to improve chemotherapy efficacy. The purposes of this study are (i) to engineer the formulation of doxorubicin-loaded poly(d,l-lactic-co-glycolic acid) (PLGA)-block-poly(ethylene glycol) (PEG) NPs to obtain <100 nm devices and (ii) to translate standard 2D cytotoxicity studies to 3D collagen systems in which an initial step gradient of the NPs is present. Doxorubicin release can be prolonged for days to weeks depending on the NP formulation and the pH of the release medium. Sub-100 nm NPs are effectively internalized by HeLa cells in 2D and are less cytotoxic than free doxorubicin. In 3D, <100 nm NPs are significantly more toxic than larger ones towards HeLa cells, and the cell death rate is affected by the contributions of drug release and device transport through collagen. Thus, the reduction of NP size is a fundamental feature from both a technological and a biological point of view and must be properly engineered to optimize the tumor response to the NPs.

  9. Extraction of sandy bedforms features through geodesic morphometry

    NASA Astrophysics Data System (ADS)

    Debese, Nathalie; Jacq, Jean-José; Garlan, Thierry

    2016-09-01

    State-of-art echosounders reveal fine-scale details of mobile sandy bedforms, which are commonly found on continental shelfs. At present, their dynamics are still far from being completely understood. These bedforms are a serious threat to navigation security, anthropic structures and activities, placing emphasis on research breakthroughs. Bedform geometries and their dynamics are closely linked; therefore, one approach is to develop semi-automatic tools aiming at extracting their structural features from bathymetric datasets. Current approaches mimic manual processes or rely on morphological simplification of bedforms. The 1D and 2D approaches cannot address the wide ranges of both types and complexities of bedforms. In contrast, this work attempts to follow a 3D global semi-automatic approach based on a bathymetric TIN. The currently extracted primitives are the salient ridge and valley lines of the sand structures, i.e., waves and mega-ripples. The main difficulty is eliminating the ripples that are found to heavily overprint any observations. To this end, an anisotropic filter that is able to discard these structures while still enhancing the wave ridges is proposed. The second part of the work addresses the semi-automatic interactive extraction and 3D augmented display of the main lines structures. The proposed protocol also allows geoscientists to interactively insert topological constraints.

  10. In situ 2D-extraction of DNA wheels by 3D through-solution transport.

    PubMed

    Yonamine, Yusuke; Cervantes-Salguero, Keitel; Nakanishi, Waka; Kawamata, Ibuki; Minami, Kosuke; Komatsu, Hirokazu; Murata, Satoshi; Hill, Jonathan P; Ariga, Katsuhiko

    2015-12-28

    Controlled transfer of DNA nanowheels from a hydrophilic to a hydrophobic surface was achieved by complexation of the nanowheels with a cationic lipid (2C12N(+)). 2D surface-assisted extraction, '2D-extraction', enabled structure-persistent transfer of DNA wheels, which could not be achieved by simple drop-casting. PMID:26583486

  11. Extraction of linear features on SAR imagery

    NASA Astrophysics Data System (ADS)

    Liu, Junyi; Li, Deren; Mei, Xin

    2006-10-01

    Linear features are usually extracted from SAR imagery by a few edge detectors derived from the contrast ratio edge detector with a constant probability of false alarm. On the other hand, the Hough Transform is an elegant way of extracting global features like curve segments from binary edge images. Randomized Hough Transform can reduce the computation time and memory usage of the HT drastically. While Randomized Hough Transform will bring about a great deal of cells invalid during the randomized sample. In this paper, we propose a new approach to extract linear features on SAR imagery, which is an almost automatic algorithm based on edge detection and Randomized Hough Transform. The presented improved method makes full use of the directional information of each edge candidate points so as to solve invalid cumulate problems. Applied result is in good agreement with the theoretical study, and the main linear features on SAR imagery have been extracted automatically. The method saves storage space and computational time, which shows its effectiveness and applicability.

  12. The Radiological Feature of Anterior Occiput-to-Axis Screw Fixation as it Guides the Screw Trajectory on 3D Printed Models: A Feasibility Study on 3D Images and 3D Printed Models

    PubMed Central

    Wu, Ai-Min; Wang, Sheng; Weng, Wan-Qing; Shao, Zhen-Xuan; Yang, Xin-Dong; Wang, Jian-Shun; Xu, Hua-Zi; Chi, Yong-Long

    2014-01-01

    Abstract Anterior occiput-to-axis screw fixation is more suitable than a posterior approach for some patients with a history of posterior surgery. The complex osseous anatomy between the occiput and the axis causes a high risk of injury to neurological and vascular structures, and it is important to have an accurate screw trajectory to guide anterior occiput-to-axis screw fixation. Thirty computed tomography (CT) scans of upper cervical spines were obtained for three-dimensional (3D) reconstruction. Cylinders (1.75 mm radius) were drawn to simulate the trajectory of an anterior occiput-to-axis screw. The imitation screw was adjusted to 4 different angles and measured, as were the values of the maximized anteroposterior width and the left-right width of the occiput (C0) to the C1 and C1 to C2 joints. Then, the 3D models were printed, and an angle guide device was used to introduce the screws into the 3D models referring to the angles calculated from the 3D images. We found the screw angle ranged from α1 (left: 4.99 ± 4.59°; right: 4.28 ± 5.45°) to α2 (left: 20.22 ± 3.61°; right: 19.63 ± 4.94°); on the lateral view, the screw angle ranged from β1 (left: 13.13 ± 4.93°; right: 11.82 ± 5.64°) to β2 (left: 34.86 ± 6.00°; right: 35.01 ± 5.77°). No statistically significant difference was found between the data of the left and right sides. On the 3D printed models, all of the anterior occiput-to-axis screws were successfully introduced, and none of them penetrated outside of the cortex; the mean α4 was 12.00 ± 4.11 (left) and 12.25 ± 4.05 (right), and the mean β4 was 23.44 ± 4.21 (left) and 22.75 ± 4.41 (right). No significant difference was found between α4 and β4 on the 3D printed models and α3 and β3 calculated from the 3D digital images of the left and right sides. Aided with the angle guide device, we could achieve an optimal screw trajectory for anterior occiput-to-axis screw fixation on

  13. Adaptive unsupervised slow feature analysis for feature extraction

    NASA Astrophysics Data System (ADS)

    Gu, Xingjian; Liu, Chuancai; Wang, Sheng

    2015-03-01

    Slow feature analysis (SFA) extracts slowly varying features out of the input data and has been successfully applied on pattern recognition. However, SFA heavily relies on the constructed time series when SFA is applied on databases that neither have obvious temporal structure nor have label information. Traditional SFA constructs time series based on k-nearest neighborhood (k-NN) criterion. Specifically, the time series set constructed by k-NN criterion is likely to include noisy time series or lose suitable time series because the parameter k is difficult to determine. To overcome these problems, a method called adaptive unsupervised slow feature analysis (AUSFA) is proposed. First, AUSFA designs an adaptive criterion to generate time series for characterizing submanifold. The constructed time series have two properties: (1) two points of time series lie on the same submanifold and (2) the submanifold of the time series is smooth. Second, AUSFA seeks projections that simultaneously minimize the slowness scatter and maximize the fastness scatter to extract slow discriminant features. Extensive experimental results on three benchmark face databases demonstrate the effectiveness of our proposed method.

  14. Report of subpanel on feature extraction

    NASA Technical Reports Server (NTRS)

    1982-01-01

    The state of knowledge in feature extraction for Earth resource observation systems is reviewed and research tasks are proposed. Issues in the subpixel feature estimation problem are defined as: (1) the identification of image models which adequately describe the data and the sensor it is using; (2) the construction of local feature models based on those image models; and (3) the problem of trying to understand these effects of preprocessing on the entire process. The development of ground control point (GCP) libraries for automated selection presents two concerns. One is the organization of these GCP libraries for rectification problems, i.e., the problems of automatically selecting by computer the specific GCP's for particular registration tasks. Second is the importance of integrating ground control patterns in a data base management system, allowing interface to a large number of sensor image types with an automatic selection system. The development of data validation criteria for the comparison of different extraction techniques is also discussed.

  15. ESPript/ENDscript: extracting and rendering sequence and 3D information from atomic structures of proteins

    PubMed Central

    Gouet, Patrice; Robert, Xavier; Courcelle, Emmanuel

    2003-01-01

    The fortran program ESPript was created in 1993, to display on a PostScript figure multiple sequence alignments adorned with secondary structure elements. A web server was made available in 1999 and ESPript has been linked to three major web tools: ProDom which identifies protein domains, PredictProtein which predicts secondary structure elements and NPS@ which runs sequence alignment programs. A web server named ENDscript was created in 2002 to facilitate the generation of ESPript figures containing a large amount of information. ENDscript uses programs such as BLAST, Clustal and PHYLODENDRON to work on protein sequences and such as DSSP, CNS and MOLSCRIPT to work on protein coordinates. It enables the creation, from a single Protein Data Bank identifier, of a multiple sequence alignment figure adorned with secondary structure elements of each sequence of known 3D structure. Similar 3D structures are superimposed in turn with the program PROFIT and a final figure is drawn with BOBSCRIPT, which shows sequence and structure conservation along the Cα trace of the query. ESPript and ENDscript are available at http://genopole.toulouse.inra.fr/ESPript. PMID:12824317

  16. The effect of parameters of equilibrium-based 3-D biomechanical models on extracted muscle synergies during isometric lumbar exertion.

    PubMed

    Eskandari, A H; Sedaghat-Nejad, E; Rashedi, E; Sedighi, A; Arjmand, N; Parnianpour, M

    2016-04-11

    A hallmark of more advanced models is their higher details of trunk muscles represented by a larger number of muscles. The question is if in reality we control these muscles individually as independent agents or we control groups of them called "synergy". To address this, we employed a 3-D biomechanical model of the spine with 18 trunk muscles that satisfied equilibrium conditions at L4/5, with different cost functions. The solutions of several 2-D and 3-D tasks were arranged in a data matrix and the synergies were computed by using non-negative matrix factorization (NMF) algorithms. Variance accounted for (VAF) was used to evaluate the number of synergies that emerged by the analysis, which were used to reconstruct the original muscle activations. It was showed that four and six muscle synergies were adequate to reconstruct the input data of 2-D and 3-D torque space analysis. The synergies were different by choosing alternative cost functions as expected. The constraints affected the extracted muscle synergies, particularly muscles that participated in more than one functional tasks were influenced substantially. The compositions of extracted muscle synergies were in agreement with experimental studies on healthy participants. The following computational methods show that the synergies can reduce the complexity of load distributions and allow reduced dimensional space to be used in clinical settings. PMID:26747515

  17. Algorithm of pulmonary emphysema extraction using thoracic 3-D CT images

    NASA Astrophysics Data System (ADS)

    Saita, Shinsuke; Kubo, Mitsuru; Kawata, Yoshiki; Niki, Noboru; Nakano, Yasutaka; Ohmatsu, Hironobu; Tominaga, Keigo; Eguchi, Kenji; Moriyama, Noriyuki

    2008-03-01

    Emphysema patients have the tendency to increase due to aging and smoking. Emphysematous disease destroys alveolus and to repair is impossible, thus early detection is essential. CT value of lung tissue decreases due to the destruction of lung structure. This CT value becomes lower than the normal lung- low density absorption region or referred to as Low Attenuation Area (LAA). So far, the conventional way of extracting LAA by simple thresholding has been proposed. However, the CT value of CT image fluctuates due to the measurement conditions, with various bias components such as inspiration, expiration and congestion. It is therefore necessary to consider these bias components in the extraction of LAA. We removed these bias components and we proposed LAA extraction algorithm. This algorithm has been applied to the phantom image. Then, by using the low dose CT(normal: 30 cases, obstructive lung disease: 26 cases), we extracted early stage LAA and quantitatively analyzed lung lobes using lung structure.

  18. Feature extraction via KPCA for classification of gait patterns.

    PubMed

    Wu, Jianning; Wang, Jue; Liu, Li

    2007-06-01

    Automated recognition of gait pattern change is important in medical diagnostics as well as in the early identification of at-risk gait in the elderly. We evaluated the use of Kernel-based Principal Component Analysis (KPCA) to extract more gait features (i.e., to obtain more significant amounts of information about human movement) and thus to improve the classification of gait patterns. 3D gait data of 24 young and 24 elderly participants were acquired using an OPTOTRAK 3020 motion analysis system during normal walking, and a total of 36 gait spatio-temporal and kinematic variables were extracted from the recorded data. KPCA was used first for nonlinear feature extraction to then evaluate its effect on a subsequent classification in combination with learning algorithms such as support vector machines (SVMs). Cross-validation test results indicated that the proposed technique could allow spreading the information about the gait's kinematic structure into more nonlinear principal components, thus providing additional discriminatory information for the improvement of gait classification performance. The feature extraction ability of KPCA was affected slightly with different kernel functions as polynomial and radial basis function. The combination of KPCA and SVM could identify young-elderly gait patterns with 91% accuracy, resulting in a markedly improved performance compared to the combination of PCA and SVM. These results suggest that nonlinear feature extraction by KPCA improves the classification of young-elderly gait patterns, and holds considerable potential for future applications in direct dimensionality reduction and interpretation of multiple gait signals. PMID:17509708

  19. Sparse Feature Extraction for Pose-Tolerant Face Recognition.

    PubMed

    Abiantun, Ramzi; Prabhu, Utsav; Savvides, Marios

    2014-10-01

    Automatic face recognition performance has been steadily improving over years of research, however it remains significantly affected by a number of factors such as illumination, pose, expression, resolution and other factors that can impact matching scores. The focus of this paper is the pose problem which remains largely overlooked in most real-world applications. Specifically, we focus on one-to-one matching scenarios where a query face image of a random pose is matched against a set of gallery images. We propose a method that relies on two fundamental components: (a) A 3D modeling step to geometrically correct the viewpoint of the face. For this purpose, we extend a recent technique for efficient synthesis of 3D face models called 3D Generic Elastic Model. (b) A sparse feature extraction step using subspace modeling and ℓ1-minimization to induce pose-tolerance in coefficient space. This in return enables the synthesis of an equivalent frontal-looking face, which can be used towards recognition. We show significant performance improvements in verification rates compared to commercial matchers, and also demonstrate the resilience of the proposed method with respect to degrading input quality. We find that the proposed technique is able to match non-frontal images to other non-frontal images of varying angles. PMID:26352635

  20. Feature extraction for structural dynamics model validation

    SciTech Connect

    Hemez, Francois; Farrar, Charles; Park, Gyuhae; Nishio, Mayuko; Worden, Keith; Takeda, Nobuo

    2010-11-08

    This study focuses on defining and comparing response features that can be used for structural dynamics model validation studies. Features extracted from dynamic responses obtained analytically or experimentally, such as basic signal statistics, frequency spectra, and estimated time-series models, can be used to compare characteristics of structural system dynamics. By comparing those response features extracted from experimental data and numerical outputs, validation and uncertainty quantification of numerical model containing uncertain parameters can be realized. In this study, the applicability of some response features to model validation is first discussed using measured data from a simple test-bed structure and the associated numerical simulations of these experiments. issues that must be considered were sensitivity, dimensionality, type of response, and presence or absence of measurement noise in the response. Furthermore, we illustrate a comparison method of multivariate feature vectors for statistical model validation. Results show that the outlier detection technique using the Mahalanobis distance metric can be used as an effective and quantifiable technique for selecting appropriate model parameters. However, in this process, one must not only consider the sensitivity of the features being used, but also correlation of the parameters being compared.

  1. Real-time 3D visualization of the thoraco-abdominal surface during breathing with body movement and deformation extraction.

    PubMed

    Povšič, K; Jezeršek, M; Možina, J

    2015-07-01

    Real-time 3D visualization of the breathing displacements can be a useful diagnostic tool in order to immediately observe the most active regions on the thoraco-abdominal surface. The developed method is capable of separating non-relevant torso movement and deformations from the deformations that are solely related to breathing. This makes it possible to visualize only the breathing displacements. The system is based on the structured laser triangulation principle, with simultaneous spatial and color data acquisition of the thoraco-abdominal region. Based on the tracking of the attached passive markers, the torso movement and deformation is compensated using rigid and non-rigid transformation models on the three-dimensional (3D) data. The total time of 3D data processing together with visualization equals 20 ms per cycle.In vitro verification of the rigid movement extraction was performed using the iterative closest point algorithm as a reference. Furthermore, a volumetric evaluation on a live subject was performed to establish the accuracy of the rigid and non-rigid model. The root mean square deviation between the measured and the reference volumes shows an error of  ±0.08 dm(3) for rigid movement extraction. Similarly, the error was calculated to be  ±0.02 dm(3) for torsional deformation extraction and  ±0.11 dm(3) for lateral bending deformation extraction. The results confirm that during the torso movement and deformation, the proposed method is sufficiently accurate to visualize only the displacements related to breathing. The method can be used, for example, during the breathing exercise on an indoor bicycle or a treadmill. PMID:26020444

  2. Registration of overlapping 3D point clouds using extracted line segments. (Polish Title: Rejestracja chmur punktów 3D w oparciu o wyodrębnione krawędzie)

    NASA Astrophysics Data System (ADS)

    Poręba, M.; Goulette, F.

    2014-12-01

    The registration of 3D point clouds collected from different scanner positions is necessary in order to avoid occlusions, ensure a full coverage of areas, and collect useful data for analyzing and documenting the surrounding environment. This procedure involves three main stages: 1) choosing appropriate features, which can be reliably extracted; 2) matching conjugate primitives; 3) estimating the transformation parameters. Currently, points and spheres are most frequently chosen as the registration features. However, due to limited point cloud resolution, proper identification and precise measurement of a common point within the overlapping laser data is almost impossible. One possible solution to this problem may be a registration process based on the Iterative Closest Point (ICP) algorithm or its variation. Alternatively, planar and linear feature-based registration techniques can also be applied. In this paper, we propose the use of line segments obtained from intersecting planes modelled within individual scans. Such primitives can be easily extracted even from low-density point clouds. Working with synthetic data, several existing line-based registration methods are evaluated according to their robustness to noise and the precision of the estimated transformation parameters. For the purpose of quantitative assessment, an accuracy criterion based on a modified Hausdorff distance is defined. Since an automated matching of segments is a challenging task that influences the correctness of the transformation parameters, a correspondence-finding algorithm is developed. The tests show that our matching algorithm provides a correct p airing with an accuracy of 99 % at least, and about 8% of omitted line pairs.

  3. Automatic segmentation of solitary pulmonary nodules based on local intensity structure analysis and 3D neighborhood features in 3D chest CT images

    NASA Astrophysics Data System (ADS)

    Chen, Bin; Kitasaka, Takayuki; Honma, Hirotoshi; Takabatake, Hirotsugu; Mori, Masaki; Natori, Hiroshi; Mori, Kensaku

    2012-03-01

    This paper presents a solitary pulmonary nodule (SPN) segmentation method based on local intensity structure analysis and neighborhood feature analysis in chest CT images. Automated segmentation of SPNs is desirable for a chest computer-aided detection/diagnosis (CAS) system since a SPN may indicate early stage of lung cancer. Due to the similar intensities of SPNs and other chest structures such as blood vessels, many false positives (FPs) are generated by nodule detection methods. To reduce such FPs, we introduce two features that analyze the relation between each segmented nodule candidate and it neighborhood region. The proposed method utilizes a blob-like structure enhancement (BSE) filter based on Hessian analysis to augment the blob-like structures as initial nodule candidates. Then a fine segmentation is performed to segment much more accurate region of each nodule candidate. FP reduction is mainly addressed by investigating two neighborhood features based on volume ratio and eigenvector of Hessian that are calculates from the neighborhood region of each nodule candidate. We evaluated the proposed method by using 40 chest CT images, include 20 standard-dose CT images that we randomly chosen from a local database and 20 low-dose CT images that were randomly chosen from a public database: LIDC. The experimental results revealed that the average TP rate of proposed method was 93.6% with 12.3 FPs/case.

  4. Automated Fluid Feature Extraction from Transient Simulations

    NASA Technical Reports Server (NTRS)

    Haimes, Robert; Lovely, David

    1999-01-01

    In the past, feature extraction and identification were interesting concepts, but not required to understand the underlying physics of a steady flow field. This is because the results of the more traditional tools like iso-surfaces, cuts and streamlines were more interactive and easily abstracted so they could be represented to the investigator. These tools worked and properly conveyed the collected information at the expense of much interaction. For unsteady flow-fields, the investigator does not have the luxury of spending time scanning only one "snap-shot" of the simulation. Automated assistance is required in pointing out areas of potential interest contained within the flow. This must not require a heavy compute burden (the visualization should not significantly slow down the solution procedure for co-processing environments like pV3). And methods must be developed to abstract the feature and display it in a manner that physically makes sense. The following is a list of the important physical phenomena found in transient (and steady-state) fluid flow: (1) Shocks, (2) Vortex cores, (3) Regions of recirculation, (4) Boundary layers, (5) Wakes. Three papers and an initial specification for the (The Fluid eXtraction tool kit) FX Programmer's guide were included. The papers, submitted to the AIAA Computational Fluid Dynamics Conference, are entitled : (1) Using Residence Time for the Extraction of Recirculation Regions, (2) Shock Detection from Computational Fluid Dynamics results and (3) On the Velocity Gradient Tensor and Fluid Feature Extraction.

  5. Geodesic Distance Algorithm for Extracting the Ascending Aorta from 3D CT Images

    PubMed Central

    Jang, Yeonggul; Jung, Ho Yub; Hong, Youngtaek; Cho, Iksung; Shim, Hackjoon; Chang, Hyuk-Jae

    2016-01-01

    This paper presents a method for the automatic 3D segmentation of the ascending aorta from coronary computed tomography angiography (CCTA). The segmentation is performed in three steps. First, the initial seed points are selected by minimizing a newly proposed energy function across the Hough circles. Second, the ascending aorta is segmented by geodesic distance transformation. Third, the seed points are effectively transferred through the next axial slice by a novel transfer function. Experiments are performed using a database composed of 10 patients' CCTA images. For the experiment, the ground truths are annotated manually on the axial image slices by a medical expert. A comparative evaluation with state-of-the-art commercial aorta segmentation algorithms shows that our approach is computationally more efficient and accurate under the DSC (Dice Similarity Coefficient) measurements. PMID:26904151

  6. A projection method to extract biological membrane models from 3D material models.

    PubMed

    Roohbakhshan, Farshad; Duong, Thang X; Sauer, Roger A

    2016-05-01

    This paper presents a projection method for deriving membrane models from the corresponding three-dimensional material models. As a particular example the anisotropic Holzapfel-Gasser-Ogden model is considered. The projection procedure is based on the kinematical and constitutive assumptions of a general membrane theory, considering the membrane to be a general two-dimensional manifold. By assuming zero transverse stress, the Lagrange multiplier associated with the incompressibility constraint can be eliminated from the formulation. The resulting nonlinear model is discretized and linearized within the finite element method. Several numerical examples are shown, considering quadratic Lagrange and NURBS finite elements. These show that the proposed model is in very good agreement with analytical solutions and with full 3D finite element computations. PMID:26455810

  7. Multi-sourced, 3D geometric characterization of volcanogenic karst features: Integrating lidar, sonar, and geophysical datasets (Invited)

    NASA Astrophysics Data System (ADS)

    Sharp, J. M.; Gary, M. O.; Reyes, R.; Halihan, T.; Fairfield, N.; Stone, W. C.

    2009-12-01

    Karstic aquifers can form very complex hydrogeological systems and 3-D mapping has been difficult, but Lidar, phased array sonar, and improved earth resistivity techniques show promise in this and in linking metadata to models. Zacatón, perhaps the Earth’s deepest cenote, has a sub-aquatic void space exceeding 7.5 x 106 cubic m3. It is the focus of this study which has created detailed 3D maps of the system. These maps include data from above and beneath the the water table and within the rock matrix to document the extent of the immense karst features and to interpret the geologic processes that formed them. Phase 1 used high resolution (20 mm) Lidar scanning of surficial features of four large cenotes. Scan locations, selected to achieve full feature coverage once registered, were established atop surface benchmarks with UTM coordinates established using GPS and Total Stations. The combined datasets form a geo-registered mesh of surface features down to water level in the cenotes. Phase 2 conducted subsurface imaging using Earth Resistivity Imaging (ERI) geophysics. ERI identified void spaces isolated from open flow conduits. A unique travertine morphology exists in which some cenotes are dry or contain shallow lakes with flat travertine floors; some water-filled cenotes have flat floors without the cone of collapse material; and some have collapse cones. We hypothesize that the floors may have large water-filled voids beneath them. Three separate flat travertine caps were imaged: 1) La Pilita, which is partially open, exposing cap structure over a deep water-filled shaft; 2) Poza Seca, which is dry and vegetated; and 3) Tule, which contains a shallow (<1 m) lake. A fourth line was run adjacent to cenote Verde. La Pilita ERI, verified by SCUBA, documented the existence of large water-filled void zones ERI at Poza Seca showed a thin cap overlying a conductive zone extending to at least 25 m depth beneath the cap with no lower boundary of this zone evident

  8. Modified kernel-based nonlinear feature extraction.

    SciTech Connect

    Ma, J.; Perkins, S. J.; Theiler, J. P.; Ahalt, S.

    2002-01-01

    Feature Extraction (FE) techniques are widely used in many applications to pre-process data in order to reduce the complexity of subsequent processes. A group of Kernel-based nonlinear FE ( H E ) algorithms has attracted much attention due to their high performance. However, a serious limitation that is inherent in these algorithms -- the maximal number of features extracted by them is limited by the number of classes involved -- dramatically degrades their flexibility. Here we propose a modified version of those KFE algorithms (MKFE), This algorithm is developed from a special form of scatter-matrix, whose rank is not determined by the number of classes involved, and thus breaks the inherent limitation in those KFE algorithms. Experimental results suggest that MKFE algorithm is .especially useful when the training set is small.

  9. LiDAR Segmentation using Suitable Seed Points for 3D Building Extraction

    NASA Astrophysics Data System (ADS)

    Abdullah, S. M.; Awrangjeb, M.; Lu, G.

    2014-08-01

    Effective building detection and roof reconstruction has an influential demand over the remote sensing research community. In this paper, we present a new automatic LiDAR point cloud segmentation method using suitable seed points for building detection and roof plane extraction. Firstly, the LiDAR point cloud is separated into "ground" and "non-ground" points based on the analysis of DEM with a height threshold. Each of the non-ground point is marked as coplanar or non-coplanar based on a coplanarity analysis. Commencing from the maximum LiDAR point height towards the minimum, all the LiDAR points on each height level are extracted and separated into several groups based on 2D distance. From each group, lines are extracted and a coplanar point which is the nearest to the midpoint of each line is considered as a seed point. This seed point and its neighbouring points are utilised to generate the plane equation. The plane is grown in a region growing fashion until no new points can be added. A robust rule-based tree removal method is applied subsequently to remove planar segments on trees. Four different rules are applied in this method. Finally, the boundary of each object is extracted from the segmented LiDAR point cloud. The method is evaluated with six different data sets consisting hilly and densely vegetated areas. The experimental results indicate that the proposed method offers a high building detection and roof plane extraction rates while compared to a recently proposed method.

  10. 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.

  11. Automatic Feature Extraction from Planetary Images

    NASA Technical Reports Server (NTRS)

    Troglio, Giulia; Le Moigne, Jacqueline; Benediktsson, Jon A.; Moser, Gabriele; Serpico, Sebastiano B.

    2010-01-01

    With the launch of several planetary missions in the last decade, a large amount of planetary images has already been acquired and much more will be available for analysis in the coming years. The image data need to be analyzed, preferably by automatic processing techniques because of the huge amount of data. Although many automatic feature extraction methods have been proposed and utilized for Earth remote sensing images, these methods are not always applicable to planetary data that often present low contrast and uneven illumination characteristics. Different methods have already been presented for crater extraction from planetary images, but the detection of other types of planetary features has not been addressed yet. Here, we propose a new unsupervised method for the extraction of different features from the surface of the analyzed planet, based on the combination of several image processing techniques, including a watershed segmentation and the generalized Hough Transform. The method has many applications, among which image registration and can be applied to arbitrary planetary images.

  12. A neuro-fuzzy system for extracting environment features based on ultrasonic sensors.

    PubMed

    Marichal, Graciliano Nicolás; Hernández, Angela; Acosta, Leopoldo; González, Evelio José

    2009-01-01

    In this paper, a method to extract features of the environment based on ultrasonic sensors is presented. A 3D model of a set of sonar systems and a workplace has been developed. The target of this approach is to extract in a short time, while the vehicle is moving, features of the environment. Particularly, the approach shown in this paper has been focused on determining walls and corners, which are very common environment features. In order to prove the viability of the devised approach, a 3D simulated environment has been built. A Neuro-Fuzzy strategy has been used in order to extract environment features from this simulated model. Several trials have been carried out, obtaining satisfactory results in this context. After that, some experimental tests have been conducted using a real vehicle with a set of sonar systems. The obtained results reveal the satisfactory generalization properties of the approach in this case. PMID:22303160

  13. A Neuro-Fuzzy System for Extracting Environment Features Based on Ultrasonic Sensors

    PubMed Central

    Marichal, Graciliano Nicolás; Hernández, Angela; Acosta, Leopoldo; González, Evelio José

    2009-01-01

    In this paper, a method to extract features of the environment based on ultrasonic sensors is presented. A 3D model of a set of sonar systems and a workplace has been developed. The target of this approach is to extract in a short time, while the vehicle is moving, features of the environment. Particularly, the approach shown in this paper has been focused on determining walls and corners, which are very common environment features. In order to prove the viability of the devised approach, a 3D simulated environment has been built. A Neuro-Fuzzy strategy has been used in order to extract environment features from this simulated model. Several trials have been carried out, obtaining satisfactory results in this context. After that, some experimental tests have been conducted using a real vehicle with a set of sonar systems. The obtained results reveal the satisfactory generalization properties of the approach in this case. PMID:22303160

  14. Automated Extraction of Secondary Flow Features

    NASA Technical Reports Server (NTRS)

    Dorney, Suzanne M.; Haimes, Robert

    2005-01-01

    The use of Computational Fluid Dynamics (CFD) has become standard practice in the design and development of the major components used for air and space propulsion. To aid in the post-processing and analysis phase of CFD many researchers now use automated feature extraction utilities. These tools can be used to detect the existence of such features as shocks, vortex cores and separation and re-attachment lines. The existence of secondary flow is another feature of significant importance to CFD engineers. Although the concept of secondary flow is relatively understood there is no commonly accepted mathematical definition for secondary flow. This paper will present a definition for secondary flow and one approach for automatically detecting and visualizing secondary flow.

  15. Extracting features to recognize partially occluded objects

    NASA Astrophysics Data System (ADS)

    Koch, Mark W.; Ramamurthy, Arjun

    1991-12-01

    Noisy objects, partially occluded objects, and objects in random positions and orientations cause significant problems for current robotic vision systems. In the past, an association graph has formed the basis for many model based matching methods. However, the association graph has many false nodes due to local and noisy features. Objects having similar local structures create many false arcs in the association graph. The maximal clique recursive and tree search procedures for finding sets of structurally compatible matches have exponential time complexity, due to these false arcs and nodes. This represents a real problem as the number of objects appearing in the scene and the model set size increase. Our approach is similar to randomized string matching algorithms. Points on edges represent the model features. A fingerprint defines a subset of model features that uniquely identify the model. These fingerprints remove the ambiguities and inconsistencies present in the association graph and eliminate the problems of Turney's connected salient features. The vision system chooses the fingerprints at random, preventing a knowledgeable adversary from constructing examples that destroy the advantages of fingerprinting. Fingerprints consist of local model features called point vectors. We have developed a heuristic approach for extracting fingerprints from a set of model objects. A list of connected and unconnected scene edges represent the scene. A Hough transform type approach matches model fingerprints to scene features. Results are given for scenes containing varying amounts of occlusion.

  16. Vessels as 4-D curves: global minimal 4-D paths to extract 3-D tubular surfaces and centerlines.

    PubMed

    Li, Hua; Yezzi, Anthony

    2007-09-01

    In this paper, we propose an innovative approach to the segmentation of tubular structures. This approach combines all of the benefits of minimal path techniques such as global minimizers, fast computation, and powerful incorporation of user input, while also having the capability to represent and detect vessel surfaces directly which so far has been a feature restricted to active contour and surface techniques. The key is to represent the trajectory of a tubular structure not as a 3-D curve but to go up a dimension and represent the entire structure as a 4-D curve. Then we are able to fully exploit minimal path techniques to obtain global minimizing trajectories between two user supplied endpoints in order to reconstruct tubular structures from noisy or low contrast 3-D data without the sensitivity to local minima inherent in most active surface techniques. In contrast to standard purely spatial 3-D minimal path techniques, however, we are able to represent a full tubular surface rather than just a curve which runs through its interior. Our representation also yields a natural notion of a tube's "central curve." We demonstrate and validate the utility of this approach on magnetic resonance (MR) angiography and computed tomography (CT) images of coronary arteries. PMID:17896594

  17. Automatic Extraction of Building Roof Planes from Airborne LIDAR Data Applying AN Extended 3d Randomized Hough Transform

    NASA Astrophysics Data System (ADS)

    Maltezos, Evangelos; Ioannidis, Charalabos

    2016-06-01

    This study aims to extract automatically building roof planes from airborne LIDAR data applying an extended 3D Randomized Hough Transform (RHT). The proposed methodology consists of three main steps, namely detection of building points, plane detection and refinement. For the detection of the building points, the vegetative areas are first segmented from the scene content and the bare earth is extracted afterwards. The automatic plane detection of each building is performed applying extensions of the RHT associated with additional constraint criteria during the random selection of the 3 points aiming at the optimum adaptation to the building rooftops as well as using a simple design of the accumulator that efficiently detects the prominent planes. The refinement of the plane detection is conducted based on the relationship between neighbouring planes, the locality of the point and the use of additional information. An indicative experimental comparison to verify the advantages of the extended RHT compared to the 3D Standard Hough Transform (SHT) is implemented as well as the sensitivity of the proposed extensions and accumulator design is examined in the view of quality and computational time compared to the default RHT. Further, a comparison between the extended RHT and the RANSAC is carried out. The plane detection results illustrate the potential of the proposed extended RHT in terms of robustness and efficiency for several applications.

  18. Coding visual features extracted from video sequences.

    PubMed

    Baroffio, Luca; Cesana, Matteo; Redondi, Alessandro; Tagliasacchi, Marco; Tubaro, Stefano

    2014-05-01

    Visual features are successfully exploited in several applications (e.g., visual search, object recognition and tracking, etc.) due to their ability to efficiently represent image content. Several visual analysis tasks require features to be transmitted over a bandwidth-limited network, thus calling for coding techniques to reduce the required bit budget, while attaining a target level of efficiency. In this paper, we propose, for the first time, a coding architecture designed for local features (e.g., SIFT, SURF) extracted from video sequences. To achieve high coding efficiency, we exploit both spatial and temporal redundancy by means of intraframe and interframe coding modes. In addition, we propose a coding mode decision based on rate-distortion optimization. The proposed coding scheme can be conveniently adopted to implement the analyze-then-compress (ATC) paradigm in the context of visual sensor networks. That is, sets of visual features are extracted from video frames, encoded at remote nodes, and finally transmitted to a central controller that performs visual analysis. This is in contrast to the traditional compress-then-analyze (CTA) paradigm, in which video sequences acquired at a node are compressed and then sent to a central unit for further processing. In this paper, we compare these coding paradigms using metrics that are routinely adopted to evaluate the suitability of visual features in the context of content-based retrieval, object recognition, and tracking. Experimental results demonstrate that, thanks to the significant coding gains achieved by the proposed coding scheme, ATC outperforms CTA with respect to all evaluation metrics. PMID:24818244

  19. Extraction of geographic features using multioperator fusion

    NASA Astrophysics Data System (ADS)

    Dherete, Pierre; Desachy, Jacky

    1998-12-01

    Automatic analysis of remote sensing images faces different problems: context diversity, complexity of information. To simplify identification and to limit the search space, we use extra data and knowledge to help the scene understanding. Diversity and imprecision of information sources generate new problems. The fuzzy logic theory is used to solve the problem of imprecision. Many extraction algorithms are used to provide a more reliable result. Extraction may be performed either globally on the whole image or locally using information of data bases. Each extractor produces a map of certainty factors for a given type of geographic features according to their characteristics: radiometry, color, linear, etc. Maps contain wrong detections due to imperfections of the detectors or non- completeness of generic models. So, we generate a new map using fusion to have a best credibility used to compute a dynamic programming. It finds an optimal path even if the linear feature is partially occluded. But the path is generally erratic due to noise. Then a snake-like technique smooth the path to clean the erratic parts and to tune the level of detail required to represent the geographic features on a map of a given scale. The result is used to update data bases.

  20. Hyperspectral image feature extraction accelerated by GPU

    NASA Astrophysics Data System (ADS)

    Qu, HaiCheng; Zhang, Ye; Lin, Zhouhan; Chen, Hao

    2012-10-01

    PCA (principal components analysis) algorithm is the most basic method of dimension reduction for high-dimensional data1, which plays a significant role in hyperspectral data compression, decorrelation, denoising and feature extraction. With the development of imaging technology, the number of spectral bands in a hyperspectral image is getting larger and larger, and the data cube becomes bigger in these years. As a consequence, operation of dimension reduction is more and more time-consuming nowadays. Fortunately, GPU-based high-performance computing has opened up a novel approach for hyperspectral data processing6. This paper is concerning on the two main processes in hyperspectral image feature extraction: (1) calculation of transformation matrix; (2) transformation in spectrum dimension. These two processes belong to computationally intensive and data-intensive data processing respectively. Through the introduction of GPU parallel computing technology, an algorithm containing PCA transformation based on eigenvalue decomposition 8(EVD) and feature matching identification is implemented, which is aimed to explore the characteristics of the GPU parallel computing and the prospects of GPU application in hyperspectral image processing by analysing thread invoking and speedup of the algorithm. At last, the result of the experiment shows that the algorithm has reached a 12x speedup in total, in which some certain step reaches higher speedups up to 270 times.

  1. Angular description for 3D scattering centers

    NASA Astrophysics Data System (ADS)

    Bhalla, Rajan; Raynal, Ann Marie; Ling, Hao; Moore, John; Velten, Vincent J.

    2006-05-01

    The electromagnetic scattered field from an electrically large target can often be well modeled as if it is emanating from a discrete set of scattering centers (see Fig. 1). In the scattering center extraction tool we developed previously based on the shooting and bouncing ray technique, no correspondence is maintained amongst the 3D scattering center extracted at adjacent angles. In this paper we present a multi-dimensional clustering algorithm to track the angular and spatial behaviors of 3D scattering centers and group them into features. The extracted features for the Slicy and backhoe targets are presented. We also describe two metrics for measuring the angular persistence and spatial mobility of the 3D scattering centers that make up these features in order to gather insights into target physics and feature stability. We find that features that are most persistent are also the most mobile and discuss implications for optimal SAR imaging.

  2. Atlas and feature based 3D pathway visualization enhancement for skull base pre-operative fast planning from head CT

    NASA Astrophysics Data System (ADS)

    Aghdasi, Nava; Li, Yangming; Berens, Angelique; Moe, Kris S.; Bly, Randall A.; Hannaford, Blake

    2015-03-01

    Minimally invasive neuroendoscopic surgery provides an alternative to open craniotomy for many skull base lesions. These techniques provides a great benefit to the patient through shorter ICU stays, decreased post-operative pain and quicker return to baseline function. However, density of critical neurovascular structures at the skull base makes planning for these procedures highly complex. Furthermore, additional surgical portals are often used to improve visualization and instrument access, which adds to the complexity of pre-operative planning. Surgical approach planning is currently limited and typically involves review of 2D axial, coronal, and sagittal CT and MRI images. In addition, skull base surgeons manually change the visualization effect to review all possible approaches to the target lesion and achieve an optimal surgical plan. This cumbersome process relies heavily on surgeon experience and it does not allow for 3D visualization. In this paper, we describe a rapid pre-operative planning system for skull base surgery using the following two novel concepts: importance-based highlight and mobile portal. With this innovation, critical areas in the 3D CT model are highlighted based on segmentation results. Mobile portals allow surgeons to review multiple potential entry portals in real-time with improved visualization of critical structures located inside the pathway. To achieve this we used the following methods: (1) novel bone-only atlases were manually generated, (2) orbits and the center of the skull serve as features to quickly pre-align the patient's scan with the atlas, (3) deformable registration technique was used for fine alignment, (4) surgical importance was assigned to each voxel according to a surgical dictionary, and (5) pre-defined transfer function was applied to the processed data to highlight important structures. The proposed idea was fully implemented as independent planning software and additional

  3. Application of 3D Code IBSimu for Designing an H-/D- Extraction System for the Texas A&M Facility Upgrade

    NASA Astrophysics Data System (ADS)

    Kalvas, T.; Tarvainen, O.; Clark, H.; Brinkley, J.; ńrje, J.

    2011-09-01

    A three dimensional ion optical code IBSimu is being developed at the University of Jyväskylä. So far the plasma modelling of the code has been restricted to positive ion extraction systems, but now a negative ion plasma extraction model has been added. The plasma model has been successfully validated with simulations of the Spallation Neutron Source (SNS) ion source extraction both in cylindrical symmetry and in full 3D, also modelling electron beam dumping and ion beam tilt. A filament-driven multicusp ion source has been installed at the Texas A&M University Cyclotron Institute for production of H- and D- beams as a part of the facility upgrade. The light ion beams, produced by the ion source, are accelerated with the K150 cyclotron for production and reacceleration of rare isotopes. The extraction system for the ion source was designed with IBSimu. The extraction features a water-cooled puller electrode with a permanent magnet dipole field for dumping the co-extracted electrons and a decelerating Einzel lens for adjusting the beam focusing for further beam transport. The ion source and the puller electrode are tilted at 4 degree angle with respect to the beam line. The extraction system can handle H- and D- beams with final beam energies from 5 keV to 15 keV using the same geometry, only adjusting the electrode voltages. So far, 24 μA of H- and 15 μA of D- have been extracted from the cyclotron.

  4. ECG feature extraction and disease diagnosis.

    PubMed

    Bhyri, Channappa; Hamde, S T; Waghmare, L M

    2011-01-01

    An important factor to consider when using findings on electrocardiograms for clinical decision making is that the waveforms are influenced by normal physiological and technical factors as well as by pathophysiological factors. In this paper, we propose a method for the feature extraction and heart disease diagnosis using wavelet transform (WT) technique and LabVIEW (Laboratory Virtual Instrument Engineering workbench). LabVIEW signal processing tools are used to denoise the signal before applying the developed algorithm for feature extraction. First, we have developed an algorithm for R-peak detection using Haar wavelet. After 4th level decomposition of the ECG signal, the detailed coefficient is squared and the standard deviation of the squared detailed coefficient is used as the threshold for detection of R-peaks. Second, we have used daubechies (db6) wavelet for the low resolution signals. After cross checking the R-peak location in 4th level, low resolution signal of daubechies wavelet P waves and T waves are detected. Other features of diagnostic importance, mainly heart rate, R-wave width, Q-wave width, T-wave amplitude and duration, ST segment and frontal plane axis are also extracted and scoring pattern is applied for the purpose of heart disease diagnosis. In this study, detection of tachycardia, bradycardia, left ventricular hypertrophy, right ventricular hypertrophy and myocardial infarction have been considered. In this work, CSE ECG data base which contains 5000 samples recorded at a sampling frequency of 500 Hz and the ECG data base created by the S.G.G.S. Institute of Engineering and Technology, Nanded (Maharashtra) have been used. PMID:21770825

  5. Automated Fluid Feature Extraction from Transient Simulations

    NASA Technical Reports Server (NTRS)

    Haimes, Robert

    2000-01-01

    In the past, feature extraction and identification were interesting concepts, but not required in understanding the physics of a steady flow field. This is because the results of the more traditional tools like iso-surfaces, cuts and streamlines, were more interactive and easily abstracted so they could be represented to the investigator. These tools worked and properly conveyed the collected information at the expense of a great deal of interaction. For unsteady flow-fields, the investigator does not have the luxury of spending time scanning only one 'snap-shot' of the simulation. Automated assistance is required in pointing out areas of potential interest contained within the flow. This must not require a heavy compute burden (the visualization should not significantly slow down the solution procedure for co-processing environments like pV3). And methods must be developed to abstract the feature and display it in a manner that physically makes sense.

  6. Line drawing extraction from gray level images by feature integration

    NASA Astrophysics Data System (ADS)

    Yoo, Hoi J.; Crevier, Daniel; Lepage, Richard; Myler, Harley R.

    1994-10-01

    We describe procedures that extract line drawings from digitized gray level images, without use of domain knowledge, by modeling preattentive and perceptual organization functions of the human visual system. First, edge points are identified by standard low-level processing, based on the Canny edge operator. Edge points are then linked into single-pixel thick straight- line segments and circular arcs: this operation serves to both filter out isolated and highly irregular segments, and to lump the remaining points into a smaller number of structures for manipulation by later stages of processing. The next stages consist in linking the segments into a set of closed boundaries, which is the system's definition of a line drawing. According to the principles of Gestalt psychology, closure allows us to organize the world by filling in the gaps in a visual stimulation so as to perceive whole objects instead of disjoint parts. To achieve such closure, the system selects particular features or combinations of features by methods akin to those of preattentive processing in humans: features include gaps, pairs of straight or curved parallel lines, L- and T-junctions, pairs of symmetrical lines, and the orientation and length of single lines. These preattentive features are grouped into higher-level structures according to the principles of proximity, similarity, closure, symmetry, and feature conjunction. Achieving closure may require supplying missing segments linking contour concavities. Choices are made between competing structures on the basis of their overall compliance with the principles of closure and symmetry. Results include clean line drawings of curvilinear manufactured objects. The procedures described are part of a system called VITREO (viewpoint-independent 3-D recognition and extraction of objects).

  7. Individual 3D region-of-interest atlas of the human brain: automatic training point extraction for neural-network-based classification of brain tissue types

    NASA Astrophysics Data System (ADS)

    Wagenknecht, Gudrun; Kaiser, Hans-Juergen; Obladen, Thorsten; Sabri, Osama; Buell, Udalrich

    2000-04-01

    Individual region-of-interest atlas extraction consists of two main parts: T1-weighted MRI grayscale images are classified into brain tissues types (gray matter (GM), white matter (WM), cerebrospinal fluid (CSF), scalp/bone (SB), background (BG)), followed by class image analysis to define automatically meaningful ROIs (e.g., cerebellum, cerebral lobes, etc.). The purpose of this algorithm is the automatic detection of training points for neural network-based classification of brain tissue types. One transaxial slice of the patient data set is analyzed. Background separation is done by simple region growing. A random generator extracts spatially uniformly distributed training points of class BG from that region. For WM training point extraction (TPE), the homogeneity operator is the most important. The most homogeneous voxels define the region for WM TPE. They are extracted by analyzing the cumulative histogram of the homogeneity operator response. Assuming a Gaussian gray value distribution in WM, a random number is used as a probabilistic threshold for TPE. Similarly, non-white matter and non-background regions are analyzed for GM and CSF training points. For SB TPE, the distance from the BG region is an additional feature. Simulated and real 3D MRI images are analyzed and error rates for TPE and classification calculated.

  8. Feature Extraction and Selection From the Perspective of Explosive Detection

    SciTech Connect

    Sengupta, S K

    2009-09-01

    Features are extractable measurements from a sample image summarizing the information content in an image and in the process providing an essential tool in image understanding. In particular, they are useful for image classification into pre-defined classes or grouping a set of image samples (also called clustering) into clusters with similar within-cluster characteristics as defined by such features. At the lowest level, features may be the intensity levels of a pixel in an image. The intensity levels of the pixels in an image may be derived from a variety of sources. For example, it can be the temperature measurement (using an infra-red camera) of the area representing the pixel or the X-ray attenuation in a given volume element of a 3-d image or it may even represent the dielectric differential in a given volume element obtained from an MIR image. At a higher level, geometric descriptors of objects of interest in a scene may also be considered as features in the image. Examples of such features are: area, perimeter, aspect ratio and other shape features, or topological features like the number of connected components, the Euler number (the number of connected components less the number of 'holes'), etc. Occupying an intermediate level in the feature hierarchy are texture features which are typically derived from a group of pixels often in a suitably defined neighborhood of a pixel. These texture features are useful not only in classification but also in the segmentation of an image into different objects/regions of interest. At the present state of our investigation, we are engaged in the task of finding a set of features associated with an object under inspection ( typically a piece of luggage or a brief case) that will enable us to detect and characterize an explosive inside, when present. Our tool of inspection is an X-Ray device with provisions for computed tomography (CT) that generate one or more (depending on the number of energy levels used) digitized 3

  9. Real-time processor for 3-D information extraction from image sequences by a moving area sensor

    NASA Astrophysics Data System (ADS)

    Hattori, Tetsuo; Nakada, Makoto; Kubo, Katsumi

    1990-11-01

    This paper presents a real time image processor for obtaining threedimensional( 3-D) distance information from image sequence caused by a moving area sensor. The processor has been developed for an automated visual inspection robot system (pilot system) with an autonomous vehicle which moves around avoiding obstacles in a power plant and checks whether there are defects or abnormal phenomena such as steam leakage from valves. The processor detects the distance between objects in the input image and the area sensor deciding corresponding points(pixels) between the first input image and the last one by tracing the loci of edges through the sequence of sixteen images. The hardware which plays an important role is two kinds of boards: mapping boards which can transform X-coordinate (horizontal direction) and Y-coordinate (vertical direction) for each horizontal row of images and a regional labelling board which extracts the connected loci of edges through image sequence. This paper also shows the whole processing flow of the distance detection algorithm. Since the processor can continuously process images ( 512x512x8 [pixels*bits per frame] ) at the NTSC video rate it takes about O. 7[sec] to measure the 3D distance by sixteen input images. The error rate of the measurement is maximum 10 percent when the area sensor laterally moves the range of 20 [centimeters] and when the measured scene including complicated background is at a distance of 4 [meters] from

  10. A parallelized surface extraction algorithm for large binary image data sets based on an adaptive 3D delaunay subdivision strategy.

    PubMed

    Ma, Yingliang; Saetzler, Kurt

    2008-01-01

    In this paper we describe a novel 3D subdivision strategy to extract the surface of binary image data. This iterative approach generates a series of surface meshes that capture different levels of detail of the underlying structure. At the highest level of detail, the resulting surface mesh generated by our approach uses only about 10% of the triangles in comparison to the marching cube algorithm (MC) even in settings were almost no image noise is present. Our approach also eliminates the so-called "staircase effect" which voxel based algorithms like the MC are likely to show, particularly if non-uniformly sampled images are processed. Finally, we show how the presented algorithm can be parallelized by subdividing 3D image space into rectilinear blocks of subimages. As the algorithm scales very well with an increasing number of processors in a multi-threaded setting, this approach is suited to process large image data sets of several gigabytes. Although the presented work is still computationally more expensive than simple voxel-based algorithms, it produces fewer surface triangles while capturing the same level of detail, is more robust towards image noise and eliminates the above-mentioned "staircase" effect in anisotropic settings. These properties make it particularly useful for biomedical applications, where these conditions are often encountered. PMID:17993710

  11. Concrete Slump Classification using GLCM Feature Extraction

    NASA Astrophysics Data System (ADS)

    Andayani, Relly; Madenda, Syarifudin

    2016-05-01

    Digital image processing technologies have been widely applies in analyzing concrete structure because the accuracy and real time result. The aim of this study is to classify concrete slump by using image processing technique. For this purpose, concrete mix design of 30 MPa compression strength designed with slump of 0-10 mm, 10-30 mm, 30-60 mm, and 60-180 mm were analysed. Image acquired by Nikon Camera D-7000 using high resolution was set up. In the first step RGB converted to greyimage than cropped to 1024 x 1024 pixel. With open-source program, cropped images to be analysed to extract GLCM feature. The result shows for the higher slump contrast getting lower, but higher correlation, energy, and homogeneity.

  12. Synthesis and characterization of magnetic solids featuring 3d-4f heterometallic oxides comprised of spin chains and 3d-6p noncentrosymmetric oxides templated by acentric salt units

    NASA Astrophysics Data System (ADS)

    West, Jennings Palmer

    solvent media is the fact that the salt itself or the alkali/alkaline-earth oxides formed in situ can be incorporated in phase formations. Both of the aforementioned cases, if incorporated, lead to an additional and different type of nonmagnetic spacer for the formation of low-dimensional 3d-4 f extended solids. It is believed that these nonmagnetic, ionic spacers are more disruptive to magnetic super-super-exchange in comparison to the nonmagnetic oxyanionic spacers, and should assist further in achieving truly confined magnetic sublattices. In the studies presented, the overall highlight considering structure and property correlations will be most exemplified through the comparison of two different pseudo-one-dimensional (1D), 3d-4 f arsenate systems (Chapters 3 and 4) where it is observed that further spacing of the 3d-4f sublattices leads to interesting low-dimensional magnetic behavior. In addition, an extension of one of these pseudo-1D, 3d-4f systems (Chapter 5) will highlight the intriguing properties resulting from the study of a family of compounds whereby a double aliovalent substitution has been performed with respect to the parent family. This particular system features a solid solution series where charge disorder exists, and in terms of magnetic properties, there are unique variations in comparison to the parent family. And finally, in relation to heterometallic system types, a new noncentrosymmetric phosphate family containing mixed 3d-6p (where 3 d = Mn, Fe; 6p = Bi3+) will be discussed (Chapter 6). As will be mentioned, new 3d-6p systems were explored originally for host materials where lanthanides could be substituted. Independent of lanthanide substitutions that are yet to be proven, the combination of both bulk acentricity and magnetically active ions makes systems of this type worthy of study due to multiferroic potentials aimed toward the coupling of polarization and magnetization.

  13. Automated Fluid Feature Extraction from Transient Simulations

    NASA Technical Reports Server (NTRS)

    Haimes, Robert

    1998-01-01

    In the past, feature extraction and identification were interesting concepts, but not required to understand the underlying physics of a steady flow field. This is because the results of the more traditional tools like iso-surfaces, cuts and streamlines were more interactive and easily abstracted so they could be represented to the investigator. These tools worked and properly conveyed the collected information at the expense of much interaction. For unsteady flow-fields, the investigator does not have the luxury of spending time scanning only one 'snap-shot' of the simulation. Automated assistance is required in pointing out areas of potential interest contained within the flow. This must not require a heavy compute burden (the visualization should not significantly slow down the solution procedure for co-processing environments like pV3). And methods must be developed to abstract the feature and display it in a manner that physically makes sense. The following is a list of the important physical phenomena found in transient (and steady-state) fluid flow: Shocks; Vortex ores; Regions of Recirculation; Boundary Layers; Wakes.

  14. Analysis of MABEL data for feature extraction

    NASA Astrophysics Data System (ADS)

    Magruder, L.; Neuenschwander, A. L.; Wharton, M.

    2011-12-01

    MABEL (Multiple Altimeter Beam Experimental Lidar) is a test bed representation for ICESat-2 with a high repetition rate, low laser pulse energy and photon-counting detection on an airborne platform. MABEL data can be scaled to simulate ICESat-2 data products and is a demonstration proving critical for model validation and algorithm development. The recent MABEL flights over White Sands Missile in New Mexico (WSMR) have provided especially useful insight for the potential processing schemes of this type of data as well as how to extract specific geophysical or passive optical features. Although the MABEL data has not been precisely geolocated to date, approximate geolocations were derived using interpolated GPS data and aircraft attitude. In addition to providing indication of expected signal response over specific types of terrain/targets, the availability of MABEL data has also facilitated preliminary development into new types of noise filtering for photon-counting data products that will contribute to capabilities associated with future capabilities for ICESat-2 data extraction. One particular useful methodology uses a combination of cluster weighting and neighbor-count weighting. For weighting clustered points, each individual point is tagged with an average distance to its neighbors within an established threshold. Histograms of the mean values are created for both a pure noise section and a signal-noise mixture section, and a deconvolution of these histograms gives a normal distribution for the signal. A fitted Gaussian is used to calculate a threshold for the average distances. This removes locally sparse points, so then a regular neighborhood-count filter is used for a larger search radius. It seems to work better with high-noise cases and allows for improved signal recovery without being computationally expensive. One specific MABEL nadir channel ground track provided returns from several distinct ground markers that included multiple mounds, an elevated

  15. 3D non-rigid registration using surface and local salient features for transrectal ultrasound image-guided prostate biopsy

    NASA Astrophysics Data System (ADS)

    Yang, Xiaofeng; Akbari, Hamed; Halig, Luma; Fei, Baowei

    2011-03-01

    We present a 3D non-rigid registration algorithm for the potential use in combining PET/CT and transrectal ultrasound (TRUS) images for targeted prostate biopsy. Our registration is a hybrid approach that simultaneously optimizes the similarities from point-based registration and volume matching methods. The 3D registration is obtained by minimizing the distances of corresponding points at the surface and within the prostate and by maximizing the overlap ratio of the bladder neck on both images. The hybrid approach not only capture deformation at the prostate surface and internal landmarks but also the deformation at the bladder neck regions. The registration uses a soft assignment and deterministic annealing process. The correspondences are iteratively established in a fuzzy-to-deterministic approach. B-splines are used to generate a smooth non-rigid spatial transformation. In this study, we tested our registration with pre- and postbiopsy TRUS images of the same patients. Registration accuracy is evaluated using manual defined anatomic landmarks, i.e. calcification. The root-mean-squared (RMS) of the difference image between the reference and floating images was decreased by 62.6+/-9.1% after registration. The mean target registration error (TRE) was 0.88+/-0.16 mm, i.e. less than 3 voxels with a voxel size of 0.38×0.38×0.38 mm3 for all five patients. The experimental results demonstrate the robustness and accuracy of the 3D non-rigid registration algorithm.

  16. Combining contour detection algorithms for the automatic extraction of the preparation line from a dental 3D measurement

    NASA Astrophysics Data System (ADS)

    Ahlers, Volker; Weigl, Paul; Schachtzabel, Hartmut

    2005-04-01

    Due to the increasing demand for high-quality ceramic crowns and bridges, the CAD/CAM-based production of dental restorations has been a subject of intensive research during the last fifteen years. A prerequisite for the efficient processing of the 3D measurement of prepared teeth with a minimal amount of user interaction is the automatic determination of the preparation line, which defines the sealing margin between the restoration and the prepared tooth. Current dental CAD/CAM systems mostly require the interactive definition of the preparation line by the user, at least by means of giving a number of start points. Previous approaches to the automatic extraction of the preparation line rely on single contour detection algorithms. In contrast, we use a combination of different contour detection algorithms to find several independent potential preparation lines from a height profile of the measured data. The different algorithms (gradient-based, contour-based, and region-based) show their strengths and weaknesses in different clinical situations. A classifier consisting of three stages (range check, decision tree, support vector machine), which is trained by human experts with real-world data, finally decides which is the correct preparation line. In a test with 101 clinical preparations, a success rate of 92.0% has been achieved. Thus the combination of different contour detection algorithms yields a reliable method for the automatic extraction of the preparation line, which enables the setup of a turn-key dental CAD/CAM process chain with a minimal amount of interactive screen work.

  17. General fusion approaches for the age determination of latent fingerprint traces: results for 2D and 3D binary pixel feature fusion

    NASA Astrophysics Data System (ADS)

    Merkel, Ronny; Gruhn, Stefan; Dittmann, Jana; Vielhauer, Claus; Bräutigam, Anja

    2012-03-01

    Determining the age of latent fingerprint traces found at crime scenes is an unresolved research issue since decades. Solving this issue could provide criminal investigators with the specific time a fingerprint trace was left on a surface, and therefore would enable them to link potential suspects to the time a crime took place as well as to reconstruct the sequence of events or eliminate irrelevant fingerprints to ensure privacy constraints. Transferring imaging techniques from different application areas, such as 3D image acquisition, surface measurement and chemical analysis to the domain of lifting latent biometric fingerprint traces is an upcoming trend in forensics. Such non-destructive sensor devices might help to solve the challenge of determining the age of a latent fingerprint trace, since it provides the opportunity to create time series and process them using pattern recognition techniques and statistical methods on digitized 2D, 3D and chemical data, rather than classical, contact-based capturing techniques, which alter the fingerprint trace and therefore make continuous scans impossible. In prior work, we have suggested to use a feature called binary pixel, which is a novel approach in the working field of fingerprint age determination. The feature uses a Chromatic White Light (CWL) image sensor to continuously scan a fingerprint trace over time and retrieves a characteristic logarithmic aging tendency for 2D-intensity as well as 3D-topographic images from the sensor. In this paper, we propose to combine such two characteristic aging features with other 2D and 3D features from the domains of surface measurement, microscopy, photography and spectroscopy, to achieve an increase in accuracy and reliability of a potential future age determination scheme. Discussing the feasibility of such variety of sensor devices and possible aging features, we propose a general fusion approach, which might combine promising features to a joint age determination scheme

  18. A synergistic approach to the design, fabrication and evaluation of 3D printed micro and nano featured scaffolds for vascularized bone tissue repair

    NASA Astrophysics Data System (ADS)

    Holmes, Benjamin; Bulusu, Kartik; Plesniak, Michael; Zhang, Lijie Grace

    2016-02-01

    3D bioprinting has begun to show great promise in advancing the development of functional tissue/organ replacements. However, to realize the true potential of 3D bioprinted tissues for clinical use requires the fabrication of an interconnected and effective vascular network. Solving this challenge is critical, as human tissue relies on an adequate network of blood vessels to transport oxygen, nutrients, other chemicals, biological factors and waste, in and out of the tissue. Here, we have successfully designed and printed a series of novel 3D bone scaffolds with both bone formation supporting structures and highly interconnected 3D microvascular mimicking channels, for efficient and enhanced osteogenic bone regeneration as well as vascular cell growth. Using a chemical functionalization process, we have conjugated our samples with nano hydroxyapatite (nHA), for the creation of novel micro and nano featured devices for vascularized bone growth. We evaluated our scaffolds with mechanical testing, hydrodynamic measurements and in vitro human mesenchymal stem cell (hMSC) adhesion (4 h), proliferation (1, 3 and 5 d) and osteogenic differentiation (1, 2 and 3 weeks). These tests confirmed bone-like physical properties and vascular-like flow profiles, as well as demonstrated enhanced hMSC adhesion, proliferation and osteogenic differentiation. Additional in vitro experiments with human umbilical vein endothelial cells also demonstrated improved vascular cell growth, migration and organization on micro-nano featured scaffolds.

  19. A synergistic approach to the design, fabrication and evaluation of 3D printed micro and nano featured scaffolds for vascularized bone tissue repair.

    PubMed

    Holmes, Benjamin; Bulusu, Kartik; Plesniak, Michael; Zhang, Lijie Grace

    2016-02-12

    3D bioprinting has begun to show great promise in advancing the development of functional tissue/organ replacements. However, to realize the true potential of 3D bioprinted tissues for clinical use requires the fabrication of an interconnected and effective vascular network. Solving this challenge is critical, as human tissue relies on an adequate network of blood vessels to transport oxygen, nutrients, other chemicals, biological factors and waste, in and out of the tissue. Here, we have successfully designed and printed a series of novel 3D bone scaffolds with both bone formation supporting structures and highly interconnected 3D microvascular mimicking channels, for efficient and enhanced osteogenic bone regeneration as well as vascular cell growth. Using a chemical functionalization process, we have conjugated our samples with nano hydroxyapatite (nHA), for the creation of novel micro and nano featured devices for vascularized bone growth. We evaluated our scaffolds with mechanical testing, hydrodynamic measurements and in vitro human mesenchymal stem cell (hMSC) adhesion (4 h), proliferation (1, 3 and 5 d) and osteogenic differentiation (1, 2 and 3 weeks). These tests confirmed bone-like physical properties and vascular-like flow profiles, as well as demonstrated enhanced hMSC adhesion, proliferation and osteogenic differentiation. Additional in vitro experiments with human umbilical vein endothelial cells also demonstrated improved vascular cell growth, migration and organization on micro-nano featured scaffolds. PMID:26758780

  20. 3D Face Modeling Using the Multi-Deformable Method

    PubMed Central

    Hwang, Jinkyu; Yu, Sunjin; Kim, Joongrock; Lee, Sangyoun

    2012-01-01

    In this paper, we focus on the problem of the accuracy performance of 3D face modeling techniques using corresponding features in multiple views, which is quite sensitive to feature extraction errors. To solve the problem, we adopt a statistical model-based 3D face modeling approach in a mirror system consisting of two mirrors and a camera. The overall procedure of our 3D facial modeling method has two primary steps: 3D facial shape estimation using a multiple 3D face deformable model and texture mapping using seamless cloning that is a type of gradient-domain blending. To evaluate our method's performance, we generate 3D faces of 30 individuals and then carry out two tests: accuracy test and robustness test. Our method shows not only highly accurate 3D face shape results when compared with the ground truth, but also robustness to feature extraction errors. Moreover, 3D face rendering results intuitively show that our method is more robust to feature extraction errors than other 3D face modeling methods. An additional contribution of our method is that a wide range of face textures can be acquired by the mirror system. By using this texture map, we generate realistic 3D face for individuals at the end of the paper. PMID:23201976

  1. 3-D Numerical Modeling as a Tool for Managing Mineral Water Extraction from a Complex Groundwater Basin in Italy

    NASA Astrophysics Data System (ADS)

    Zanini, A.; Tanda, M.

    2007-12-01

    The groundwater in Italy plays an important role as drinking water; in fact it covers about the 30% of the national demand (70% in Northern Italy). The mineral water distribution in Italy is an important business with an increasing demand from abroad countries. The mineral water Companies have a great interest in order to increase the water extraction, but for the delicate and complex geology of the subsoil, where such very high quality waters are contained, a particular attention must be paid in order to avoid an excessive lowering of the groundwater reservoirs or great changes in the groundwater flow directions. A big water Company asked our University to set up a numerical model of the groundwater basin, in order to obtain a useful tool which allows to evaluate the strength of the aquifer and to design new extraction wells. The study area is located along Appennini Mountains and it covers a surface of about 18 km2; the topography ranges from 200 to 600 m a.s.l.. In ancient times only a spring with naturally sparkling water was known in the area, but at present the mineral water is extracted from deep pumping wells. The area is characterized by a very complex geology: the subsoil structure is described by a sequence of layers of silt-clay, marl-clay, travertine and alluvial deposit. Different groundwater layers are present and the one with best quality flows in the travertine layer; the natural flow rate seems to be not subjected to seasonal variations. The water age analysis revealed a very old water which means that the mineral aquifers are not directly connected with the meteoric recharge. The Geologists of the Company suggest that the water supply of the mineral aquifers comes from a carbonated unit located in the deep layers of the mountains bordering the spring area. The valley is crossed by a river that does not present connections to the mineral aquifers. Inside the area there are about 30 pumping wells that extract water at different depths. We built a 3

  2. Automatic organ localizations on 3D CT images by using majority-voting of multiple 2D detections based on local binary patterns and Haar-like features

    NASA Astrophysics Data System (ADS)

    Zhou, Xiangrong; Yamaguchi, Shoutarou; Zhou, Xinxin; Chen, Huayue; Hara, Takeshi; Yokoyama, Ryujiro; Kanematsu, Masayuki; Fujita, Hiroshi

    2013-02-01

    This paper describes an approach to accomplish the fast and automatic localization of the different inner organ regions on 3D CT scans. The proposed approach combines object detections and the majority voting technique to achieve the robust and quick organ localization. The basic idea of proposed method is to detect a number of 2D partial appearances of a 3D target region on CT images from multiple body directions, on multiple image scales, by using multiple feature spaces, and vote all the 2D detecting results back to the 3D image space to statistically decide one 3D bounding rectangle of the target organ. Ensemble learning was used to train the multiple 2D detectors based on template matching on local binary patterns and Haar-like feature spaces. A collaborative voting was used to decide the corner coordinates of the 3D bounding rectangle of the target organ region based on the coordinate histograms from detection results in three body directions. Since the architecture of the proposed method (multiple independent detections connected to a majority voting) naturally fits the parallel computing paradigm and multi-core CPU hardware, the proposed algorithm was easy to achieve a high computational efficiently for the organ localizations on a whole body CT scan by using general-purpose computers. We applied this approach to localization of 12 kinds of major organ regions independently on 1,300 torso CT scans. In our experiments, we randomly selected 300 CT scans (with human indicated organ and tissue locations) for training, and then, applied the proposed approach with the training results to localize each of the target regions on the other 1,000 CT scans for the performance testing. The experimental results showed the possibility of the proposed approach to automatically locate different kinds of organs on the whole body CT scans.

  3. Highway 3D model from image and lidar data

    NASA Astrophysics Data System (ADS)

    Chen, Jinfeng; Chu, Henry; Sun, Xiaoduan

    2014-05-01

    We present a new method of highway 3-D model construction developed based on feature extraction in highway images and LIDAR data. We describe the processing road coordinate data that connect the image frames to the coordinates of the elevation data. Image processing methods are used to extract sky, road, and ground regions as well as significant objects (such as signs and building fronts) in the roadside for the 3D model. LIDAR data are interpolated and processed to extract the road lanes as well as other features such as trees, ditches, and elevated objects to form the 3D model. 3D geometry reasoning is used to match the image features to the 3D model. Results from successive frames are integrated to improve the final model.

  4. [An automatic extraction algorithm for individual tree crown projection area and volume based on 3D point cloud data].

    PubMed

    Xu, Wei-Heng; Feng, Zhong-Ke; Su, Zhi-Fang; Xu, Hui; Jiao, You-Quan; Deng, Ou

    2014-02-01

    fixed angles to estimate crown projections, and (2) different regular volume formula to simulate crown volume according to the tree crown shapes. Based on the high-resolution 3D LIDAR point cloud data of individual tree, tree crown structure was reconstructed at a high rate of speed with high accuracy, and crown projection and volume of individual tree were extracted by this automatical untouched method, which can provide a reference for tree crown structure studies and be worth to popularize in the field of precision forestry. PMID:24822422

  5. Integrated feature extraction and selection for neuroimage classification

    NASA Astrophysics Data System (ADS)

    Fan, Yong; Shen, Dinggang

    2009-02-01

    Feature extraction and selection are of great importance in neuroimage classification for identifying informative features and reducing feature dimensionality, which are generally implemented as two separate steps. This paper presents an integrated feature extraction and selection algorithm with two iterative steps: constrained subspace learning based feature extraction and support vector machine (SVM) based feature selection. The subspace learning based feature extraction focuses on the brain regions with higher possibility of being affected by the disease under study, while the possibility of brain regions being affected by disease is estimated by the SVM based feature selection, in conjunction with SVM classification. This algorithm can not only take into account the inter-correlation among different brain regions, but also overcome the limitation of traditional subspace learning based feature extraction methods. To achieve robust performance and optimal selection of parameters involved in feature extraction, selection, and classification, a bootstrapping strategy is used to generate multiple versions of training and testing sets for parameter optimization, according to the classification performance measured by the area under the ROC (receiver operating characteristic) curve. The integrated feature extraction and selection method is applied to a structural MR image based Alzheimer's disease (AD) study with 98 non-demented and 100 demented subjects. Cross-validation results indicate that the proposed algorithm can improve performance of the traditional subspace learning based classification.

  6. Using Mobile Laser Scanning Data for Features Extraction of High Accuracy Driving Maps

    NASA Astrophysics Data System (ADS)

    Yang, Bisheng; Liu, Yuan; Liang, Fuxun; Dong, Zhen

    2016-06-01

    High Accuracy Driving Maps (HADMs) are the core component of Intelligent Drive Assistant Systems (IDAS), which can effectively reduce the traffic accidents due to human error and provide more comfortable driving experiences. Vehicle-based mobile laser scanning (MLS) systems provide an efficient solution to rapidly capture three-dimensional (3D) point clouds of road environments with high flexibility and precision. This paper proposes a novel method to extract road features (e.g., road surfaces, road boundaries, road markings, buildings, guardrails, street lamps, traffic signs, roadside-trees, power lines, vehicles and so on) for HADMs in highway environment. Quantitative evaluations show that the proposed algorithm attains an average precision and recall in terms of 90.6% and 91.2% in extracting road features. Results demonstrate the efficiencies and feasibilities of the proposed method for extraction of road features for HADMs.

  7. An Efficient Method for Automatic Road Extraction Based on Multiple Features from LiDAR Data

    NASA Astrophysics Data System (ADS)

    Li, Y.; Hu, X.; Guan, H.; Liu, P.

    2016-06-01

    The road extraction in urban areas is difficult task due to the complicated patterns and many contextual objects. LiDAR data directly provides three dimensional (3D) points with less occlusions and smaller shadows. The elevation information and surface roughness are distinguishing features to separate roads. However, LiDAR data has some disadvantages are not beneficial to object extraction, such as the irregular distribution of point clouds and lack of clear edges of roads. For these problems, this paper proposes an automatic road centerlines extraction method which has three major steps: (1) road center point detection based on multiple feature spatial clustering for separating road points from ground points, (2) local principal component analysis with least squares fitting for extracting the primitives of road centerlines, and (3) hierarchical grouping for connecting primitives into complete roads network. Compared with MTH (consist of Mean shift algorithm, Tensor voting, and Hough transform) proposed in our previous article, this method greatly reduced the computational cost. To evaluate the proposed method, the Vaihingen data set, a benchmark testing data provided by ISPRS for "Urban Classification and 3D Building Reconstruction" project, was selected. The experimental results show that our method achieve the same performance by less time in road extraction using LiDAR data.

  8. Munitions related feature extraction from LIDAR data.

    SciTech Connect

    Roberts, Barry L.

    2010-06-01

    The characterization of former military munitions ranges is critical in the identification of areas likely to contain residual unexploded ordnance (UXO). Although these ranges are large, often covering tens-of-thousands of acres, the actual target areas represent only a small fraction of the sites. The challenge is that many of these sites do not have records indicating locations of former target areas. The identification of target areas is critical in the characterization and remediation of these sites. The Strategic Environmental Research and Development Program (SERDP) and Environmental Security Technology Certification Program (ESTCP) of the DoD have been developing and implementing techniques for the efficient characterization of large munitions ranges. As part of this process, high-resolution LIDAR terrain data sets have been collected over several former ranges. These data sets have been shown to contain information relating to former munitions usage at these ranges, specifically terrain cratering due to high-explosives detonations. The location and relative intensity of crater features can provide information critical in reconstructing the usage history of a range, and indicate areas most likely to contain UXO. We have developed an automated procedure using an adaptation of the Circular Hough Transform for the identification of crater features in LIDAR terrain data. The Circular Hough Transform is highly adept at finding circular features (craters) in noisy terrain data sets. This technique has the ability to find features of a specific radius providing a means of filtering features based on expected scale and providing additional spatial characterization of the identified feature. This method of automated crater identification has been applied to several former munitions ranges with positive results.

  9. Noise, Edge Extraction and Visibility of Features

    NASA Technical Reports Server (NTRS)

    Rahman, Zia-ur; Jobson, Daniel J.

    2005-01-01

    Noise, whether due to the image-gathering device or some other reason, reduces the visibility of fine features in an image. Several techniques attempt to mitigate the impact of noise by performing a low-pass filtering operation on the acquired data. This is based on the assumption that the uncorrelated noise has high-frequency content and thus will be suppressed by low-pass filtering. A result of this operation is that edges in a noisy image also tend to get blurred, and, in some cases, may get completely lost due to the low-pass filtering. In this paper, we quantitatively assess the impact of noise on fine feature visibility by using computer-generated targets of known spatial detail. Additionally, we develop a new scheme for noise-reduction based on the connectivity of edge-features. The overall impact of this scheme is to reduce overall noise, yet retain the high frequency content that make edge-features sharp.

  10. Extracting textural features from tactile sensors.

    PubMed

    Edwards, J; Lawry, J; Rossiter, J; Melhuish, C

    2008-09-01

    This paper describes an experiment to quantify texture using an artificial finger equipped with a microphone to detect frictional sound. Using a microphone to record tribological data is a biologically inspired approach that emulates the Pacinian corpuscle. Artificial surfaces were created to constrain the subsequent analysis to specific textures. Recordings of the artificial surfaces were made to create a library of frictional sounds for data analysis. These recordings were mapped to the frequency domain using fast Fourier transforms for direct comparison, manipulation and quantifiable analysis. Numerical features such as modal frequency and average value were calculated to analyze the data and compared with attributes generated from principal component analysis (PCA). It was found that numerical features work well for highly constrained data but cannot classify multiple textural elements. PCA groups textures according to a natural similarity. Classification of the recordings using k nearest neighbors shows a high accuracy for PCA data. Clustering of the PCA data shows that similar discs are grouped together with few classification errors. In contrast, clustering of numerical features produces erroneous classification by splitting discs between clusters. The temperature of the finger is shown to have a direct relation to some of the features and subsequent data in PCA. PMID:18583731

  11. Feature extraction from Doppler ultrasound signals for automated diagnostic systems.

    PubMed

    Ubeyli, Elif Derya; Güler, Inan

    2005-11-01

    This paper presented the assessment of feature extraction methods used in automated diagnosis of arterial diseases. Since classification is more accurate when the pattern is simplified through representation by important features, feature extraction and selection play an important role in classifying systems such as neural networks. Different feature extraction methods were used to obtain feature vectors from ophthalmic and internal carotid arterial Doppler signals. In addition to this, the problem of selecting relevant features among the features available for the purpose of classification of Doppler signals was dealt with. Multilayer perceptron neural networks (MLPNNs) with different inputs (feature vectors) were used for diagnosis of ophthalmic and internal carotid arterial diseases. The assessment of feature extraction methods was performed by taking into consideration of performances of the MLPNNs. The performances of the MLPNNs were evaluated by the convergence rates (number of training epochs) and the total classification accuracies. Finally, some conclusions were drawn concerning the efficiency of discrete wavelet transform as a feature extraction method used for the diagnosis of ophthalmic and internal carotid arterial diseases. PMID:16278106

  12. Bootstrapping 3D fermions

    NASA Astrophysics Data System (ADS)

    Iliesiu, Luca; Kos, Filip; Poland, David; Pufu, Silviu S.; Simmons-Duffin, David; Yacoby, Ran

    2016-03-01

    We study the conformal bootstrap for a 4-point function of fermions < ψψψψ> in 3D. We first introduce an embedding formalism for 3D spinors and compute the conformal blocks appearing in fermion 4-point functions. Using these results, we find general bounds on the dimensions of operators appearing in the ψ × ψ OPE, and also on the central charge C T . We observe features in our bounds that coincide with scaling dimensions in the GrossNeveu models at large N . We also speculate that other features could coincide with a fermionic CFT containing no relevant scalar operators.

  13. EFFICIENT FEATURE-BASED CONTOUR EXTRACTION.

    SciTech Connect

    Gattiker, J. R.

    2001-01-01

    Extraction of contours in binary images is an important element of object recognition. This paper discusses a more efficient approach to contour representation and generation. This approach defines a bounding polygon as defined by its vertices rather than by all enclosing pixels, which in itself is an effective representation. These corners can be identified by convolution of the image with a 3 x 3 filter. When these corners are organized by their connecting orientation, identified by the convolution, and type, inside or outside, connectivity characteristics can be articulated to highly constrain the task of sorting the vertices into ordered boundary lists. The search for the next bounding polygon vertex is reduced to a one dimensional minimum distance search rather than the standard, more intensive two dimensional nearest Euclidean neighbor search.

  14. Renyi information for extracting features from TFDs

    NASA Astrophysics Data System (ADS)

    Williams, William J.

    2001-11-01

    Introduction of Renyi information to time-frequency analysis occurred in 1991, by Williams et al at SPIE. The Renyi measure provides a single objective indication of the complexity of a signal as reflected in its time-frequency representation. The Gabor logon is the minimum complexity signal and its informational value is zero bits. All other signals exhibit increased Renyi information. Certain time-frequency distributions are information invariant, meaning that their Renyi information does not change under time-shift, frequency shift and scale changes. The Reduced Interference Distributions are information invariant. Thus a given signal within that class will always have the same Renyi result. This can be used to survey large data sequences in order to isolate certain types of signals. One application is to extract instances of such a signal from a streaming RID representation. Examples for temporomandibular joint clicks are provided.

  15. Direct extraction of topographic features from gray scale haracter images

    SciTech Connect

    Seong-Whan Lee; Young Joon Kim

    1994-12-31

    Optical character recognition (OCR) traditionally applies to binary-valued imagery although text is always scanned and stored in gray scale. However, binarization of multivalued image may remove important topological information from characters and introduce noise to character background. In order to avoid this problem, it is indispensable to develop a method which can minimize the information loss due to binarization by extracting features directly from gray scale character images. In this paper, we propose a new method for the direct extraction of topographic features from gray scale character images. By comparing the proposed method with the Wang and Pavlidis`s method we realized that the proposed method enhanced the performance of topographic feature extraction by computing the directions of principal curvature efficiently and prevented the extraction of unnecessary features. We also show that the proposed method is very effective for gray scale skeletonization compared to Levi and Montanari`s method.

  16. Parasitic extraction and magnetic analysis for transformers, inductors and igbt bridge busbar with maxwell 2d and maxwell 3d simulation

    NASA Astrophysics Data System (ADS)

    Zhang, Ning

    This thesis presents the parasitic extraction and magnetic analysis for transformers, inductors, and IGBT bridge busbars with Maxwell 2D and Maxwell 3D simulation. In the first chapter, the magnetic field of a transformer in Maxwell 2D is analyzed. The parasitic capacitance between each winding of the transformer are extracted by Maxwell 2D. According to the actual dimensions, the parasitic capacitances are calculated. The results are verified by comparing with the measurement results from 4395A impedance analyzer. In the second chapter, two CM inductors are simulated in Maxwell 3D. One is the conventional winding inductor, the other one is the proposed one. The magnetic field distributions of different winding directions are analyzed. The analysis is verified by the simulation result. The last chapter introduces a technique to analyze, extract, and measure the parasitic inductance of planar busbars. With this technique, the relationship between self-inductance and mutual-inductance is analyzed. Secondly, a total inductance is calculated based on the developed technique. Thirdly, the current paths and the inductance on a planar busbar are investigated with DC-link capacitors. Furthermore, the analysis of the inductance is addressed. Ansys Q3D simulation and analysis are presented. Finally, the experimental verification is shown by the S-parameter measurement.

  17. Terrestrial laser scanning point clouds time series for the monitoring of slope movements: displacement measurement using image correlation and 3D feature tracking

    NASA Astrophysics Data System (ADS)

    Bornemann, Pierrick; Jean-Philippe, Malet; André, Stumpf; Anne, Puissant; Julien, Travelletti

    2016-04-01

    Dense multi-temporal point clouds acquired with terrestrial laser scanning (TLS) have proved useful for the study of structure and kinematics of slope movements. Most of the existing deformation analysis methods rely on the use of interpolated data. Approaches that use multiscale image correlation provide a precise and robust estimation of the observed movements; however, for non-rigid motion patterns, these methods tend to underestimate all the components of the movement. Further, for rugged surface topography, interpolated data introduce a bias and a loss of information in some local places where the point cloud information is not sufficiently dense. Those limits can be overcome by using deformation analysis exploiting directly the original 3D point clouds assuming some hypotheses on the deformation (e.g. the classic ICP algorithm requires an initial guess by the user of the expected displacement patterns). The objective of this work is therefore to propose a deformation analysis method applied to a series of 20 3D point clouds covering the period October 2007 - October 2015 at the Super-Sauze landslide (South East French Alps). The dense point clouds have been acquired with a terrestrial long-range Optech ILRIS-3D laser scanning device from the same base station. The time series are analyzed using two approaches: 1) a method of correlation of gradient images, and 2) a method of feature tracking in the raw 3D point clouds. The estimated surface displacements are then compared with GNSS surveys on reference targets. Preliminary results tend to show that the image correlation method provides a good estimation of the displacement fields at first order, but shows limitations such as the inability to track some deformation patterns, and the use of a perspective projection that does not maintain original angles and distances in the correlated images. Results obtained with 3D point clouds comparison algorithms (C2C, ICP, M3C2) bring additional information on the

  18. Morphological Feature Extraction for Automatic Registration of Multispectral Images

    NASA Technical Reports Server (NTRS)

    Plaza, Antonio; LeMoigne, Jacqueline; Netanyahu, Nathan S.

    2007-01-01

    The task of image registration can be divided into two major components, i.e., the extraction of control points or features from images, and the search among the extracted features for the matching pairs that represent the same feature in the images to be matched. Manual extraction of control features can be subjective and extremely time consuming, and often results in few usable points. On the other hand, automated feature extraction allows using invariant target features such as edges, corners, and line intersections as relevant landmarks for registration purposes. In this paper, we present an extension of a recently developed morphological approach for automatic extraction of landmark chips and corresponding windows in a fully unsupervised manner for the registration of multispectral images. Once a set of chip-window pairs is obtained, a (hierarchical) robust feature matching procedure, based on a multiresolution overcomplete wavelet decomposition scheme, is used for registration purposes. The proposed method is validated on a pair of remotely sensed scenes acquired by the Advanced Land Imager (ALI) multispectral instrument and the Hyperion hyperspectral instrument aboard NASA's Earth Observing-1 satellite.

  19. The characterization and optimization of NIO1 ion source extraction aperture using a 3D particle-in-cell code

    NASA Astrophysics Data System (ADS)

    Taccogna, F.; Minelli, P.; Cavenago, M.; Veltri, P.; Ippolito, N.

    2016-02-01

    The geometry of a single aperture in the extraction grid plays a relevant role for the optimization of negative ion transport and extraction probability in a hybrid negative ion source. For this reason, a three-dimensional particle-in-cell/Monte Carlo collision model of the extraction region around the single aperture including part of the source and part of the acceleration (up to the extraction grid (EG) middle) regions has been developed for the new aperture design prepared for negative ion optimization 1 source. Results have shown that the dimension of the flat and chamfered parts and the slope of the latter in front of the source region maximize the product of production rate and extraction probability (allowing the best EG field penetration) of surface-produced negative ions. The negative ion density in the plane yz has been reported.

  20. The characterization and optimization of NIO1 ion source extraction aperture using a 3D particle-in-cell code.

    PubMed

    Taccogna, F; Minelli, P; Cavenago, M; Veltri, P; Ippolito, N

    2016-02-01

    The geometry of a single aperture in the extraction grid plays a relevant role for the optimization of negative ion transport and extraction probability in a hybrid negative ion source. For this reason, a three-dimensional particle-in-cell/Monte Carlo collision model of the extraction region around the single aperture including part of the source and part of the acceleration (up to the extraction grid (EG) middle) regions has been developed for the new aperture design prepared for negative ion optimization 1 source. Results have shown that the dimension of the flat and chamfered parts and the slope of the latter in front of the source region maximize the product of production rate and extraction probability (allowing the best EG field penetration) of surface-produced negative ions. The negative ion density in the plane yz has been reported. PMID:26932027

  1. EEG signal features extraction based on fractal dimension.

    PubMed

    Finotello, Francesca; Scarpa, Fabio; Zanon, Mattia

    2015-08-01

    The spread of electroencephalography (EEG) in countless applications has fostered the development of new techniques for extracting synthetic and informative features from EEG signals. However, the definition of an effective feature set depends on the specific problem to be addressed and is currently an active field of research. In this work, we investigated the application of features based on fractal dimension to a problem of sleep identification from EEG data. We demonstrated that features based on fractal dimension, including two novel indices defined in this work, add valuable information to standard EEG features and significantly improve sleep identification performance. PMID:26737209

  2. Feature Extraction and Selection Strategies for Automated Target Recognition

    NASA Technical Reports Server (NTRS)

    Greene, W. Nicholas; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

    2010-01-01

    Several feature extraction and selection methods for an existing automatic target recognition (ATR) system using JPLs Grayscale Optical Correlator (GOC) and Optimal Trade-Off Maximum Average Correlation Height (OT-MACH) filter were tested using MATLAB. The ATR system is composed of three stages: a cursory region of-interest (ROI) search using the GOC and OT-MACH filter, a feature extraction and selection stage, and a final classification stage. Feature extraction and selection concerns transforming potential target data into more useful forms as well as selecting important subsets of that data which may aide in detection and classification. The strategies tested were built around two popular extraction methods: Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Performance was measured based on the classification accuracy and free-response receiver operating characteristic (FROC) output of a support vector machine(SVM) and a neural net (NN) classifier.

  3. A Comprehensive Automated 3D Approach for Building Extraction, Reconstruction, and Regularization from Airborne Laser Scanning Point Clouds

    PubMed Central

    Dorninger, Peter; Pfeifer, Norbert

    2008-01-01

    Three dimensional city models are necessary for supporting numerous management applications. For the determination of city models for visualization purposes, several standardized workflows do exist. They are either based on photogrammetry or on LiDAR or on a combination of both data acquisition techniques. However, the automated determination of reliable and highly accurate city models is still a challenging task, requiring a workflow comprising several processing steps. The most relevant are building detection, building outline generation, building modeling, and finally, building quality analysis. Commercial software tools for building modeling require, generally, a high degree of human interaction and most automated approaches described in literature stress the steps of such a workflow individually. In this article, we propose a comprehensive approach for automated determination of 3D city models from airborne acquired point cloud data. It is based on the assumption that individual buildings can be modeled properly by a composition of a set of planar faces. Hence, it is based on a reliable 3D segmentation algorithm, detecting planar faces in a point cloud. This segmentation is of crucial importance for the outline detection and for the modeling approach. We describe the theoretical background, the segmentation algorithm, the outline detection, and the modeling approach, and we present and discuss several actual projects.

  4. Automated feature extraction and classification from image sources

    USGS Publications Warehouse

    U.S. Geological Survey

    1995-01-01

    The U.S. Department of the Interior, U.S. Geological Survey (USGS), and Unisys Corporation have completed a cooperative research and development agreement (CRADA) to explore automated feature extraction and classification from image sources. The CRADA helped the USGS define the spectral and spatial resolution characteristics of airborne and satellite imaging sensors necessary to meet base cartographic and land use and land cover feature classification requirements and help develop future automated geographic and cartographic data production capabilities. The USGS is seeking a new commercial partner to continue automated feature extraction and classification research and development.

  5. On-chip concentration of bacteria using a 3D dielectrophoretic chip and subsequent laser-based DNA extraction in the same chip

    NASA Astrophysics Data System (ADS)

    Cho, Yoon-Kyoung; Kim, Tae-hyeong; Lee, Jeong-Gun

    2010-06-01

    We report the on-chip concentration of bacteria using a dielectrophoretic (DEP) chip with 3D electrodes and subsequent laser-based DNA extraction in the same chip. The DEP chip has a set of interdigitated Au post electrodes with 50 µm height to generate a network of non-uniform electric fields for the efficient trapping by DEP. The metal post array was fabricated by photolithography and subsequent Ni and Au electroplating. Three model bacteria samples (Escherichia coli, Staphylococcus epidermidis, Streptococcus mutans) were tested and over 80-fold concentrations were achieved within 2 min. Subsequently, on-chip DNA extraction from the concentrated bacteria in the 3D DEP chip was performed by laser irradiation using the laser-irradiated magnetic bead system (LIMBS) in the same chip. The extracted DNA was analyzed with silicon chip-based real-time polymerase chain reaction (PCR). The total process of on-chip bacteria concentration and the subsequent DNA extraction can be completed within 10 min including the manual operation time.

  6. Invariant facial feature extraction using biologically inspired strategies

    NASA Astrophysics Data System (ADS)

    Du, Xing; Gong, Weiguo

    2011-12-01

    In this paper, a feature extraction model for face recognition is proposed. This model is constructed by implementing three biologically inspired strategies, namely a hierarchical network, a learning mechanism of the V1 simple cells, and a data-driven attention mechanism. The hierarchical network emulates the functions of the V1 cortex to progressively extract facial features invariant to illumination, expression, slight pose change, and variations caused by local transformation of facial parts. In the network, filters that account for the local structures of the face are derived through the learning mechanism and used for the invariant feature extraction. The attention mechanism computes a saliency map for the face, and enhances the salient regions of the invariant features to further improve the performance. Experiments on the FERET and AR face databases show that the proposed model boosts the recognition accuracy effectively.

  7. Feature extraction from multiple data sources using genetic programming

    NASA Astrophysics Data System (ADS)

    Szymanski, John J.; Brumby, Steven P.; Pope, Paul A.; Eads, Damian R.; Esch-Mosher, Diana M.; Galassi, Mark C.; Harvey, Neal R.; McCulloch, Hersey D.; Perkins, Simon J.; Porter, Reid B.; Theiler, James P.; Young, Aaron C.; Bloch, Jeffrey J.; David, Nancy A.

    2002-08-01

    Feature extraction from imagery is an important and long-standing problem in remote sensing. In this paper, we report on work using genetic programming to perform feature extraction simultaneously from multispectral and digital elevation model (DEM) data. We use the GENetic Imagery Exploitation (GENIE) software for this purpose, which produces image-processing software that inherently combines spatial and spectral processing. GENIE is particularly useful in exploratory studies of imagery, such as one often does in combining data from multiple sources. The user trains the software by painting the feature of interest with a simple graphical user interface. GENIE then uses genetic programming techniques to produce an image-processing pipeline. Here, we demonstrate evolution of image processing algorithms that extract a range of land cover features including towns, wildfire burnscars, and forest. We use imagery from the DOE/NNSA Multispectral Thermal Imager (MTI) spacecraft, fused with USGS 1:24000 scale DEM data.

  8. Distinctive Feature Extraction for Indian Sign Language (ISL) Gesture using Scale Invariant Feature Transform (SIFT)

    NASA Astrophysics Data System (ADS)

    Patil, Sandeep Baburao; Sinha, G. R.

    2016-07-01

    India, having less awareness towards the deaf and dumb peoples leads to increase the communication gap between deaf and hard hearing community. Sign language is commonly developed for deaf and hard hearing peoples to convey their message by generating the different sign pattern. The scale invariant feature transform was introduced by David Lowe to perform reliable matching between different images of the same object. This paper implements the various phases of scale invariant feature transform to extract the distinctive features from Indian sign language gestures. The experimental result shows the time constraint for each phase and the number of features extracted for 26 ISL gestures.

  9. 3D Spray Droplet Distributions in Sneezes

    NASA Astrophysics Data System (ADS)

    Techet, Alexandra; Scharfman, Barry; Bourouiba, Lydia

    2015-11-01

    3D spray droplet clouds generated during human sneezing are investigated using the Synthetic Aperture Feature Extraction (SAFE) method, which relies on light field imaging (LFI) and synthetic aperture (SA) refocusing computational photographic techniques. An array of nine high-speed cameras are used to image sneeze droplets and tracked the droplets in 3D space and time (3D + T). An additional high-speed camera is utilized to track the motion of the head during sneezing. In the SAFE method, the raw images recorded by each camera in the array are preprocessed and binarized, simplifying post processing after image refocusing and enabling the extraction of feature sizes and positions in 3D + T. These binary images are refocused using either additive or multiplicative methods, combined with thresholding. Sneeze droplet centroids, radii, distributions and trajectories are determined and compared with existing data. The reconstructed 3D droplet centroids and radii enable a more complete understanding of the physical extent and fluid dynamics of sneeze ejecta. These measurements are important for understanding the infectious disease transmission potential of sneezes in various indoor environments.

  10. Extraction of 3d transition metals from molten cesium-sodium-potassium/acetate eutectic into dodecane using organophosphorous ligands

    SciTech Connect

    Maroni, V.A.; Philbin, C.E.; Yonco, R.M.

    1983-01-01

    Measurements have been made of the transfer of the transition metal cations Cr/sup 3 +/, Fe/sup 2 +/, Co/sup 2 +/, Ni/sup 2 +/ from molten cesium acetate-sodium acetate-potassium acetate eutectic (50-25-25 mol%, mp approx. 90/sup 0/C) into dodecane solutions containing selected acidic and neutral organophosphorous extracting ligands. The ordering of the transition metals according to their relative extents of extraction into the dodecane phase when the ligand bis(2-ethylhexyl)-phosphinic acid, H(DEPH), is employed (and the conditions of extraction are the same for each cation) is Co/sup 2 +/ > Fe/sup 2 +/ > Cr/sup 3 +/ > Ni/sup 2 +/. Comparisons of results obtained using the acidic ligand H(DEPH) and the neutral ligand tri-n-octylphosphine oxide, TOPO, indicate that the extractible TM complex does not contain acetate as a charge neutralizing ligand, but rather requires complete displacement of inner sphere acetate ions by protonated and/or deprotonated alkylphosphinate groups. The mechanism controlling the transfer kinetics has not been elucidated, but the rates of extraction from the acetate eutectic appear to be somewhat slower than has been observed for the extraction of transition metals from molten alkali metal thiocyanate and nitrate media at comparable temperatures, i.e., 140 ..-->.. 180/sup 0/C. 13 references, 2 figures, 2 tables.

  11. Extraction of 3d transition metals from molten cesium-sodium-potassium/acetate eutectic into dodecane using organophosphorous ligands

    SciTech Connect

    Maroni, V.A.; Philbin, C.E.; Yonco, R.M.

    1983-01-01

    Experimental results are reported for the transfer of the transition metal (TM) cations Cr/sup 3 +/, Fe/sup 2 +/, Co/sup 2 +/, Ni/sup 2 +/ from molten cesium acetate-sodium acetate-potassium acetate eutectic (50-25-25 mol%, mp approx. 90/sup 0/C) into dodecane solutions containing selected acidic and neutral organophosphorous extracting ligands. The ordering of the transition metals according to their relative extents of extraction into the dodecane phase when the ligand bis(2-ethylhexyl)-phosphinic acid, H(DEPH), is employed (and the conditions of extraction are the same for each cation) is Co/sup 2 +/ > Fe/sup 2 +/ > Cr/sup 3 +/ > Ni/sup 2 +/. Comparisons of results obtained using the acidic ligand H(DEPH) and the neutral ligand tri-n-octylphosphine oxide, TOPO, indicate that the extractible TM complex does not contain acetate as a charge neutralizing ligand, but rather requires complete displacement of inner sphere acetate ions by protonated and/or deprotonated alkylphosphinate groups. The mechanism controlling the transfer kinetics has not been elucidated, but the rates of extraction from the acetate eutectic appear to be somewhat slower than has been observed for the extraction of transition metals from molten alkali metal thiocyanate and nitrate media at comparable temperatures, i.e., 140 ..-->.. 180/sup 0/C. 13 references, 2 figures, 2 tables.

  12. Extraction of 3d transition metals from molten cesium-sodium-potassium/acetate eutectic into dodecane using organophosphorous ligands

    SciTech Connect

    Maroni, V.A.; Philbin, C.E.; Yonco, R.M.

    1983-04-01

    Measurements have been made of the transfer of the transition metal cations Cr/sup 3 +/, Fe/sup 2 +/, Co/sup 2 +/, Ni/sup 2 +/ from molten cesium acetate-sodium acetate-potassium acetate eutectic (50-25-25 mol%, mp approx. 90/sup 0/C) into dodecane solutions containing selected acidic and neutral organophosphorous extracting ligands. The ordering of the relative rates and extents of extraction when the ligand bis(2-ethylhexyl)phosphinic acid, H(DEPH), is employed (and the conditions of extraction are the same for each cation) is Co/sup 2 +/ > Fe/sup 2 +/ > Cr/sup 3 +/ > Ni/sup 2 +/. Comparisons of results obtained using the acidic ligand H(DEPH) and the neutralligand Tri-n-octylphosphien oxide, TOPO, indicate that the extractible TM complex does not contain acetate as a charge neutralizing ligand, but rather requires complete displacement of inner sphere acetate ions by both protonated and deprotonated alkylphosphinate groups. In the case of Co/sup 2 +/, the extraction reaction involves the transformation of the cation from an octahedral ligand field in the acetate eutectic to a tetrahedral ligand field in the H(DEPH)/dodecane phase. The mechanism(s) controlling the transfer kinetics has not been elucidated, but it is noted that the rates of extraction from the acetate eutectic seem to be much slower than has been observed for extractions of transition metals from molten alkali metal thiocyanate and nitrate media over comparable temperature ranges (140 to 180/sup 0/C). 1 figure, 2 tables.

  13. Fast SIFT design for real-time visual feature extraction.

    PubMed

    Chiu, Liang-Chi; Chang, Tian-Sheuan; Chen, Jiun-Yen; Chang, Nelson Yen-Chung

    2013-08-01

    Visual feature extraction with scale invariant feature transform (SIFT) is widely used for object recognition. However, its real-time implementation suffers from long latency, heavy computation, and high memory storage because of its frame level computation with iterated Gaussian blur operations. Thus, this paper proposes a layer parallel SIFT (LPSIFT) with integral image, and its parallel hardware design with an on-the-fly feature extraction flow for real-time application needs. Compared with the original SIFT algorithm, the proposed approach reduces the computational amount by 90% and memory usage by 95%. The final implementation uses 580-K gate count with 90-nm CMOS technology, and offers 6000 feature points/frame for VGA images at 30 frames/s and ∼ 2000 feature points/frame for 1920 × 1080 images at 30 frames/s at the clock rate of 100 MHz. PMID:23743775

  14. Automated Image Registration Using Morphological Region of Interest Feature Extraction

    NASA Technical Reports Server (NTRS)

    Plaza, Antonio; LeMoigne, Jacqueline; Netanyahu, Nathan S.

    2005-01-01

    With the recent explosion in the amount of remotely sensed imagery and the corresponding interest in temporal change detection and modeling, image registration has become increasingly important as a necessary first step in the integration of multi-temporal and multi-sensor data for applications such as the analysis of seasonal and annual global climate changes, as well as land use/cover changes. The task of image registration can be divided into two major components: (1) the extraction of control points or features from images; and (2) the search among the extracted features for the matching pairs that represent the same feature in the images to be matched. Manual control feature extraction can be subjective and extremely time consuming, and often results in few usable points. Automated feature extraction is a solution to this problem, where desired target features are invariant, and represent evenly distributed landmarks such as edges, corners and line intersections. In this paper, we develop a novel automated registration approach based on the following steps. First, a mathematical morphology (MM)-based method is used to obtain a scale-orientation morphological profile at each image pixel. Next, a spectral dissimilarity metric such as the spectral information divergence is applied for automated extraction of landmark chips, followed by an initial approximate matching. This initial condition is then refined using a hierarchical robust feature matching (RFM) procedure. Experimental results reveal that the proposed registration technique offers a robust solution in the presence of seasonal changes and other interfering factors. Keywords-Automated image registration, multi-temporal imagery, mathematical morphology, robust feature matching.

  15. Investigation of image feature extraction by a genetic algorithm

    NASA Astrophysics Data System (ADS)

    Brumby, Steven P.; Theiler, James P.; Perkins, Simon J.; Harvey, Neal R.; Szymanski, John J.; Bloch, Jeffrey J.; Mitchell, Melanie

    1999-11-01

    We describe the implementation and performance of a genetic algorithm which generates image feature extraction algorithms for remote sensing applications. We describe our basis set of primitive image operators and present our chromosomal representation of a complete algorithm. Our initial application has been geospatial feature extraction using publicly available multi-spectral aerial-photography data sets. We present the preliminary results of our analysis of the efficiency of the classic genetic operations of crossover and mutation for our application, and discuss our choice of evolutionary control parameters. We exhibit some of our evolved algorithms, and discuss possible avenues for future progress.

  16. Coevolving feature extraction agents for target recognition in SAR images

    NASA Astrophysics Data System (ADS)

    Bhanu, Bir; Krawiec, Krzysztof

    2003-09-01

    This paper describes a novel evolutionary method for automatic induction of target recognition procedures from examples. The learning process starts with training data containing SAR images with labeled targets and consists in coevolving the population of feature extraction agents that cooperate to build an appropriate representation of the input image. Features extracted by a team of cooperating agents are used to induce a machine learning classifier that is responsible for making the final decision of recognizing a target in a SAR image. Each agent (individual) contains feature extraction procedure encoded according to the principles of linear genetic programming (LGP). Like 'plain' genetic programming, in LGP an agent's genome encodes a program that is executed and tested on the set of training images during the fitness calculation. The program is a sequence of calls to the library of parameterized operations, including, but not limited to, global and local image processing operations, elementary feature extraction, and logic and arithmetic operations. Particular calls operate on working variables that enable the program to store intermediate results, and therefore design complex features. This paper contains detailed description of the learning and recognition methodology outlined here. In experimental part, we report and analyze the results obtained when testing the proposed approach for SAR target recognition using MSTAR database.

  17. 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

  18. 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. PMID:24696801

  19. On-line object feature extraction for multispectral scene representation

    NASA Technical Reports Server (NTRS)

    Ghassemian, Hassan; Landgrebe, David

    1988-01-01

    A new on-line unsupervised object-feature extraction method is presented that reduces the complexity and costs associated with the analysis of the multispectral image data and data transmission, storage, archival and distribution. The ambiguity in the object detection process can be reduced if the spatial dependencies, which exist among the adjacent pixels, are intelligently incorporated into the decision making process. The unity relation was defined that must exist among the pixels of an object. Automatic Multispectral Image Compaction Algorithm (AMICA) uses the within object pixel-feature gradient vector as a valuable contextual information to construct the object's features, which preserve the class separability information within the data. For on-line object extraction the path-hypothesis and the basic mathematical tools for its realization are introduced in terms of a specific similarity measure and adjacency relation. AMICA is applied to several sets of real image data, and the performance and reliability of features is evaluated.

  20. Feature extraction from multiple data sources using genetic programming.

    SciTech Connect

    Szymanski, J. J.; Brumby, Steven P.; Pope, P. A.; Eads, D. R.; Galassi, M. C.; Harvey, N. R.; Perkins, S. J.; Porter, R. B.; Theiler, J. P.; Young, A. C.; Bloch, J. J.; David, N. A.; Esch-Mosher, D. M.

    2002-01-01

    Feature extration from imagery is an important and long-standing problem in remote sensing. In this paper, we report on work using genetic programming to perform feature extraction simultaneously from multispectral and digital elevation model (DEM) data. The tool used is the GENetic Imagery Exploitation (GENIE) software, which produces image-processing software that inherently combines spatial and spectral processing. GENIE is particularly useful in exploratory studies of imagery, such as one often does in combining data from multiple sources. The user trains the software by painting the feature of interest with a simple graphical user interface. GENIE then uses genetic programming techniques to produce an image-processing pipeline. Here, we demonstrate evolution of image processing algorithms that extract a range of land-cover features including towns, grasslands, wild fire burn scars, and several types of forest. We use imagery from the DOE/NNSA Multispectral Thermal Imager (MTI) spacecraft, fused with USGS 1:24000 scale DEM data.

  1. Image feature extraction based multiple ant colonies cooperation

    NASA Astrophysics Data System (ADS)

    Zhang, Zhilong; Yang, Weiping; Li, Jicheng

    2015-05-01

    This paper presents a novel image feature extraction algorithm based on multiple ant colonies cooperation. Firstly, a low resolution version of the input image is created using Gaussian pyramid algorithm, and two ant colonies are spread on the source image and low resolution image respectively. The ant colony on the low resolution image uses phase congruency as its inspiration information, while the ant colony on the source image uses gradient magnitude as its inspiration information. These two ant colonies cooperate to extract salient image features through sharing a same pheromone matrix. After the optimization process, image features are detected based on thresholding the pheromone matrix. Since gradient magnitude and phase congruency of the input image are used as inspiration information of the ant colonies, our algorithm shows higher intelligence and is capable of acquiring more complete and meaningful image features than other simpler edge detectors.

  2. Extracting alveolar structure of human lung tissue specimens based on surface skeleton representation from 3D micro-CT images

    NASA Astrophysics Data System (ADS)

    Ishimori, Hiroyuki; Kawata, Yoshiki; Niki, Noboru; Nakaya, Yoshihiro; Ohmatsu, Hironobu; Matsui, Eisuke; Fujii, Masashi; Moriyama, Noriyuki

    2007-03-01

    We have developed a Micro CT system for understanding lung function at a high resolution of the micrometer order (up to 5µm in spatial resolution). Micro CT system enables the removal specimen of lungs to be observed at micro level, has expected a big contribution for micro internal organs morphology and the image diagnosis study. In this research, we develop system to visualize lung microstructures in three dimensions from micro CT images and analyze them. They characterize in that high CT value of the noise area is, and the difficulty of only using threshold processing to extract the alveolar wall of micro CT images. Thus, we are developing a method of extracting the alveolar wall with surface thinning algorithm. In this report, we propose the method which reduces the excessive degeneracy of figure which caused by surface thinning process. And, we apply this algorithm to the micro CT image of the actual pulmonary specimen. It is shown that the extraction of the alveolus wall becomes possible in the high precision.

  3. A common feature-based 3D-pharmacophore model generation and virtual screening: identification of potential PfDHFR inhibitors.

    PubMed

    Adane, Legesse; Bharatam, Prasad V; Sharma, Vikas

    2010-10-01

    A four-feature 3D-pharmacophore model was built from a set of 24 compounds whose activities were reported against the V1/S strain of the Plasmodium falciparum dihydrofolate reductase (PfDHFR) enzyme. This is an enzyme harboring Asn51Ile + Cys59Arg + Ser108Asn + Ile164Leu mutations. The HipHop module of the Catalyst program was used to generate the model. Selection of the best model among the 10 hypotheses generated by HipHop was carried out based on rank and best-fit values or alignments of the training set compounds onto a particular hypothesis. The best model (hypo1) consisted of two H-bond donors, one hydrophobic aromatic, and one hydrophobic aliphatic features. Hypo1 was used as a query to virtually screen Maybridge2004 and NCI2000 databases. The hits obtained from the search were subsequently subjected to FlexX and Glide docking studies. Based on the binding scores and interactions in the active site of quadruple-mutant PfDHFR, a set of nine hits were identified as potential inhibitors. PMID:19995305

  4. Self-assembled 3D heterometallic Cu(II)/Fe(II) coordination polymers with octahedral net skeletons: structural features, molecular magnetism, thermal and oxidation catalytic properties.

    PubMed

    Karabach, Yauhen Y; Guedes da Silva, M Fátima C; Kopylovich, Maximilian N; Gil-Hernández, Beatriz; Sanchiz, Joaquin; Kirillov, Alexander M; Pombeiro, Armando J L

    2010-12-01

    The new three-dimensional (3D) heterometallic Cu(II)/Fe(II) coordination polymers [Cu(6)(H(2)tea)(6)Fe(CN)(6)](n)(NO(3))(2n)·6nH(2)O (1) and [Cu(6)(Hmdea)(6)Fe(CN)(6)](n)(NO(3))(2n)·7nH(2)O (2) have been easily generated by aqueous-medium self-assembly reactions of copper(II) nitrate with triethanolamine or N-methyldiethanolamine (H(3)tea or H(2)mdea, respectively), in the presence of potassium ferricyanide and sodium hydroxide. They have been isolated as air-stable crystalline solids and fully characterized including by single-crystal X-ray diffraction analyses. The latter reveal the formation of 3D metal-organic frameworks that are constructed from the [Cu(2)(μ-H(2)tea)(2)](2+) or [Cu(2)(μ-Hmdea)(2)](2+) nodes and the octahedral [Fe(CN)(6)](4-) linkers, featuring regular (1) or distorted (2) octahedral net skeletons. Upon dehydration, both compounds show reversible escape and binding processes toward water or methanol molecules. Magnetic susceptibility measurements of 1 and 2 reveal strong antiferromagnetic [J = -199(1) cm(-1)] or strong ferromagnetic [J = +153(1) cm(-1)] couplings between the copper(II) ions through the μ-O-alkoxo atoms in 1 or 2, respectively. The differences in magnetic behavior are explained in terms of the dependence of the magnetic coupling constant on the Cu-O-Cu bridging angle. Compounds 1 and 2 also act as efficient catalyst precursors for the mild oxidation of cyclohexane by aqueous hydrogen peroxide to cyclohexanol and cyclohexanone (homogeneous catalytic system), leading to maximum total yields (based on cyclohexane) and turnover numbers (TONs) up to about 22% and 470, respectively. PMID:21028781

  5. Fast and robust extraction of centerlines in 3D tubular structures using a scattered-snakelet approach

    NASA Astrophysics Data System (ADS)

    Spuhler, Christoph; Harders, Matthias; Székely, Gábor

    2006-03-01

    We present a fast and robust approach for automatic centerline extraction of tubular structures. The underlying idea is to cut traditional snakes into a set of shorter, independent segments - so-called snakelets. Following the same variational principles, each snakelet acts locally and extracts a subpart of the overall structure. After a parallel optimization step, outliers are detected and the remaining segments then form an implicit centerline. No manual initialization of the snakelets is necessary, which represents one advantage of the method. Moreover, computational complexity does not directly depend on dataset size, but on the number of snake segments necessary to cover the structure of interest, resulting in short computation times. Lastly, the approach is robust even for very complex datasets such as the small intestine. Our approach was tested on several medical datasets (CT datasets of colon, small bowel, and blood vessels) and yielded smooth, connected centerlines with few or no branches. The computation time needed is less than a minute using standard computing hardware.

  6. 3D scene modeling from multiple range views

    NASA Astrophysics Data System (ADS)

    Sequeira, Vitor; Goncalves, Joao G. M.; Ribeiro, M. Isabel

    1995-09-01

    This paper presents a new 3D scene analysis system that automatically reconstructs the 3D geometric model of real-world scenes from multiple range images acquired by a laser range finder on board of a mobile robot. The reconstruction is achieved through an integrated procedure including range data acquisition, geometrical feature extraction, registration, and integration of multiple views. Different descriptions of the final 3D scene model are obtained: a polygonal triangular mesh, a surface description in terms of planar and biquadratics surfaces, and a 3D boundary representation. Relevant experimental results from the complete 3D scene modeling are presented. Direct applications of this technique include 3D reconstruction and/or update of architectual or industrial plans into a CAD model, design verification of buildings, navigation of autonomous robots, and input to virtual reality systems.

  7. Syzygium aromaticum extract mediated, rapid and facile biogenic synthesis of shape-controlled (3D) silver nanocubes.

    PubMed

    Chaudhari, Anuj N; Ingale, Arun G

    2016-06-01

    The synthesis of metal nano materials with controllable geometry has received extensive attention of researchers from the past decade. In this study, we report an unexplored new route for rapid and facile biogenic synthesis of silver nanocubes (AgNCs) by systematic reduction of silver ions with crude clove (Syzygium aromaticum) extract at room temperature. The formation and plasmonic properties of AgNCs were observed and the UV-vis spectra show characteristic absorption peak of AgNCs with broaden region at 430 nm along with the intense (124), (686), (454) and (235) peak in X-ray diffraction pattern confirmed the formation and crystallinity of AgNCs. The average size of AgNC cubes were found to be in the range of ~80 to 150 nm and it was confirmed by particles size distribution, scanning and transmission electron microscopy with elemental detection by EDAX. Further FTIR spectra provide the various functional groups present in the S. aromaticum extract which are supposed to be responsible and participating in the reaction for the synthesis of AgNCs. The AgNCs casted over glass substrate show an electrical conductivity of ~0.55 × 10(6) S/m demonstrating AgNCs to be a potential next generation conducting material due to its high conductivity. This work provides a novel and effective approach to control the shape of silver nanomaterial for impending applications. The current synthesis mode is eco-friendly, low cost and promises different potential applications such as biosensing, nanoelectronics, etc. PMID:26921103

  8. A semi-automatic method to extract canal pathways in 3D micro-CT images of Octocorals.

    PubMed

    Morales Pinzón, Alfredo; Orkisz, Maciej; Rodríguez Useche, Catalina María; Torres González, Juan Sebastián; Teillaud, Stanislas; Sánchez, Juan Armando; Hernández Hoyos, Marcela

    2014-01-01

    The long-term goal of our study is to understand the internal organization of the octocoral stem canals, as well as their physiological and functional role in the growth of the colonies, and finally to assess the influence of climatic changes on this species. Here we focus on imaging tools, namely acquisition and processing of three-dimensional high-resolution images, with emphasis on automated extraction of canal pathways. Our aim was to evaluate the feasibility of the whole process, to point out and solve - if possible - technical problems related to the specimen conditioning, to determine the best acquisition parameters and to develop necessary image-processing algorithms. The pathways extracted are expected to facilitate the structural analysis of the colonies, namely to help observing the distribution, formation and number of canals along the colony. Five volumetric images of Muricea muricata specimens were successfully acquired by X-ray computed tomography with spatial resolution ranging from 4.5 to 25 micrometers. The success mainly depended on specimen immobilization. More than [Formula: see text] of the canals were successfully detected and tracked by the image-processing method developed. Thus obtained three-dimensional representation of the canal network was generated for the first time without the need of histological or other destructive methods. Several canal patterns were observed. Although most of them were simple, i.e. only followed the main branch or "turned" into a secondary branch, many others bifurcated or fused. A majority of bifurcations were observed at branching points. However, some canals appeared and/or ended anywhere along a branch. At the tip of a branch, all canals fused into a unique chamber. Three-dimensional high-resolution tomographic imaging gives a non-destructive insight to the coral ultrastructure and helps understanding the organization of the canal network. Advanced image-processing techniques greatly reduce human observer

  9. A Semi-Automatic Method to Extract Canal Pathways in 3D Micro-CT Images of Octocorals

    PubMed Central

    Morales Pinzón, Alfredo; Orkisz, Maciej; Rodríguez Useche, Catalina María; Torres González, Juan Sebastián; Teillaud, Stanislas; Sánchez, Juan Armando; Hernández Hoyos, Marcela

    2014-01-01

    The long-term goal of our study is to understand the internal organization of the octocoral stem canals, as well as their physiological and functional role in the growth of the colonies, and finally to assess the influence of climatic changes on this species. Here we focus on imaging tools, namely acquisition and processing of three-dimensional high-resolution images, with emphasis on automated extraction of canal pathways. Our aim was to evaluate the feasibility of the whole process, to point out and solve – if possible – technical problems related to the specimen conditioning, to determine the best acquisition parameters and to develop necessary image-processing algorithms. The pathways extracted are expected to facilitate the structural analysis of the colonies, namely to help observing the distribution, formation and number of canals along the colony. Five volumetric images of Muricea muricata specimens were successfully acquired by X-ray computed tomography with spatial resolution ranging from 4.5 to 25 micrometers. The success mainly depended on specimen immobilization. More than of the canals were successfully detected and tracked by the image-processing method developed. Thus obtained three-dimensional representation of the canal network was generated for the first time without the need of histological or other destructive methods. Several canal patterns were observed. Although most of them were simple, i.e. only followed the main branch or “turned” into a secondary branch, many others bifurcated or fused. A majority of bifurcations were observed at branching points. However, some canals appeared and/or ended anywhere along a branch. At the tip of a branch, all canals fused into a unique chamber. Three-dimensional high-resolution tomographic imaging gives a non-destructive insight to the coral ultrastructure and helps understanding the organization of the canal network. Advanced image-processing techniques greatly reduce human observer's effort and

  10. Bilinear analysis for kernel selection and nonlinear feature extraction.

    PubMed

    Yang, Shu; Yan, Shuicheng; Zhang, Chao; Tang, Xiaoou

    2007-09-01

    This paper presents a unified criterion, Fisher + kernel criterion (FKC), for feature extraction and recognition. This new criterion is intended to extract the most discriminant features in different nonlinear spaces, and then, fuse these features under a unified measurement. Thus, FKC can simultaneously achieve nonlinear discriminant analysis and kernel selection. In addition, we present an efficient algorithm Fisher + kernel analysis (FKA), which utilizes the bilinear analysis, to optimize the new criterion. This FKA algorithm can alleviate the ill-posed problem existed in traditional kernel discriminant analysis (KDA), and usually, has no singularity problem. The effectiveness of our proposed algorithm is validated by a series of face-recognition experiments on several different databases. PMID:18220192

  11. Genetic programming approach to extracting features from remotely sensed imagery

    SciTech Connect

    Theiler, J. P.; Perkins, S. J.; Harvey, N. R.; Szymanski, J. J.; Brumby, Steven P.

    2001-01-01

    Multi-instrument data sets present an interesting challenge to feature extraction algorithm developers. Beyond the immediate problems of spatial co-registration, the remote sensing scientist must explore a complex algorithm space in which both spatial and spectral signatures may be required to identify a feature of interest. We describe a genetic programming/supervised classifier software system, called Genie, which evolves and combines spatio-spectral image processing tools for remotely sensed imagery. We describe our representation of candidate image processing pipelines, and discuss our set of primitive image operators. Our primary application has been in the field of geospatial feature extraction, including wildfire scars and general land-cover classes, using publicly available multi-spectral imagery (MSI) and hyper-spectral imagery (HSI). Here, we demonstrate our system on Landsat 7 Enhanced Thematic Mapper (ETM+) MSI. We exhibit an evolved pipeline, and discuss its operation and performance.

  12. An Automatic Registration Algorithm for 3D Maxillofacial Model

    NASA Astrophysics Data System (ADS)

    Qiu, Luwen; Zhou, Zhongwei; Guo, Jixiang; Lv, Jiancheng

    2016-09-01

    3D image registration aims at aligning two 3D data sets in a common coordinate system, which has been widely used in computer vision, pattern recognition and computer assisted surgery. One challenging problem in 3D registration is that point-wise correspondences between two point sets are often unknown apriori. In this work, we develop an automatic algorithm for 3D maxillofacial models registration including facial surface model and skull model. Our proposed registration algorithm can achieve a good alignment result between partial and whole maxillofacial model in spite of ambiguous matching, which has a potential application in the oral and maxillofacial reparative and reconstructive surgery. The proposed algorithm includes three steps: (1) 3D-SIFT features extraction and FPFH descriptors construction; (2) feature matching using SAC-IA; (3) coarse rigid alignment and refinement by ICP. Experiments on facial surfaces and mandible skull models demonstrate the efficiency and robustness of our algorithm.

  13. Feature extraction and classification algorithms for high dimensional data

    NASA Technical Reports Server (NTRS)

    Lee, Chulhee; Landgrebe, David

    1993-01-01

    Feature extraction and classification algorithms for high dimensional data are investigated. Developments with regard to sensors for Earth observation are moving in the direction of providing much higher dimensional multispectral imagery than is now possible. In analyzing such high dimensional data, processing time becomes an important factor. With large increases in dimensionality and the number of classes, processing time will increase significantly. To address this problem, a multistage classification scheme is proposed which reduces the processing time substantially by eliminating unlikely classes from further consideration at each stage. Several truncation criteria are developed and the relationship between thresholds and the error caused by the truncation is investigated. Next an approach to feature extraction for classification is proposed based directly on the decision boundaries. It is shown that all the features needed for classification can be extracted from decision boundaries. A characteristic of the proposed method arises by noting that only a portion of the decision boundary is effective in discriminating between classes, and the concept of the effective decision boundary is introduced. The proposed feature extraction algorithm has several desirable properties: it predicts the minimum number of features necessary to achieve the same classification accuracy as in the original space for a given pattern recognition problem; and it finds the necessary feature vectors. The proposed algorithm does not deteriorate under the circumstances of equal means or equal covariances as some previous algorithms do. In addition, the decision boundary feature extraction algorithm can be used both for parametric and non-parametric classifiers. Finally, some problems encountered in analyzing high dimensional data are studied and possible solutions are proposed. First, the increased importance of the second order statistics in analyzing high dimensional data is recognized

  14. Principal curves for lumen center extraction and flow channel width estimation in 3-D arterial networks: theory, algorithm, and validation.

    PubMed

    Wong, Wilbur C K; So, Ronald W K; Chung, Albert C S

    2012-04-01

    We present an energy-minimization-based framework for locating the centerline and estimating the width of tubelike objects from their structural network with a nonparametric model. The nonparametric representation promotes simple modeling of nested branches and n -way furcations, i.e., structures that abound in an arterial network, e.g., a cerebrovascular circulation. Our method is capable of extracting the entire vascular tree from an angiogram in a single execution with a proper initialization. A succinct initial model from the user with arterial network inlets, outlets, and branching points is sufficient for complex vasculature. The novel method is based upon the theory of principal curves. In this paper, theoretical extension to grayscale angiography is discussed, and an algorithm to find an arterial network as principal curves is also described. Quantitative validation on a number of simulated data sets, synthetic volumes of 19 BrainWeb vascular models, and 32 Rotterdam Coronary Artery volumes was conducted. We compared the algorithm to a state-of-the-art method and further tested it on two clinical data sets. Our algorithmic outputs-lumen centers and flow channel widths-are important to various medical and clinical applications, e.g., vasculature segmentation, registration and visualization, virtual angioscopy, and vascular atlas formation and population study. PMID:22167625

  15. A Spiking Neural Network in sEMG Feature Extraction.

    PubMed

    Lobov, Sergey; Mironov, Vasiliy; Kastalskiy, Innokentiy; Kazantsev, Victor

    2015-01-01

    We have developed a novel algorithm for sEMG feature extraction and classification. It is based on a hybrid network composed of spiking and artificial neurons. The spiking neuron layer with mutual inhibition was assigned as feature extractor. We demonstrate that the classification accuracy of the proposed model could reach high values comparable with existing sEMG interface systems. Moreover, the algorithm sensibility for different sEMG collecting systems characteristics was estimated. Results showed rather equal accuracy, despite a significant sampling rate difference. The proposed algorithm was successfully tested for mobile robot control. PMID:26540060

  16. A Spiking Neural Network in sEMG Feature Extraction

    PubMed Central

    Lobov, Sergey; Mironov, Vasiliy; Kastalskiy, Innokentiy; Kazantsev, Victor

    2015-01-01

    We have developed a novel algorithm for sEMG feature extraction and classification. It is based on a hybrid network composed of spiking and artificial neurons. The spiking neuron layer with mutual inhibition was assigned as feature extractor. We demonstrate that the classification accuracy of the proposed model could reach high values comparable with existing sEMG interface systems. Moreover, the algorithm sensibility for different sEMG collecting systems characteristics was estimated. Results showed rather equal accuracy, despite a significant sampling rate difference. The proposed algorithm was successfully tested for mobile robot control. PMID:26540060

  17. Digital in-line holography for the extraction of 3D trajectories of small particles in a 2D Benard-von Karman flow

    NASA Astrophysics Data System (ADS)

    Salah, Nebya; Allano, Daniel; Godard, Gilles; Malek, Mokrane; Lebrun, Denis; Paranthoën, P.

    2006-09-01

    Digital In-line Holography is widely used to visualize fluid flows seeded with small particles. Such holograms record directly the far-field diffraction patterns of particles on a CCD camera. From the successive reconstruction planes, the three-dimensional location of the particles can be determined. This imaging system doesn't need focusing. The principle is based on the direct analysis of the diffraction patterns by mean of space-frequency operators such as Wavelet Transformation or Fractional Fourier Transformation. This method, already tested in our laboratory, leads to a better resolution than classical holography for the estimation of 3D particle locations (50μm instead of 0.5mm in depth). In the case of moving particles, it is interesting to illuminate the sample volume by several laser pulses. This can be easily realized by controlling the input current of a modulated laser diode. Then, the CCD camera cumulates the sum of in-line particle holograms recorded at different times. By searching for the best focus plane of each particle image, the 3D coordinate of each particle can be extracted at a given time. This technique is applied to determine trajectories of small particles in a well-controlled 2D Benard-von Karman street allowing a Lagrangian approach. Preliminary results are presented.

  18. Event extraction with complex event classification using rich features.

    PubMed

    Miwa, Makoto; Saetre, Rune; Kim, Jin-Dong; Tsujii, Jun'ichi

    2010-02-01

    Biomedical Natural Language Processing (BioNLP) attempts to capture biomedical phenomena from texts by extracting relations between biomedical entities (i.e. proteins and genes). Traditionally, only binary relations have been extracted from large numbers of published papers. Recently, more complex relations (biomolecular events) have also been extracted. Such events may include several entities or other relations. To evaluate the performance of the text mining systems, several shared task challenges have been arranged for the BioNLP community. With a common and consistent task setting, the BioNLP'09 shared task evaluated complex biomolecular events such as binding and regulation.Finding these events automatically is important in order to improve biomedical event extraction systems. In the present paper, we propose an automatic event extraction system, which contains a model for complex events, by solving a classification problem with rich features. The main contributions of the present paper are: (1) the proposal of an effective bio-event detection method using machine learning, (2) provision of a high-performance event extraction system, and (3) the execution of a quantitative error analysis. The proposed complex (binding and regulation) event detector outperforms the best system from the BioNLP'09 shared task challenge. PMID:20183879

  19. Feature extraction on local jet space for texture classification

    NASA Astrophysics Data System (ADS)

    Oliveira, Marcos William da Silva; da Silva, Núbia Rosa; Manzanera, Antoine; Bruno, Odemir Martinez

    2015-12-01

    The proposal of this study is to analyze the texture pattern recognition over the local jet space looking forward to improve the texture characterization. Local jets decompose the image based on partial derivatives allowing the texture feature extraction be exploited in different levels of geometrical structures. Each local jet component evidences a different local pattern, such as, flat regions, directional variations and concavity or convexity. Subsequently, a texture descriptor is used to extract features from 0th, 1st and 2nd-derivative components. Four well-known databases (Brodatz, Vistex, Usptex and Outex) and four texture descriptors (Fourier descriptors, Gabor filters, Local Binary Pattern and Local Binary Pattern Variance) were used to validate the idea, showing in most cases an increase of the success rates.

  20. Optimal feature extraction for segmentation of Diesel spray images.

    PubMed

    Payri, Francisco; Pastor, José V; Palomares, Alberto; Juliá, J Enrique

    2004-04-01

    A one-dimensional simplification, based on optimal feature extraction, of the algorithm based on the likelihood-ratio test method (LRT) for segmentation in colored Diesel spray images is presented. If the pixel values of the Diesel spray and the combustion images are represented in RGB space, in most cases they are distributed in an area with a given so-called privileged direction. It is demonstrated that this direction permits optimal feature extraction for one-dimensional segmentation in the Diesel spray images, and some of its advantages compared with more-conventional one-dimensional simplification methods, including considerably reduced computational cost while accuracy is maintained within more than reasonable limits, are presented. The method has been successfully applied to images of Diesel sprays injected at room temperature as well as to images of sprays with evaporation and combustion. It has proved to be valid for several cameras and experimental arrangements. PMID:15074419

  1. A Review of Feature Selection and Feature Extraction Methods Applied on Microarray Data

    PubMed Central

    Hira, Zena M.; Gillies, Duncan F.

    2015-01-01

    We summarise various ways of performing dimensionality reduction on high-dimensional microarray data. Many different feature selection and feature extraction methods exist and they are being widely used. All these methods aim to remove redundant and irrelevant features so that classification of new instances will be more accurate. A popular source of data is microarrays, a biological platform for gathering gene expressions. Analysing microarrays can be difficult due to the size of the data they provide. In addition the complicated relations among the different genes make analysis more difficult and removing excess features can improve the quality of the results. We present some of the most popular methods for selecting significant features and provide a comparison between them. Their advantages and disadvantages are outlined in order to provide a clearer idea of when to use each one of them for saving computational time and resources. PMID:26170834

  2. The research of edge extraction and target recognition based on inherent feature of objects

    NASA Astrophysics Data System (ADS)

    Xie, Yu-chan; Lin, Yu-chi; Huang, Yin-guo

    2008-03-01

    Current research on computer vision often needs specific techniques for particular problems. Little use has been made of high-level aspects of computer vision, such as three-dimensional (3D) object recognition, that are appropriate for large classes of problems and situations. In particular, high-level vision often focuses mainly on the extraction of symbolic descriptions, and pays little attention to the speed of processing. In order to extract and recognize target intelligently and rapidly, in this paper we developed a new 3D target recognition method based on inherent feature of objects in which cuboid was taken as model. On the basis of analysis cuboid nature contour and greyhound distributing characteristics, overall fuzzy evaluating technique was utilized to recognize and segment the target. Then Hough transform was used to extract and match model's main edges, we reconstruct aim edges by stereo technology in the end. There are three major contributions in this paper. Firstly, the corresponding relations between the parameters of cuboid model's straight edges lines in an image field and in the transform field were summed up. By those, the aimless computations and searches in Hough transform processing can be reduced greatly and the efficiency is improved. Secondly, as the priori knowledge about cuboids contour's geometry character known already, the intersections of the component extracted edges are taken, and assess the geometry of candidate edges matches based on the intersections, rather than the extracted edges. Therefore the outlines are enhanced and the noise is depressed. Finally, a 3-D target recognition method is proposed. Compared with other recognition methods, this new method has a quick response time and can be achieved with high-level computer vision. The method present here can be used widely in vision-guide techniques to strengthen its intelligence and generalization, which can also play an important role in object tracking, port AGV, robots

  3. Automated Feature Extraction of Foredune Morphology from Terrestrial Lidar Data

    NASA Astrophysics Data System (ADS)

    Spore, N.; Brodie, K. L.; Swann, C.

    2014-12-01

    Foredune morphology is often described in storm impact prediction models using the elevation of the dune crest and dune toe and compared with maximum runup elevations to categorize the storm impact and predicted responses. However, these parameters do not account for other foredune features that may make them more or less erodible, such as alongshore variations in morphology, vegetation coverage, or compaction. The goal of this work is to identify other descriptive features that can be extracted from terrestrial lidar data that may affect the rate of dune erosion under wave attack. Daily, mobile-terrestrial lidar surveys were conducted during a 6-day nor'easter (Hs = 4 m in 6 m water depth) along 20km of coastline near Duck, North Carolina which encompassed a variety of foredune forms in close proximity to each other. This abstract will focus on the tools developed for the automated extraction of the morphological features from terrestrial lidar data, while the response of the dune will be presented by Brodie and Spore as an accompanying abstract. Raw point cloud data can be dense and is often under-utilized due to time and personnel constraints required for analysis, since many algorithms are not fully automated. In our approach, the point cloud is first projected into a local coordinate system aligned with the coastline, and then bare earth points are interpolated onto a rectilinear 0.5 m grid creating a high resolution digital elevation model. The surface is analyzed by identifying features along each cross-shore transect. Surface curvature is used to identify the position of the dune toe, and then beach and berm morphology is extracted shoreward of the dune toe, and foredune morphology is extracted landward of the dune toe. Changes in, and magnitudes of, cross-shore slope, curvature, and surface roughness are used to describe the foredune face and each cross-shore transect is then classified using its pre-storm morphology for storm-response analysis.

  4. Extracting BI-RADS Features from Portuguese Clinical Texts

    PubMed Central

    Nassif, Houssam; Cunha, Filipe; Moreira, Inês C.; Cruz-Correia, Ricardo; Sousa, Eliana; Page, David; Burnside, Elizabeth; Dutra, Inês

    2013-01-01

    In this work we build the first BI-RADS parser for Portuguese free texts, modeled after existing approaches to extract BI-RADS features from English medical records. Our concept finder uses a semantic grammar based on the BIRADS lexicon and on iterative transferred expert knowledge. We compare the performance of our algorithm to manual annotation by a specialist in mammography. Our results show that our parser’s performance is comparable to the manual method. PMID:23797461

  5. Eddy current pulsed phase thermography and feature extraction

    NASA Astrophysics Data System (ADS)

    He, Yunze; Tian, GuiYun; Pan, Mengchun; Chen, Dixiang

    2013-08-01

    This letter proposed an eddy current pulsed phase thermography technique combing eddy current excitation, infrared imaging, and phase analysis. One steel sample is selected as the material under test to avoid the influence of skin depth, which provides subsurface defects with different depths. The experimental results show that this proposed method can eliminate non-uniform heating and improve defect detectability. Several features are extracted from differential phase spectra and the preliminary linear relationships are built to measure these subsurface defects' depth.

  6. Dual-pass feature extraction on human vessel images.

    PubMed

    Hernandez, W; Grimm, S; Andriantsimiavona, R

    2014-06-01

    We present a novel algorithm for the extraction of cavity features on images of human vessels. Fat deposits in the inner wall of such structure introduce artifacts, and regions in the images captured invalidating the usual assumption of an elliptical model which makes the process of extracting the central passage effectively more difficult. Our approach was designed to cope with these challenges and extract the required image features in a fully automated, accurate, and efficient way using two stages: the first allows to determine a bounding segmentation mask to prevent major leakages from pixels of the cavity area by using a circular region fill that operates as a paint brush followed by Principal Component Analysis with auto correction; the second allows to extract a precise cavity enclosure using a micro-dilation filter and an edge-walking scheme. The accuracy of the algorithm has been tested using 30 computed tomography angiography scans of the lower part of the body containing different degrees of inner wall distortion. The results were compared to manual annotations from a specialist resulting in sensitivity around 98 %, false positive rate around 8 %, and positive predictive value around 93 %. The average execution time was 24 and 18 ms on two types of commodity hardware over sections of 15 cm of length (approx. 1 ms per contour) which makes it more than suitable for use in interactive software applications. Reproducibility tests were also carried out with synthetic images showing no variation for the computed diameters against the theoretical measure. PMID:24197278

  7. Chemical-induced disease relation extraction with various linguistic features

    PubMed Central

    Gu, Jinghang; Qian, Longhua; Zhou, Guodong

    2016-01-01

    Understanding the relations between chemicals and diseases is crucial in various biomedical tasks such as new drug discoveries and new therapy developments. While manually mining these relations from the biomedical literature is costly and time-consuming, such a procedure is often difficult to keep up-to-date. To address these issues, the BioCreative-V community proposed a challenging task of automatic extraction of chemical-induced disease (CID) relations in order to benefit biocuration. This article describes our work on the CID relation extraction task on the BioCreative-V tasks. We built a machine learning based system that utilized simple yet effective linguistic features to extract relations with maximum entropy models. In addition to leveraging various features, the hypernym relations between entity concepts derived from the Medical Subject Headings (MeSH)-controlled vocabulary were also employed during both training and testing stages to obtain more accurate classification models and better extraction performance, respectively. We demoted relation extraction between entities in documents to relation extraction between entity mentions. In our system, pairs of chemical and disease mentions at both intra- and inter-sentence levels were first constructed as relation instances for training and testing, then two classification models at both levels were trained from the training examples and applied to the testing examples. Finally, we merged the classification results from mention level to document level to acquire final relations between chemicals and diseases. Our system achieved promising F-scores of 60.4% on the development dataset and 58.3% on the test dataset using gold-standard entity annotations, respectively. Database URL: https://github.com/JHnlp/BC5CIDTask PMID:27052618

  8. Chemical-induced disease relation extraction with various linguistic features.

    PubMed

    Gu, Jinghang; Qian, Longhua; Zhou, Guodong

    2016-01-01

    Understanding the relations between chemicals and diseases is crucial in various biomedical tasks such as new drug discoveries and new therapy developments. While manually mining these relations from the biomedical literature is costly and time-consuming, such a procedure is often difficult to keep up-to-date. To address these issues, the BioCreative-V community proposed a challenging task of automatic extraction of chemical-induced disease (CID) relations in order to benefit biocuration. This article describes our work on the CID relation extraction task on the BioCreative-V tasks. We built a machine learning based system that utilized simple yet effective linguistic features to extract relations with maximum entropy models. In addition to leveraging various features, the hypernym relations between entity concepts derived from the Medical Subject Headings (MeSH)-controlled vocabulary were also employed during both training and testing stages to obtain more accurate classification models and better extraction performance, respectively. We demoted relation extraction between entities in documents to relation extraction between entity mentions. In our system, pairs of chemical and disease mentions at both intra- and inter-sentence levels were first constructed as relation instances for training and testing, then two classification models at both levels were trained from the training examples and applied to the testing examples. Finally, we merged the classification results from mention level to document level to acquire final relations between chemicals and diseases. Our system achieved promisingF-scores of 60.4% on the development dataset and 58.3% on the test dataset using gold-standard entity annotations, respectively. Database URL:https://github.com/JHnlp/BC5CIDTask. PMID:27052618

  9. A flexible data-driven comorbidity feature extraction framework.

    PubMed

    Sideris, Costas; Pourhomayoun, Mohammad; Kalantarian, Haik; Sarrafzadeh, Majid

    2016-06-01

    Disease and symptom diagnostic codes are a valuable resource for classifying and predicting patient outcomes. In this paper, we propose a novel methodology for utilizing disease diagnostic information in a predictive machine learning framework. Our methodology relies on a novel, clustering-based feature extraction framework using disease diagnostic information. To reduce the data dimensionality, we identify disease clusters using co-occurrence statistics. We optimize the number of generated clusters in the training set and then utilize these clusters as features to predict patient severity of condition and patient readmission risk. We build our clustering and feature extraction algorithm using the 2012 National Inpatient Sample (NIS), Healthcare Cost and Utilization Project (HCUP) which contains 7 million hospital discharge records and ICD-9-CM codes. The proposed framework is tested on Ronald Reagan UCLA Medical Center Electronic Health Records (EHR) from 3041 Congestive Heart Failure (CHF) patients and the UCI 130-US diabetes dataset that includes admissions from 69,980 diabetic patients. We compare our cluster-based feature set with the commonly used comorbidity frameworks including Charlson's index, Elixhauser's comorbidities and their variations. The proposed approach was shown to have significant gains between 10.7-22.1% in predictive accuracy for CHF severity of condition prediction and 4.65-5.75% in diabetes readmission prediction. PMID:27127895

  10. 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.

  11. Magnetic Field Feature Extraction and Selection for Indoor Location Estimation

    PubMed Central

    Galván-Tejada, Carlos E.; García-Vázquez, Juan Pablo; Brena, Ramon F.

    2014-01-01

    User indoor positioning has been under constant improvement especially with the availability of new sensors integrated into the modern mobile devices, which allows us to exploit not only infrastructures made for everyday use, such as WiFi, but also natural infrastructure, as is the case of natural magnetic field. In this paper we present an extension and improvement of our current indoor localization model based on the feature extraction of 46 magnetic field signal features. The extension adds a feature selection phase to our methodology, which is performed through Genetic Algorithm (GA) with the aim of optimizing the fitness of our current model. In addition, we present an evaluation of the final model in two different scenarios: home and office building. The results indicate that performing a feature selection process allows us to reduce the number of signal features of the model from 46 to 5 regardless the scenario and room location distribution. Further, we verified that reducing the number of features increases the probability of our estimator correctly detecting the user's location (sensitivity) and its capacity to detect false positives (specificity) in both scenarios. PMID:24955944

  12. Magnetic field feature extraction and selection for indoor location estimation.

    PubMed

    Galván-Tejada, Carlos E; García-Vázquez, Juan Pablo; Brena, Ramon F

    2014-01-01

    User indoor positioning has been under constant improvement especially with the availability of new sensors integrated into the modern mobile devices, which allows us to exploit not only infrastructures made for everyday use, such as WiFi, but also natural infrastructure, as is the case of natural magnetic field. In this paper we present an extension and improvement of our current indoor localization model based on the feature extraction of 46 magnetic field signal features. The extension adds a feature selection phase to our methodology, which is performed through Genetic Algorithm (GA) with the aim of optimizing the fitness of our current model. In addition, we present an evaluation of the final model in two different scenarios: home and office building. The results indicate that performing a feature selection process allows us to reduce the number of signal features of the model from 46 to 5 regardless the scenario and room location distribution. Further, we verified that reducing the number of features increases the probability of our estimator correctly detecting the user's location (sensitivity) and its capacity to detect false positives (specificity) in both scenarios. PMID:24955944

  13. Harnessing Satellite Imageries in Feature Extraction Using Google Earth Pro

    NASA Astrophysics Data System (ADS)

    Fernandez, Sim Joseph; Milano, Alan

    2016-07-01

    Climate change has been a long-time concern worldwide. Impending flooding, for one, is among its unwanted consequences. The Phil-LiDAR 1 project of the Department of Science and Technology (DOST), Republic of the Philippines, has developed an early warning system in regards to flood hazards. The project utilizes the use of remote sensing technologies in determining the lives in probable dire danger by mapping and attributing building features using LiDAR dataset and satellite imageries. A free mapping software named Google Earth Pro (GEP) is used to load these satellite imageries as base maps. Geotagging of building features has been done so far with the use of handheld Global Positioning System (GPS). Alternatively, mapping and attribution of building features using GEP saves a substantial amount of resources such as manpower, time and budget. Accuracy-wise, geotagging by GEP is dependent on either the satellite imageries or orthophotograph images of half-meter resolution obtained during LiDAR acquisition and not on the GPS of three-meter accuracy. The attributed building features are overlain to the flood hazard map of Phil-LiDAR 1 in order to determine the exposed population. The building features as obtained from satellite imageries may not only be used in flood exposure assessment but may also be used in assessing other hazards and a number of other uses. Several other features may also be extracted from the satellite imageries.

  14. Feature extraction algorithm for space targets based on fractal theory

    NASA Astrophysics Data System (ADS)

    Tian, Balin; Yuan, Jianping; Yue, Xiaokui; Ning, Xin

    2007-11-01

    In order to offer a potential for extending the life of satellites and reducing the launch and operating costs, satellite servicing including conducting repairs, upgrading and refueling spacecraft on-orbit become much more frequently. Future space operations can be more economically and reliably executed using machine vision systems, which can meet real time and tracking reliability requirements for image tracking of space surveillance system. Machine vision was applied to the research of relative pose for spacecrafts, the feature extraction algorithm was the basis of relative pose. In this paper fractal geometry based edge extraction algorithm which can be used in determining and tracking the relative pose of an observed satellite during proximity operations in machine vision system was presented. The method gets the gray-level image distributed by fractal dimension used the Differential Box-Counting (DBC) approach of the fractal theory to restrain the noise. After this, we detect the consecutive edge using Mathematical Morphology. The validity of the proposed method is examined by processing and analyzing images of space targets. The edge extraction method not only extracts the outline of the target, but also keeps the inner details. Meanwhile, edge extraction is only processed in moving area to reduce computation greatly. Simulation results compared edge detection using the method which presented by us with other detection methods. The results indicate that the presented algorithm is a valid method to solve the problems of relative pose for spacecrafts.

  15. The optimal extraction of feature algorithm based on KAZE

    NASA Astrophysics Data System (ADS)

    Yao, Zheyi; Gu, Guohua; Qian, Weixian; Wang, Pengcheng

    2015-10-01

    As a novel method of 2D features extraction algorithm over the nonlinear scale space, KAZE provide a special method. However, the computation of nonlinear scale space and the construction of KAZE feature vectors are more expensive than the SIFT and SURF significantly. In this paper, the given image is used to build the nonlinear space up to a maximum evolution time through the efficient Additive Operator Splitting (AOS) techniques and the variable conductance diffusion. Changing the parameter can improve the construction of nonlinear scale space and simplify the image conductivities for each dimension space, with the predigest computation. Then, the detection for points of interest can exhibit a maxima of the scale-normalized determinant with the Hessian response in the nonlinear scale space. At the same time, the detection of feature vectors is optimized by the Wavelet Transform method, which can avoid the second Gaussian smoothing in the KAZE Features and cut down the complexity of the algorithm distinctly in the building and describing vectors steps. In this way, the dominant orientation is obtained, similar to SURF, by summing the responses within a sliding circle segment covering an angle of π/3 in the circular area of radius 6σ with a sampling step of size σ one by one. Finally, the extraction in the multidimensional patch at the given scale, centered over the points of interest and rotated to align its dominant orientation to a canonical direction, is able to simplify the description of feature by reducing the description dimensions, just as the PCA-SIFT method. Even though the features are somewhat more expensive to compute than SIFT due to the construction of nonlinear scale space, but compared to SURF, the result revels a step forward in performance in detection, description and application against the previous ways by the following contrast experiments.

  16. 3-D crustal structure of the western United States: application of Rayleigh-wave ellipticity extracted from noise cross-correlations

    NASA Astrophysics Data System (ADS)

    Lin, Fan-Chi; Tsai, Victor C.; Schmandt, Brandon

    2014-08-01

    We present a new 3-D seismic model of the western United States crust derived from a joint inversion of Rayleigh-wave phase velocity and ellipticity measurements using periods from 8 to 100 s. Improved constraints on upper-crustal structure result from use of short-period Rayleigh-wave ellipticity, or Rayleigh-wave H/V (horizontal to vertical) amplitude ratios, measurements determined using multicomponent ambient noise cross-correlations. To retain the amplitude ratio information between vertical and horizontal components, for each station, we perform daily noise pre-processing (temporal normalization and spectrum whitening) simultaneously for all three components. For each station pair, amplitude measurements between cross-correlations of different components (radial-radial, radial-vertical, vertical-radial and vertical-vertical) are then used to determine the Rayleigh-wave H/V ratios at the two station locations. We use all EarthScope/USArray Tranportable Array data available between 2007 January and 2011 June to determine the Rayleigh-wave H/V ratios and their uncertainties at all station locations and construct new Rayleigh-wave H/V ratio maps in the western United States between periods of 8 and 24 s. Combined with previous longer period earthquake Rayleigh-wave H/V ratio measurements and Rayleigh-wave phase velocity measurements from both ambient noise and earthquakes, we invert for a new 3-D crustal and upper-mantle model in the western United States. Correlation between the inverted model and known geological features at all depths suggests good resolution in five crustal layers. Use of short-period Rayleigh-wave H/V ratio measurements based on noise cross-correlation enables resolution of distinct near surface features such as the Columbia River Basalt flows, which overlie a thick sedimentary basin.

  17. A new methodology in fast and accurate matching of the 2D and 3D point clouds extracted by laser scanner systems

    NASA Astrophysics Data System (ADS)

    Torabi, M.; Mousavi G., S. M.; Younesian, D.

    2015-03-01

    Registration of the point clouds is a conventional challenge in computer vision related applications. As an application, matching of train wheel profiles extracted from two viewpoints is studied in this paper. The registration problem is formulated into an optimization problem. An error minimization function for registration of the two partially overlapping point clouds is presented. The error function is defined as the sum of the squared distance between the source points and their corresponding pairs which should be minimized. The corresponding pairs are obtained thorough Iterative Closest Point (ICP) variants. Here, a point-to-plane ICP variant is employed. Principal Component Analysis (PCA) is used to obtain tangent planes. Thus it is shown that minimization of the proposed objective function diminishes point-to-plane ICP variant. We utilized this algorithm to register point clouds of two partially overlapping profiles of wheel train extracted from two viewpoints in 2D. Also, a number of synthetic point clouds and a number of real point clouds in 3D are studied to evaluate the reliability and rate of convergence in our method compared with other registration methods.

  18. Feature extraction from mammographic images using fast marching methods

    NASA Astrophysics Data System (ADS)

    Bottigli, U.; Golosio, B.

    2002-07-01

    Features extraction from medical images represents a fundamental step for shape recognition and diagnostic support. The present work faces the problem of the detection of large features, such as massive lesions and organ contours, from mammographic images. The regions of interest are often characterized by an average grayness intensity that is different from the surrounding. In most cases, however, the desired features cannot be extracted by simple gray level thresholding, because of image noise and non-uniform density of the surrounding tissue. In this work, edge detection is achieved through the fast marching method (Level Set Methods and Fast Marching Methods, Cambridge University Press, Cambridge, 1999), which is based on the theory of interface evolution. Starting from a seed point in the shape of interest, a front is generated which evolves according to an appropriate speed function. Such function is expressed in terms of geometric properties of the evolving interface and of image properties, and should become zero when the front reaches the desired boundary. Some examples of application of such method to mammographic images from the CALMA database (Nucl. Instr. and Meth. A 460 (2001) 107) are presented here and discussed.

  19. A multi-approach feature extractions for iris recognition

    NASA Astrophysics Data System (ADS)

    Sanpachai, H.; Settapong, M.

    2014-04-01

    Biometrics is a promising technique that is used to identify individual traits and characteristics. Iris recognition is one of the most reliable biometric methods. As iris texture and color is fully developed within a year of birth, it remains unchanged throughout a person's life. Contrary to fingerprint, which can be altered due to several aspects including accidental damage, dry or oily skin and dust. Although iris recognition has been studied for more than a decade, there are limited commercial products available due to its arduous requirement such as camera resolution, hardware size, expensive equipment and computational complexity. However, at the present time, technology has overcome these obstacles. Iris recognition can be done through several sequential steps which include pre-processing, features extractions, post-processing, and matching stage. In this paper, we adopted the directional high-low pass filter for feature extraction. A box-counting fractal dimension and Iris code have been proposed as feature representations. Our approach has been tested on CASIA Iris Image database and the results are considered successful.

  20. On the comparison of visual discomfort generated by S3D and 2D content based on eye-tracking features

    NASA Astrophysics Data System (ADS)

    Iatsun, Iana; Larabi, Mohamed-Chaker; Fernandez-Maloigne, Christine

    2014-03-01

    The changing of TV systems from 2D to 3D mode is the next expected step in the telecommunication world. Some works have already been done to perform this progress technically, but interaction of the third dimension with humans is not yet clear. Previously, it was found that any increased load of visual system can create visual fatigue, like prolonged TV watching, computer work or video gaming. But watching S3D can cause another nature of visual fatigue, since all S3D technologies creates illusion of the third dimension based on characteristics of binocular vision. In this work we propose to evaluate and compare the visual fatigue from watching 2D and S3D content. This work shows the difference in accumulation of visual fatigue and its assessment for two types of content. In order to perform this comparison eye-tracking experiments using six commercially available movies were conducted. Healthy naive participants took part into the test and gave their answers feeling the subjective evaluation. It was found that watching stereo 3D content induce stronger feeling of visual fatigue than conventional 2D, and the nature of video has an important effect on its increase. Visual characteristics obtained by using eye-tracking were investigated regarding their relation with visual fatigue.

  1. Linear unmixing of hyperspectral signals via wavelet feature extraction

    NASA Astrophysics Data System (ADS)

    Li, Jiang

    A pixel in remotely sensed hyperspectral imagery is typically a mixture of multiple electromagnetic radiances from various ground cover materials. Spectral unmixing is a quantitative analysis procedure used to recognize constituent ground cover materials (or endmembers) and obtain their mixing proportions (or abundances) from a mixed pixel. The abundances are typically estimated using the least squares estimation (LSE) method based on the linear mixture model (LMM). This dissertation provides a complete investigation on how the use of appropriate features can improve the LSE of endmember abundances using remotely sensed hyperspectral signals. The dissertation shows how features based on signal classification approaches, such as discrete wavelet transform (DWT), outperform features based on conventional signal representation methods for dimensionality reduction, such as principal component analysis (PCA), for the LSE of endmember abundances. Both experimental and theoretical analyses are reported in the dissertation. A DWT-based linear unmixing system is designed specially for the abundance estimation. The system utilizes the DWT as a pre-processing step for the feature extraction. Based on DWT-based features, the system utilizes the constrained LSE for the abundance estimation. Experimental results show that the use of DWT-based features reduces the abundance estimation deviation by 30--50% on average, as compared to the use of original hyperspectral signals or conventional PCA-based features. Based on the LMM and the LSE method, a series of theoretical analyses are derived to reveal the fundamental reasons why the use of the appropriate features, such as DWT-based features, can improve the LSE of endmember abundances. Under reasonable assumptions, the dissertation derives a generalized mathematical relationship between the abundance estimation error and the endmember separabilty. It is proven that the abundance estimation error can be reduced through increasing

  2. [Feature extraction for breast cancer data based on geometric algebra theory and feature selection using differential evolution].

    PubMed

    Li, Jing; Hong, Wenxue

    2014-12-01

    The feature extraction and feature selection are the important issues in pattern recognition. Based on the geometric algebra representation of vector, a new feature extraction method using blade coefficient of geometric algebra was proposed in this study. At the same time, an improved differential evolution (DE) feature selection method was proposed to solve the elevated high dimension issue. The simple linear discriminant analysis was used as the classifier. The result of the 10-fold cross-validation (10 CV) classification of public breast cancer biomedical dataset was more than 96% and proved superior to that of the original features and traditional feature extraction method. PMID:25868233

  3. Opinion mining feature-level using Naive Bayes and feature extraction based analysis dependencies

    NASA Astrophysics Data System (ADS)

    Sanda, Regi; Baizal, Z. K. Abdurahman; Nhita, Fhira

    2015-12-01

    Development of internet and technology, has major impact and providing new business called e-commerce. Many e-commerce sites that provide convenience in transaction, and consumers can also provide reviews or opinions on products that purchased. These opinions can be used by consumers and producers. Consumers to know the advantages and disadvantages of particular feature of the product. Procuders can analyse own strengths and weaknesses as well as it's competitors products. Many opinions need a method that the reader can know the point of whole opinion. The idea emerged from review summarization that summarizes the overall opinion based on sentiment and features contain. In this study, the domain that become the main focus is about the digital camera. This research consisted of four steps 1) giving the knowledge to the system to recognize the semantic orientation of an opinion 2) indentify the features of product 3) indentify whether the opinion gives a positive or negative 4) summarizing the result. In this research discussed the methods such as Naï;ve Bayes for sentiment classification, and feature extraction algorithm based on Dependencies Analysis, which is one of the tools in Natural Language Processing (NLP) and knowledge based dictionary which is useful for handling implicit features. The end result of research is a summary that contains a bunch of reviews from consumers on the features and sentiment. With proposed method, accuration for sentiment classification giving 81.2 % for positive test data, 80.2 % for negative test data, and accuration for feature extraction reach 90.3 %.

  4. Extract relevant features from DEM for groundwater potential mapping

    NASA Astrophysics Data System (ADS)

    Liu, T.; Yan, H.; Zhai, L.

    2015-06-01

    Multi-criteria evaluation (MCE) method has been applied much in groundwater potential mapping researches. But when to data scarce areas, it will encounter lots of problems due to limited data. Digital Elevation Model (DEM) is the digital representations of the topography, and has many applications in various fields. Former researches had been approved that much information concerned to groundwater potential mapping (such as geological features, terrain features, hydrology features, etc.) can be extracted from DEM data. This made using DEM data for groundwater potential mapping is feasible. In this research, one of the most widely used and also easy to access data in GIS, DEM data was used to extract information for groundwater potential mapping in batter river basin in Alberta, Canada. First five determining factors for potential ground water mapping were put forward based on previous studies (lineaments and lineament density, drainage networks and its density, topographic wetness index (TWI), relief and convergence Index (CI)). Extraction methods of the five determining factors from DEM were put forward and thematic maps were produced accordingly. Cumulative effects matrix was used for weight assignment, a multi-criteria evaluation process was carried out by ArcGIS software to delineate the potential groundwater map. The final groundwater potential map was divided into five categories, viz., non-potential, poor, moderate, good, and excellent zones. Eventually, the success rate curve was drawn and the area under curve (AUC) was figured out for validation. Validation result showed that the success rate of the model was 79% and approved the method's feasibility. The method afforded a new way for researches on groundwater management in areas suffers from data scarcity, and also broaden the application area of DEM data.

  5. Feature Extraction and Analysis of Breast Cancer Specimen

    NASA Astrophysics Data System (ADS)

    Bhattacharyya, Debnath; Robles, Rosslin John; Kim, Tai-Hoon; Bandyopadhyay, Samir Kumar

    In this paper, we propose a method to identify abnormal growth of cells in breast tissue and suggest further pathological test, if necessary. We compare normal breast tissue with malignant invasive breast tissue by a series of image processing steps. Normal ductal epithelial cells and ductal / lobular invasive carcinogenic cells also consider for comparison here in this paper. In fact, features of cancerous breast tissue (invasive) are extracted and analyses with normal breast tissue. We also suggest the breast cancer recognition technique through image processing and prevention by controlling p53 gene mutation to some greater extent.

  6. Cepstrum based feature extraction method for fungus detection

    NASA Astrophysics Data System (ADS)

    Yorulmaz, Onur; Pearson, Tom C.; Çetin, A. Enis

    2011-06-01

    In this paper, a method for detection of popcorn kernels infected by a fungus is developed using image processing. The method is based on two dimensional (2D) mel and Mellin-cepstrum computation from popcorn kernel images. Cepstral features that were extracted from popcorn images are classified using Support Vector Machines (SVM). Experimental results show that high recognition rates of up to 93.93% can be achieved for both damaged and healthy popcorn kernels using 2D mel-cepstrum. The success rate for healthy popcorn kernels was found to be 97.41% and the recognition rate for damaged kernels was found to be 89.43%.

  7. Feature extraction and dimensionality reduction for mass spectrometry data.

    PubMed

    Liu, Yihui

    2009-09-01

    Mass spectrometry is being used to generate protein profiles from human serum, and proteomic data obtained from mass spectrometry have attracted great interest for the detection of early stage cancer. However, high dimensional mass spectrometry data cause considerable challenges. In this paper we propose a feature extraction algorithm based on wavelet analysis for high dimensional mass spectrometry data. A set of wavelet detail coefficients at different scale is used to detect the transient changes of mass spectrometry data. The experiments are performed on 2 datasets. A highly competitive accuracy, compared with the best performance of other kinds of classification models, is achieved. Experimental results show that the wavelet detail coefficients are efficient way to characterize features of high dimensional mass spectra and reduce the dimensionality of high dimensional mass spectra. PMID:19646687

  8. Road marking features extraction using the VIAPIX® system

    NASA Astrophysics Data System (ADS)

    Kaddah, W.; Ouerhani, Y.; Alfalou, A.; Desthieux, M.; Brosseau, C.; Gutierrez, C.

    2016-07-01

    Precise extraction of road marking features is a critical task for autonomous urban driving, augmented driver assistance, and robotics technologies. In this study, we consider an autonomous system allowing us lane detection for marked urban roads and analysis of their features. The task is to relate the georeferencing of road markings from images obtained using the VIAPIX® system. Based on inverse perspective mapping and color segmentation to detect all white objects existing on this road, the present algorithm enables us to examine these images automatically and rapidly and also to get information on road marks, their surface conditions, and their georeferencing. This algorithm allows detecting all road markings and identifying some of them by making use of a phase-only correlation filter (POF). We illustrate this algorithm and its robustness by applying it to a variety of relevant scenarios.

  9. Texture Feature Extraction and Classification for Iris Diagnosis

    NASA Astrophysics Data System (ADS)

    Ma, Lin; Li, Naimin

    Appling computer aided techniques in iris image processing, and combining occidental iridology with the traditional Chinese medicine is a challenging research area in digital image processing and artificial intelligence. This paper proposes an iridology model that consists the iris image pre-processing, texture feature analysis and disease classification. To the pre-processing, a 2-step iris localization approach is proposed; a 2-D Gabor filter based texture analysis and a texture fractal dimension estimation method are proposed for pathological feature extraction; and at last support vector machines are constructed to recognize 2 typical diseases such as the alimentary canal disease and the nerve system disease. Experimental results show that the proposed iridology diagnosis model is quite effective and promising for medical diagnosis and health surveillance for both hospital and public use.

  10. Wavelet based feature extraction and visualization in hyperspectral tissue characterization

    PubMed Central

    Denstedt, Martin; Bjorgan, Asgeir; Milanič, Matija; Randeberg, Lise Lyngsnes

    2014-01-01

    Hyperspectral images of tissue contain extensive and complex information relevant for clinical applications. In this work, wavelet decomposition is explored for feature extraction from such data. Wavelet methods are simple and computationally effective, and can be implemented in real-time. The aim of this study was to correlate results from wavelet decomposition in the spectral domain with physical parameters (tissue oxygenation, blood and melanin content). Wavelet decomposition was tested on Monte Carlo simulations, measurements of a tissue phantom and hyperspectral data from a human volunteer during an occlusion experiment. Reflectance spectra were decomposed, and the coefficients were correlated to tissue parameters. This approach was used to identify wavelet components that can be utilized to map levels of blood, melanin and oxygen saturation. The results show a significant correlation (p <0.02) between the chosen tissue parameters and the selected wavelet components. The tissue parameters could be mapped using a subset of the calculated components due to redundancy in spectral information. Vessel structures are well visualized. Wavelet analysis appears as a promising tool for extraction of spectral features in skin. Future studies will aim at developing quantitative mapping of optical properties based on wavelet decomposition. PMID:25574437

  11. Detailed hydrographic feature extraction from high-resolution LIDAR data

    NASA Astrophysics Data System (ADS)

    Anderson, Danny L.

    Detailed hydrographic feature extraction from high-resolution light detection and ranging (LiDAR) data is investigated. Methods for quantitatively evaluating and comparing such extractions are presented, including the use of sinuosity and longitudinal root-mean-square-error (LRMSE). These metrics are then used to quantitatively compare stream networks in two studies. The first study examines the effect of raster cell size on watershed boundaries and stream networks delineated from LiDAR-derived digital elevation models (DEMs). The study confirmed that, with the greatly increased resolution of LiDAR data, smaller cell sizes generally yielded better stream network delineations, based on sinuosity and LRMSE. The second study demonstrates a new method of delineating a stream directly from LiDAR point clouds, without the intermediate step of deriving a DEM. Direct use of LiDAR point clouds could improve efficiency and accuracy of hydrographic feature extractions. The direct delineation method developed herein and termed "mDn", is an extension of the D8 method that has been used for several decades with gridded raster data. The method divides the region around a starting point into sectors, using the LiDAR data points within each sector to determine an average slope, and selecting the sector with the greatest downward slope to determine the direction of flow. An mDn delineation was compared with a traditional grid-based delineation, using TauDEM, and other readily available, common stream data sets. Although, the TauDEM delineation yielded a sinuosity that more closely matches the reference, the mDn delineation yielded a sinuosity that was higher than either the TauDEM method or the existing published stream delineations. Furthermore, stream delineation using the mD n method yielded the smallest LRMSE.

  12. Automated extraction of aorta and pulmonary artery in mediastinum from 3D chest x-ray CT images without contrast medium

    NASA Astrophysics Data System (ADS)

    Kitasaka, Takayuki; Mori, Kensaku; Hasegawa, Jun-ichi; Toriwaki, Jun-ichiro; Katada, Kazuhiro

    2002-05-01

    This paper proposes a method for automated extraction of the aorta and pulmonary artery (PA) in the mediastinum of the chest from uncontrasted chest X-ray CT images. The proposed method employs a model fitting technique to use shape features of blood vessels for extraction. First, edge voxels are detected based on the standard deviation of CT values. A likelihood image, which shows the degree of likelihood on medial axes of vessels, are calculated by applying the Euclidean distance transformation to non-edge voxels. Second, the medial axis of each vessel is obtained by fitting the model. This is done by referring the likelihood image. Finally, the aorta and PA areas are recovered from the medial axes by executing the reverse Euclidean distance transformation. We applied the proposed method to seven cases of uncontrasted chest X-ray CT images and evaluated the results by calculating the coincidence index computed from the extracted regions and the regions manually traced. Experimental results showed that the extracted aorta and the PA areas coincides with manually input regions with the coincidence indexes values 90% and 80-90%,respectively.

  13. Deep PDF parsing to extract features for detecting embedded malware.

    SciTech Connect

    Munson, Miles Arthur; Cross, Jesse S.

    2011-09-01

    The number of PDF files with embedded malicious code has risen significantly in the past few years. This is due to the portability of the file format, the ways Adobe Reader recovers from corrupt PDF files, the addition of many multimedia and scripting extensions to the file format, and many format properties the malware author may use to disguise the presence of malware. Current research focuses on executable, MS Office, and HTML formats. In this paper, several features and properties of PDF Files are identified. Features are extracted using an instrumented open source PDF viewer. The feature descriptions of benign and malicious PDFs can be used to construct a machine learning model for detecting possible malware in future PDF files. The detection rate of PDF malware by current antivirus software is very low. A PDF file is easy to edit and manipulate because it is a text format, providing a low barrier to malware authors. Analyzing PDF files for malware is nonetheless difficult because of (a) the complexity of the formatting language, (b) the parsing idiosyncrasies in Adobe Reader, and (c) undocumented correction techniques employed in Adobe Reader. In May 2011, Esparza demonstrated that PDF malware could be hidden from 42 of 43 antivirus packages by combining multiple obfuscation techniques [4]. One reason current antivirus software fails is the ease of varying byte sequences in PDF malware, thereby rendering conventional signature-based virus detection useless. The compression and encryption functions produce sequences of bytes that are each functions of multiple input bytes. As a result, padding the malware payload with some whitespace before compression/encryption can change many of the bytes in the final payload. In this study we analyzed a corpus of 2591 benign and 87 malicious PDF files. While this corpus is admittedly small, it allowed us to test a system for collecting indicators of embedded PDF malware. We will call these indicators features throughout

  14. Extraction of Surface-Related Features in a Recurrent Model of V1-V2 Interactions

    PubMed Central

    Weidenbacher, Ulrich; Neumann, Heiko

    2009-01-01

    Background Humans can effortlessly segment surfaces and objects from two-dimensional (2D) images that are projections of the 3D world. The projection from 3D to 2D leads partially to occlusions of surfaces depending on their position in depth and on viewpoint. One way for the human visual system to infer monocular depth cues could be to extract and interpret occlusions. It has been suggested that the perception of contour junctions, in particular T-junctions, may be used as cue for occlusion of opaque surfaces. Furthermore, X-junctions could be used to signal occlusion of transparent surfaces. Methodology/Principal Findings In this contribution, we propose a neural model that suggests how surface-related cues for occlusion can be extracted from a 2D luminance image. The approach is based on feedforward and feedback mechanisms found in visual cortical areas V1 and V2. In a first step, contours are completed over time by generating groupings of like-oriented contrasts. Few iterations of feedforward and feedback processing lead to a stable representation of completed contours and at the same time to a suppression of image noise. In a second step, contour junctions are localized and read out from the distributed representation of boundary groupings. Moreover, surface-related junctions are made explicit such that they are evaluated to interact as to generate surface-segmentations in static images. In addition, we compare our extracted junction signals with a standard computer vision approach for junction detection to demonstrate that our approach outperforms simple feedforward computation-based approaches. Conclusions/Significance A model is proposed that uses feedforward and feedback mechanisms to combine contextually relevant features in order to generate consistent boundary groupings of surfaces. Perceptually important junction configurations are robustly extracted from neural representations to signal cues for occlusion and transparency. Unlike previous proposals

  15. Europeana and 3D

    NASA Astrophysics Data System (ADS)

    Pletinckx, D.

    2011-09-01

    The current 3D hype creates a lot of interest in 3D. People go to 3D movies, but are we ready to use 3D in our homes, in our offices, in our communication? Are we ready to deliver real 3D to a general public and use interactive 3D in a meaningful way to enjoy, learn, communicate? The CARARE project is realising this for the moment in the domain of monuments and archaeology, so that real 3D of archaeological sites and European monuments will be available to the general public by 2012. There are several aspects to this endeavour. First of all is the technical aspect of flawlessly delivering 3D content over all platforms and operating systems, without installing software. We have currently a working solution in PDF, but HTML5 will probably be the future. Secondly, there is still little knowledge on how to create 3D learning objects, 3D tourist information or 3D scholarly communication. We are still in a prototype phase when it comes to integrate 3D objects in physical or virtual museums. Nevertheless, Europeana has a tremendous potential as a multi-facetted virtual museum. Finally, 3D has a large potential to act as a hub of information, linking to related 2D imagery, texts, video, sound. We describe how to create such rich, explorable 3D objects that can be used intuitively by the generic Europeana user and what metadata is needed to support the semantic linking.

  16. Segmentation-based filtering and object-based feature extraction from airborne LiDAR point cloud data

    NASA Astrophysics Data System (ADS)

    Chang, Jie

    Three dimensional (3D) information about ground and above-ground features such as buildings and trees is important for many urban and environmental applications. Recent developments in Light Detection And Ranging (LiDAR) technology provide promising alternatives to conventional techniques for acquiring such information. The focus of this dissertation research is to effectively and efficiently filter massive airborne LiDAR point cloud data and to extract main above-ground features such as buildings and trees in the urban area. A novel segmentation algorithm for point cloud data, namely the 3D k mutual nearest neighborhood (kMNN) segmentation algorithm, was developed based on the improvement to the kMNN clustering algorithm by employing distances in 3D space to define mutual nearest neighborhoods. A set of optimization strategies, including dividing dataset into multiple blocks and small size grids, and using distance thresholds in x and y, were implemented to improve the efficiency of the segmentation algorithm. A segmentation based filtering method was then employed to filter the generated segments, which first generates segment boundaries using Voronoi polygon and dissolving operations, and then labels the segments as ground and above-ground based on their size and relative heights to the surrounding segments. An object-based feature extraction approach was also devised to extract buildings and trees from the above-ground segments based on object-level statistics derived, which were subject to a rule based classification system developed by either human experts or an inductive machine-learning algorithm. Case studies were conducted with four different LiDAR datasets to evaluate the effectiveness and efficiency of the proposed approaches. The proposed segmentation algorithm proved to be not only effective in separating ground and above-ground measurements into different segments, but also efficient in processing large datasets. The segmentation based filtering and

  17. PLOT3D/AMES, APOLLO UNIX VERSION USING GMR3D (WITH TURB3D)

    NASA Technical Reports Server (NTRS)

    Buning, P.

    1994-01-01

    PLOT3D is an interactive graphics program designed to help scientists visualize computational fluid dynamics (CFD) grids and solutions. Today, supercomputers and CFD algorithms can provide scientists with simulations of such highly complex phenomena that obtaining an understanding of the simulations has become a major problem. Tools which help the scientist visualize the simulations can be of tremendous aid. PLOT3D/AMES offers more functions and features, and has been adapted for more types of computers than any other CFD graphics program. Version 3.6b+ is supported for five computers and graphic libraries. Using PLOT3D, CFD physicists can view their computational models from any angle, observing the physics of problems and the quality of solutions. As an aid in designing aircraft, for example, PLOT3D's interactive computer graphics can show vortices, temperature, reverse flow, pressure, and dozens of other characteristics of air flow during flight. As critical areas become obvious, they can easily be studied more closely using a finer grid. PLOT3D is part of a computational fluid dynamics software cycle. First, a program such as 3DGRAPE (ARC-12620) helps the scientist generate computational grids to model an object and its surrounding space. Once the grids have been designed and parameters such as the angle of attack, Mach number, and Reynolds number have been specified, a "flow-solver" program such as INS3D (ARC-11794 or COS-10019) solves the system of equations governing fluid flow, usually on a supercomputer. Grids sometimes have as many as two million points, and the "flow-solver" produces a solution file which contains density, x- y- and z-momentum, and stagnation energy for each grid point. With such a solution file and a grid file containing up to 50 grids as input, PLOT3D can calculate and graphically display any one of 74 functions, including shock waves, surface pressure, velocity vectors, and particle traces. PLOT3D's 74 functions are organized into

  18. PLOT3D/AMES, APOLLO UNIX VERSION USING GMR3D (WITHOUT TURB3D)

    NASA Technical Reports Server (NTRS)

    Buning, P.

    1994-01-01

    PLOT3D is an interactive graphics program designed to help scientists visualize computational fluid dynamics (CFD) grids and solutions. Today, supercomputers and CFD algorithms can provide scientists with simulations of such highly complex phenomena that obtaining an understanding of the simulations has become a major problem. Tools which help the scientist visualize the simulations can be of tremendous aid. PLOT3D/AMES offers more functions and features, and has been adapted for more types of computers than any other CFD graphics program. Version 3.6b+ is supported for five computers and graphic libraries. Using PLOT3D, CFD physicists can view their computational models from any angle, observing the physics of problems and the quality of solutions. As an aid in designing aircraft, for example, PLOT3D's interactive computer graphics can show vortices, temperature, reverse flow, pressure, and dozens of other characteristics of air flow during flight. As critical areas become obvious, they can easily be studied more closely using a finer grid. PLOT3D is part of a computational fluid dynamics software cycle. First, a program such as 3DGRAPE (ARC-12620) helps the scientist generate computational grids to model an object and its surrounding space. Once the grids have been designed and parameters such as the angle of attack, Mach number, and Reynolds number have been specified, a "flow-solver" program such as INS3D (ARC-11794 or COS-10019) solves the system of equations governing fluid flow, usually on a supercomputer. Grids sometimes have as many as two million points, and the "flow-solver" produces a solution file which contains density, x- y- and z-momentum, and stagnation energy for each grid point. With such a solution file and a grid file containing up to 50 grids as input, PLOT3D can calculate and graphically display any one of 74 functions, including shock waves, surface pressure, velocity vectors, and particle traces. PLOT3D's 74 functions are organized into

  19. Automatic feature extraction from micrographs of forged superalloys

    NASA Astrophysics Data System (ADS)

    Berhuber, E.; Rinnhofer, A.; Stockinger, M.; Benesova, W.; Jakob, G.

    2008-07-01

    The manual determination of metallurgical parameters of forged superalloys can be dramatically improved by automatic, image-processing-based feature extraction. With the proposed methods, the typical errors during grain size estimation for Inconel 718 and Allvac 718Plus ™ , caused by twins and other artifacts like scratches, can be eliminated. Different processing strategies for grain size estimation allow the application of a wide range of ASTM grain size numbers from G3 to G12 with the typical variations in the manifestation of metallurgical details and the magnification-related limitations of image quality. Intercept counting strategies show advantages for samples with pronounced anisotropy and can produce detailed statistics on grain orientation. In addition to a single grain size number, grain size histograms offer a more precise description of the material properties.

  20. Unassisted 3D camera calibration

    NASA Astrophysics Data System (ADS)

    Atanassov, Kalin; Ramachandra, Vikas; Nash, James; Goma, Sergio R.

    2012-03-01

    With the rapid growth of 3D technology, 3D image capture has become a critical part of the 3D feature set on mobile phones. 3D image quality is affected by the scene geometry as well as on-the-device processing. An automatic 3D system usually assumes known camera poses accomplished by factory calibration using a special chart. In real life settings, pose parameters estimated by factory calibration can be negatively impacted by movements of the lens barrel due to shaking, focusing, or camera drop. If any of these factors displaces the optical axes of either or both cameras, vertical disparity might exceed the maximum tolerable margin and the 3D user may experience eye strain or headaches. To make 3D capture more practical, one needs to consider unassisted (on arbitrary scenes) calibration. In this paper, we propose an algorithm that relies on detection and matching of keypoints between left and right images. Frames containing erroneous matches, along with frames with insufficiently rich keypoint constellations, are detected and discarded. Roll, pitch yaw , and scale differences between left and right frames are then estimated. The algorithm performance is evaluated in terms of the remaining vertical disparity as compared to the maximum tolerable vertical disparity.

  1. Crown Features Extraction from Low Altitude AVIRIS Data

    NASA Astrophysics Data System (ADS)

    Ogunjemiyo, S. O.; Roberts, D.; Ustin, S.

    2005-12-01

    Automated tree recognition and crown delineations are computer-assisted procedures for identifying individual trees and segmenting their crown boundaries on digital imagery. The success of the procedures is dependent on the quality of the image data and the physiognomy of the stand as evidence by previous studies, which have all used data with spatial resolution less than 1 m and average crown diameter to pixel size ratio greater than 4. In this study we explored the prospect of identifying individual tree species and extracting crown features from low altitude AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) data with spatial resolution of 4 m. The test site is a Douglas-fir and Western hemlock dominated old-growth conifer forest in the Pacific Northwest with average crown diameter of 12 m, which translates to a crown diameter pixel ratio less than 4 m; the lowest value ever used in similar studies. The analysis was carried out using AVIRIS reflectance imagery in the NIR band centered at 885 nm wavelength. The analysis required spatial filtering of the reflectance imagery followed by application of a tree identification algorithm based on maximum filter technique. For every identified tree location a crown polygon was delineated by applying crown segmentation algorithm. Each polygon boundary was characterized by a loop connecting pixels that were geometrically determined to define the crown boundary. Crown features were extracted based on the area covered by the polygons, and they include crown diameters, average distance between crowns, species spectral, pixel brightness at the identified tree locations, average brightness of pixels enclosed by the crown boundary and within crown variation in pixel brightness. Comparison of the results with ground reference data showed a high correlation between the two datasets and highlights the potential of low altitude AVIRIS data to provide the means to improve forest management and practices and estimates of critical

  2. A Study of Feature Extraction Using Divergence Analysis of Texture Features

    NASA Technical Reports Server (NTRS)

    Hallada, W. A.; Bly, B. G.; Boyd, R. K.; Cox, S.

    1982-01-01

    An empirical study of texture analysis for feature extraction and classification of high spatial resolution remotely sensed imagery (10 meters) is presented in terms of specific land cover types. The principal method examined is the use of spatial gray tone dependence (SGTD). The SGTD method reduces the gray levels within a moving window into a two-dimensional spatial gray tone dependence matrix which can be interpreted as a probability matrix of gray tone pairs. Haralick et al (1973) used a number of information theory measures to extract texture features from these matrices, including angular second moment (inertia), correlation, entropy, homogeneity, and energy. The derivation of the SGTD matrix is a function of: (1) the number of gray tones in an image; (2) the angle along which the frequency of SGTD is calculated; (3) the size of the moving window; and (4) the distance between gray tone pairs. The first three parameters were varied and tested on a 10 meter resolution panchromatic image of Maryville, Tennessee using the five SGTD measures. A transformed divergence measure was used to determine the statistical separability between four land cover categories forest, new residential, old residential, and industrial for each variation in texture parameters.

  3. STATISTICAL BASED NON-LINEAR MODEL UPDATING USING FEATURE EXTRACTION

    SciTech Connect

    Schultz, J.F.; Hemez, F.M.

    2000-10-01

    This research presents a new method to improve analytical model fidelity for non-linear systems. The approach investigates several mechanisms to assist the analyst in updating an analytical model based on experimental data and statistical analysis of parameter effects. The first is a new approach at data reduction called feature extraction. This is an expansion of the update metrics to include specific phenomena or character of the response that is critical to model application. This is an extension of the classical linear updating paradigm of utilizing the eigen-parameters or FRFs to include such devices as peak acceleration, time of arrival or standard deviation of model error. The next expansion of the updating process is the inclusion of statistical based parameter analysis to quantify the effects of uncertain or significant effect parameters in the construction of a meta-model. This provides indicators of the statistical variation associated with parameters as well as confidence intervals on the coefficients of the resulting meta-model, Also included in this method is the investigation of linear parameter effect screening using a partial factorial variable array for simulation. This is intended to aid the analyst in eliminating from the investigation the parameters that do not have a significant variation effect on the feature metric, Finally an investigation of the model to replicate the measured response variation is examined.

  4. Evolving spatio-spectral feature extraction algorithms for hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Brumby, Steven P.; Galbraith, Amy E.

    2002-11-01

    Hyperspectral imagery data sets present an interesting challenge to feature extraction algorithm developers. Beyond the immediate problem of dealing with the sheer amount of spectral information per pixel in a hyperspectral image, the remote sensing scientist must explore a complex algorithm space in which both spatial and spectral signatures may be required to identify a feature of interest. Rather than carry out this algorithm exploration by hand, we are interested in developing learning systems that can evolve these algorithms. We describe a genetic programming/supervised classifier software system, called GENIE, which evolves image processing tools for remotely sensed imagery. Our primary application has been land-cover classification from satellite imagery. GENIE was developed to evolve classification algorithms for multispectral imagery, and the extension to hyperspectral imagery presents a chance to test a genetic programming system by greatly increasing the complexity of the data under analysis, as well as a chance to find interesting spatio-spectral algorithms for hyperspectral imagery. We demonstrate our system on publicly available imagery from the new Hyperion imaging spectrometer onboard the NASA Earth Observing-1 (EO-1) satellite.

  5. Pomegranate peel and peel extracts: chemistry and food features.

    PubMed

    Akhtar, Saeed; Ismail, Tariq; Fraternale, Daniele; Sestili, Piero

    2015-05-01

    The present review focuses on the nutritional, functional and anti-infective properties of pomegranate (Punica granatum L.) peel (PoP) and peel extract (PoPx) and on their applications as food additives, functional food ingredients or biologically active components in nutraceutical preparations. Due to their well-known ethnomedical relevance and chemical features, the biomolecules available in PoP and PoPx have been proposed, for instance, as substitutes of synthetic food additives, as nutraceuticals and chemopreventive agents. However, because of their astringency and anti-nutritional properties, PoP and PoPx are not yet considered as ingredients of choice in food systems. Indeed, considering the prospects related to both their health promoting activity and chemical features, the nutritional and nutraceutical potential of PoP and PoPx seems to be still underestimated. The present review meticulously covers the wide range of actual and possible applications (food preservatives, stabilizers, supplements, prebiotics and quality enhancers) of PoP and PoPx components in various food products. Given the overall properties of PoP and PoPx, further investigations in toxicological and sensory aspects of PoP and PoPx should be encouraged to fully exploit the health promoting and technical/economic potential of these waste materials as food supplements. PMID:25529700

  6. Extraction of Molecular Features through Exome to Transcriptome Alignment.

    PubMed

    Mudvari, Prakriti; Kowsari, Kamran; Cole, Charles; Mazumder, Raja; Horvath, Anelia

    2013-08-22

    Integrative Next Generation Sequencing (NGS) DNA and RNA analyses have very recently become feasible, and the published to date studies have discovered critical disease implicated pathways, and diagnostic and therapeutic targets. A growing number of exomes, genomes and transcriptomes from the same individual are quickly accumulating, providing unique venues for mechanistic and regulatory features analysis, and, at the same time, requiring new exploration strategies. In this study, we have integrated variation and expression information of four NGS datasets from the same individual: normal and tumor breast exomes and transcriptomes. Focusing on SNPcentered variant allelic prevalence, we illustrate analytical algorithms that can be applied to extract or validate potential regulatory elements, such as expression or growth advantage, imprinting, loss of heterozygosity (LOH), somatic changes, and RNA editing. In addition, we point to some critical elements that might bias the output and recommend alternative measures to maximize the confidence of findings. The need for such strategies is especially recognized within the growing appreciation of the concept of systems biology: integrative exploration of genome and transcriptome features reveal mechanistic and regulatory insights that reach far beyond linear addition of the individual datasets. PMID:24791251

  7. Extraction of Molecular Features through Exome to Transcriptome Alignment

    PubMed Central

    Mudvari, Prakriti; Kowsari, Kamran; Cole, Charles; Mazumder, Raja; Horvath, Anelia

    2014-01-01

    Integrative Next Generation Sequencing (NGS) DNA and RNA analyses have very recently become feasible, and the published to date studies have discovered critical disease implicated pathways, and diagnostic and therapeutic targets. A growing number of exomes, genomes and transcriptomes from the same individual are quickly accumulating, providing unique venues for mechanistic and regulatory features analysis, and, at the same time, requiring new exploration strategies. In this study, we have integrated variation and expression information of four NGS datasets from the same individual: normal and tumor breast exomes and transcriptomes. Focusing on SNPcentered variant allelic prevalence, we illustrate analytical algorithms that can be applied to extract or validate potential regulatory elements, such as expression or growth advantage, imprinting, loss of heterozygosity (LOH), somatic changes, and RNA editing. In addition, we point to some critical elements that might bias the output and recommend alternative measures to maximize the confidence of findings. The need for such strategies is especially recognized within the growing appreciation of the concept of systems biology: integrative exploration of genome and transcriptome features reveal mechanistic and regulatory insights that reach far beyond linear addition of the individual datasets. PMID:24791251

  8. Fingerprint data acquisition, desmearing, wavelet feature extraction, and identification

    NASA Astrophysics Data System (ADS)

    Szu, Harold H.; Hsu, Charles C.; Garcia, Joseph P.; Telfer, Brian A.

    1995-04-01

    In this paper, we present (1) a design concept of a fingerprint scanning system that can reject severely blurred inputs for retakes and then de-smear those less blurred prints. The de-smear algorithm is new and is based on the digital filter theory of the lossless QMF (quadrature mirror filter) subband coding. Then, we present (2) a new fingerprint minutia feature extraction methodology which uses a 2D STAR mother wavelet that can efficiently locate the fork feature anywhere on the fingerprints in parallel and is independent of its scale, shift, and rotation. Such a combined system can achieve high data compression to send through a binary facsimile machine that when combined with a tabletop computer can achieve the automatic finger identification systems (AFIS) using today's technology in the office environment. An interim recommendation for the National Crime Information Center is given about how to reduce the crime rate by an upgrade of today's police office technology in the light of the military expertise in ATR.

  9. Identification of the Structural Features of Guanine Derivatives as MGMT Inhibitors Using 3D-QSAR Modeling Combined with Molecular Docking.

    PubMed

    Sun, Guohui; Fan, Tengjiao; Zhang, Na; Ren, Ting; Zhao, Lijiao; Zhong, Rugang

    2016-01-01

    DNA repair enzyme O⁶-methylguanine-DNA methyltransferase (MGMT), which plays an important role in inducing drug resistance against alkylating agents that modify the O⁶ position of guanine in DNA, is an attractive target for anti-tumor chemotherapy. A series of MGMT inhibitors have been synthesized over the past decades to improve the chemotherapeutic effects of O⁶-alkylating agents. In the present study, we performed a three-dimensional quantitative structure activity relationship (3D-QSAR) study on 97 guanine derivatives as MGMT inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. Three different alignment methods (ligand-based, DFT optimization-based and docking-based alignment) were employed to develop reliable 3D-QSAR models. Statistical parameters derived from the models using the above three alignment methods showed that the ligand-based CoMFA (Qcv² = 0.672 and Rncv² = 0.997) and CoMSIA (Qcv² = 0.703 and Rncv² = 0.946) models were better than the other two alignment methods-based CoMFA and CoMSIA models. The two ligand-based models were further confirmed by an external test-set validation and a Y-randomization examination. The ligand-based CoMFA model (Qext² = 0.691, Rpred² = 0.738 and slope k = 0.91) was observed with acceptable external test-set validation values rather than the CoMSIA model (Qext² = 0.307, Rpred² = 0.4 and slope k = 0.719). Docking studies were carried out to predict the binding modes of the inhibitors with MGMT. The results indicated that the obtained binding interactions were consistent with the 3D contour maps. Overall, the combined results of the 3D-QSAR and the docking obtained in this study provide an insight into the understanding of the interactions between guanine derivatives and MGMT protein, which will assist in designing novel MGMT inhibitors with desired activity. PMID:27347909

  10. Feature extraction for change analysis in SAR time series

    NASA Astrophysics Data System (ADS)

    Boldt, Markus; Thiele, Antje; Schulz, Karsten; Hinz, Stefan

    2015-10-01

    In remote sensing, the change detection topic represents a broad field of research. If time series data is available, change detection can be used for monitoring applications. These applications require regular image acquisitions at identical time of day along a defined period. Focusing on remote sensing sensors, radar is especially well-capable for applications requiring regularity, since it is independent from most weather and atmospheric influences. Furthermore, regarding the image acquisitions, the time of day plays no role due to the independence from daylight. Since 2007, the German SAR (Synthetic Aperture Radar) satellite TerraSAR-X (TSX) permits the acquisition of high resolution radar images capable for the analysis of dense built-up areas. In a former study, we presented the change analysis of the Stuttgart (Germany) airport. The aim of this study is the categorization of detected changes in the time series. This categorization is motivated by the fact that it is a poor statement only to describe where and when a specific area has changed. At least as important is the statement about what has caused the change. The focus is set on the analysis of so-called high activity areas (HAA) representing areas changing at least four times along the investigated period. As first step for categorizing these HAAs, the matching HAA changes (blobs) have to be identified. Afterwards, operating in this object-based blob level, several features are extracted which comprise shape-based, radiometric, statistic, morphological values and one context feature basing on a segmentation of the HAAs. This segmentation builds on the morphological differential attribute profiles (DAPs). Seven context classes are established: Urban, infrastructure, rural stable, rural unstable, natural, water and unclassified. A specific HA blob is assigned to one of these classes analyzing the CovAmCoh time series signature of the surrounding segments. In combination, also surrounding GIS information

  11. 3d-3d correspondence revisited

    NASA Astrophysics Data System (ADS)

    Chung, Hee-Joong; Dimofte, Tudor; Gukov, Sergei; Sułkowski, Piotr

    2016-04-01

    In fivebrane compactifications on 3-manifolds, we point out the importance of all flat connections in the proper definition of the effective 3d {N}=2 theory. The Lagrangians of some theories with the desired properties can be constructed with the help of homological knot invariants that categorify colored Jones polynomials. Higgsing the full 3d theories constructed this way recovers theories found previously by Dimofte-Gaiotto-Gukov. We also consider the cutting and gluing of 3-manifolds along smooth boundaries and the role played by all flat connections in this operation.

  12. High Accuracy 3D Processing of Satellite Imagery

    NASA Technical Reports Server (NTRS)

    Gruen, A.; Zhang, L.; Kocaman, S.

    2007-01-01

    Automatic DSM/DTM generation reproduces not only general features, but also detailed features of the terrain relief. Height accuracy of around 1 pixel in cooperative terrain. RMSE values of 1.3-1.5 m (1.0-2.0 pixels) for IKONOS and RMSE values of 2.9-4.6 m (0.5-1.0 pixels) for SPOT5 HRS. For 3D city modeling, the manual and semi-automatic feature extraction capability of SAT-PP provides a good basis. The tools of SAT-PP allowed the stereo-measurements of points on the roofs in order to generate a 3D city model with CCM The results show that building models with main roof structures can be successfully extracted by HRSI. As expected, with Quickbird more details are visible.

  13. 3D features of delayed thermal convection in fault zones: consequences for deep fluid processes in the Tiberias Basin, Jordan Rift Valley

    NASA Astrophysics Data System (ADS)

    Magri, Fabien; Möller, Sebastian; Inbar, Nimrod; Siebert, Christian; Möller, Peter; Rosenthal, Eliyahu; Kühn, Michael

    2015-04-01

    It has been shown that thermal convection in faults can also occur for subcritical Rayleigh conditions. This type of convection develops after a certain period and is referred to as "delayed convection" (Murphy, 1979). The delay in the onset is due to the heat exchange between the damage zone and the surrounding units that adds a thermal buffer along the fault walls. Few numerical studies investigated delayed thermal convection in fractured zones, despite it has the potential to transport energy and minerals over large spatial scales (Tournier, 2000). Here 3D numerical simulations of thermally driven flow in faults are presented in order to investigate the impact of delayed convection on deep fluid processes at basin-scale. The Tiberias Basin (TB), in the Jordan Rift Valley, serves as study area. The TB is characterized by upsurge of deep-seated hot waters along the faulted shores of Lake Tiberias and high temperature gradient that can locally reach 46 °C/km, as in the Lower Yarmouk Gorge (LYG). 3D simulations show that buoyant flow ascend in permeable faults which hydraulic conductivity is estimated to vary between 30 m/yr and 140 m/yr. Delayed convection starts respectively at 46 and 200 kyrs and generate temperature anomalies in agreement with observations. It turned out that delayed convective cells are transient. Cellular patterns that initially develop in permeable units surrounding the faults can trigger convection also within the fault plane. The combination of these two convective modes lead to helicoidal-like flow patterns. This complex flow can explain the location of springs along different fault traces of the TB. Besides being of importance for understanding the hydrogeological processes of the TB (Magri et al., 2015), the presented simulations provide a scenario illustrating fault-induced 3D cells that could develop in any geothermal system. References Magri, F., Inbar, N., Siebert, C., Rosenthal, E., Guttman, J., Möller, P., 2015. Transient

  14. 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

  15. Fast and Accurate Data Extraction for Near Real-Time Registration of 3-D Ultrasound and Computed Tomography in Orthopedic Surgery.

    PubMed

    Brounstein, Anna; Hacihaliloglu, Ilker; Guy, Pierre; Hodgson, Antony; Abugharbieh, Rafeef

    2015-12-01

    Automatic, accurate and real-time registration is an important step in providing effective guidance and successful anatomic restoration in ultrasound (US)-based computer assisted orthopedic surgery. We propose a method in which local phase-based bone surfaces, extracted from intra-operative US data, are registered to pre-operatively segmented computed tomography data. Extracted bone surfaces are downsampled and reinforced with high curvature features. A novel hierarchical simplification algorithm is used to further optimize the point clouds. The final point clouds are represented as Gaussian mixture models and iteratively matched by minimizing the dissimilarity between them using an L2 metric. For 44 clinical data sets from 25 pelvic fracture patients and 49 phantom data sets, we report mean surface registration accuracies of 0.31 and 0.77 mm, respectively, with an average registration time of 1.41 s. Our results suggest the viability and potential of the chosen method for real-time intra-operative registration in orthopedic surgery. PMID:26365924

  16. 3D and Education

    NASA Astrophysics Data System (ADS)

    Meulien Ohlmann, Odile

    2013-02-01

    Today the industry offers a chain of 3D products. Learning to "read" and to "create in 3D" becomes an issue of education of primary importance. 25 years professional experience in France, the United States and Germany, Odile Meulien set up a personal method of initiation to 3D creation that entails the spatial/temporal experience of the holographic visual. She will present some different tools and techniques used for this learning, their advantages and disadvantages, programs and issues of educational policies, constraints and expectations related to the development of new techniques for 3D imaging. Although the creation of display holograms is very much reduced compared to the creation of the 90ies, the holographic concept is spreading in all scientific, social, and artistic activities of our present time. She will also raise many questions: What means 3D? Is it communication? Is it perception? How the seeing and none seeing is interferes? What else has to be taken in consideration to communicate in 3D? How to handle the non visible relations of moving objects with subjects? Does this transform our model of exchange with others? What kind of interaction this has with our everyday life? Then come more practical questions: How to learn creating 3D visualization, to learn 3D grammar, 3D language, 3D thinking? What for? At what level? In which matter? for whom?

  17. A review of recent advances in 3D face recognition

    NASA Astrophysics Data System (ADS)

    Luo, Jing; Geng, Shuze; Xiao, Zhaoxia; Xiu, Chunbo

    2015-03-01

    Face recognition based on machine vision has achieved great advances and been widely used in the various fields. However, there are some challenges on the face recognition, such as facial pose, variations in illumination, and facial expression. So, this paper gives the recent advances in 3D face recognition. 3D face recognition approaches are categorized into four groups: minutiae approach, space transform approach, geometric features approach, model approach. Several typical approaches are compared in detail, including feature extraction, recognition algorithm, and the performance of the algorithm. Finally, this paper summarized the challenge existing in 3D face recognition and the future trend. This paper aims to help the researches majoring on face recognition.

  18. Automated segmentation and feature extraction of product inspection items

    NASA Astrophysics Data System (ADS)

    Talukder, Ashit; Casasent, David P.

    1997-03-01

    X-ray film and linescan images of pistachio nuts on conveyor trays for product inspection are considered. The final objective is the categorization of pistachios into good, blemished and infested nuts. A crucial step before classification is the separation of touching products and the extraction of features essential for classification. This paper addresses new detection and segmentation algorithms to isolate touching or overlapping items. These algorithms employ a new filter, a new watershed algorithm, and morphological processing to produce nutmeat-only images. Tests on a large database of x-ray film and real-time x-ray linescan images of around 2900 small, medium and large nuts showed excellent segmentation results. A new technique to detect and segment dark regions in nutmeat images is also presented and tested on approximately 300 x-ray film and approximately 300 real-time linescan x-ray images with 95-97 percent detection and correct segmentation. New algorithms are described that determine nutmeat fill ratio and locate splits in nutmeat. The techniques formulated in this paper are of general use in many different product inspection and computer vision problems.

  19. Historical feature pattern extraction based network attack situation sensing algorithm.

    PubMed

    Zeng, Yong; Liu, Dacheng; Lei, Zhou

    2014-01-01

    The situation sequence contains a series of complicated and multivariate random trends, which are very sudden, uncertain, and difficult to recognize and describe its principle by traditional algorithms. To solve the above questions, estimating parameters of super long situation sequence is essential, but very difficult, so this paper proposes a situation prediction method based on historical feature pattern extraction (HFPE). First, HFPE algorithm seeks similar indications from the history situation sequence recorded and weighs the link intensity between occurred indication and subsequent effect. Then it calculates the probability that a certain effect reappears according to the current indication and makes a prediction after weighting. Meanwhile, HFPE method gives an evolution algorithm to derive the prediction deviation from the views of pattern and accuracy. This algorithm can continuously promote the adaptability of HFPE through gradual fine-tuning. The method preserves the rules in sequence at its best, does not need data preprocessing, and can track and adapt to the variation of situation sequence continuously. PMID:24892054

  20. Fault feature extraction of rolling element bearings using sparse representation

    NASA Astrophysics Data System (ADS)

    He, Guolin; Ding, Kang; Lin, Huibin

    2016-03-01

    Influenced by factors such as speed fluctuation, rolling element sliding and periodical variation of load distribution and impact force on the measuring direction of sensor, the impulse response signals caused by defective rolling bearing are non-stationary, and the amplitudes of the impulse may even drop to zero when the fault is out of load zone. The non-stationary characteristic and impulse missing phenomenon reduce the effectiveness of the commonly used demodulation method on rolling element bearing fault diagnosis. Based on sparse representation theories, a new approach for fault diagnosis of rolling element bearing is proposed. The over-complete dictionary is constructed by the unit impulse response function of damped second-order system, whose natural frequencies and relative damping ratios are directly identified from the fault signal by correlation filtering method. It leads to a high similarity between atoms and defect induced impulse, and also a sharply reduction of the redundancy of the dictionary. To improve the matching accuracy and calculation speed of sparse coefficient solving, the fault signal is divided into segments and the matching pursuit algorithm is carried out by segments. After splicing together all the reconstructed signals, the fault feature is extracted successfully. The simulation and experimental results show that the proposed method is effective for the fault diagnosis of rolling element bearing in large rolling element sliding and low signal to noise ratio circumstances.

  1. Information Theoretic Extraction of EEG Features for Monitoring Subject Attention

    NASA Technical Reports Server (NTRS)

    Principe, Jose C.

    2000-01-01

    The goal of this project was to test the applicability of information theoretic learning (feasibility study) to develop new brain computer interfaces (BCI). The difficulty to BCI comes from several aspects: (1) the effective data collection of signals related to cognition; (2) the preprocessing of these signals to extract the relevant information; (3) the pattern recognition methodology to detect reliably the signals related to cognitive states. We only addressed the two last aspects in this research. We started by evaluating an information theoretic measure of distance (Bhattacharyya distance) for BCI performance with good predictive results. We also compared several features to detect the presence of event related desynchronization (ERD) and synchronization (ERS), and concluded that at least for now the bandpass filtering is the best compromise between simplicity and performance. Finally, we implemented several classifiers for temporal - pattern recognition. We found out that the performance of temporal classifiers is superior to static classifiers but not by much. We conclude by stating that the future of BCI should be found in alternate approaches to sense, collect and process the signals created by populations of neurons. Towards this goal, cross-disciplinary teams of neuroscientists and engineers should be funded to approach BCIs from a much more principled view point.

  2. Feature extraction and models for speech: An overview

    NASA Astrophysics Data System (ADS)

    Schroeder, Manfred

    2002-11-01

    Modeling of speech has a long history, beginning with Count von Kempelens 1770 mechanical speaking machine. Even then human vowel production was seen as resulting from a source (the vocal chords) driving a physically separate resonator (the vocal tract). Homer Dudley's 1928 frequency-channel vocoder and many of its descendants are based on the same successful source-filter paradigm. For linguistic studies as well as practical applications in speech recognition, compression, and synthesis (see M. R. Schroeder, Computer Speech), the extant models require the (often difficult) extraction of numerous parameters such as the fundamental and formant frequencies and various linguistic distinctive features. Some of these difficulties were obviated by the introduction of linear predictive coding (LPC) in 1967 in which the filter part is an all-pole filter, reflecting the fact that for non-nasalized vowels the vocal tract is well approximated by an all-pole transfer function. In the now ubiquitous code-excited linear prediction (CELP), the source-part is replaced by a code book which (together with a perceptual error criterion) permits speech compression to very low bit rates at high speech quality for the Internet and cell phones.

  3. YouDash3D: exploring stereoscopic 3D gaming for 3D movie theaters

    NASA Astrophysics Data System (ADS)

    Schild, Jonas; Seele, Sven; Masuch, Maic

    2012-03-01

    Along with the success of the digitally revived stereoscopic cinema, events beyond 3D movies become attractive for movie theater operators, i.e. interactive 3D games. In this paper, we present a case that explores possible challenges and solutions for interactive 3D games to be played by a movie theater audience. We analyze the setting and showcase current issues related to lighting and interaction. Our second focus is to provide gameplay mechanics that make special use of stereoscopy, especially depth-based game design. Based on these results, we present YouDash3D, a game prototype that explores public stereoscopic gameplay in a reduced kiosk setup. It features live 3D HD video stream of a professional stereo camera rig rendered in a real-time game scene. We use the effect to place the stereoscopic effigies of players into the digital game. The game showcases how stereoscopic vision can provide for a novel depth-based game mechanic. Projected trigger zones and distributed clusters of the audience video allow for easy adaptation to larger audiences and 3D movie theater gaming.

  4. SNL3dFace

    SciTech Connect

    Russ, Trina; Koch, Mark; Koudelka, Melissa; Peters, Ralph; Little, Charles; Boehnen, Chris; Peters, Tanya

    2007-07-20

    This software distribution contains MATLAB and C++ code to enable identity verification using 3D images that may or may not contain a texture component. The code is organized to support system performance testing and system capability demonstration through the proper configuration of the available user interface. Using specific algorithm parameters the face recognition system has been demonstrated to achieve a 96.6% verification rate (Pd) at 0.001 false alarm rate. The system computes robust facial features of a 3D normalized face using Principal Component Analysis (PCA) and Fisher Linear Discriminant Analysis (FLDA). A 3D normalized face is obtained by alighning each face, represented by a set of XYZ coordinated, to a scaled reference face using the Iterative Closest Point (ICP) algorithm. The scaled reference face is then deformed to the input face using an iterative framework with parameters that control the deformed surface regulation an rate of deformation. A variety of options are available to control the information that is encoded by the PCA. Such options include the XYZ coordinates, the difference of each XYZ coordinates from the reference, the Z coordinate, the intensity/texture values, etc. In addition to PCA/FLDA feature projection this software supports feature matching to obtain similarity matrices for performance analysis. In addition, this software supports visualization of the STL, MRD, 2D normalized, and PCA synthetic representations in a 3D environment.

  5. 3D object retrieval using salient views.

    PubMed

    Atmosukarto, Indriyati; Shapiro, Linda G

    2013-06-01

    This paper presents a method for selecting salient 2D views to describe 3D objects for the purpose of retrieval. The views are obtained by first identifying salient points via a learning approach that uses shape characteristics of the 3D points (Atmosukarto and Shapiro in International workshop on structural, syntactic, and statistical pattern recognition, 2008; Atmosukarto and Shapiro in ACM multimedia information retrieval, 2008). The salient views are selected by choosing views with multiple salient points on the silhouette of the object. Silhouette-based similarity measures from Chen et al. (Comput Graph Forum 22(3):223-232, 2003) are then used to calculate the similarity between two 3D objects. Retrieval experiments were performed on three datasets: the Heads dataset, the SHREC2008 dataset, and the Princeton dataset. Experimental results show that the retrieval results using the salient views are comparable to the existing light field descriptor method (Chen et al. in Comput Graph Forum 22(3):223-232, 2003), and our method achieves a 15-fold speedup in the feature extraction computation time. PMID:23833704

  6. 3D object retrieval using salient views

    PubMed Central

    Shapiro, Linda G.

    2013-01-01

    This paper presents a method for selecting salient 2D views to describe 3D objects for the purpose of retrieval. The views are obtained by first identifying salient points via a learning approach that uses shape characteristics of the 3D points (Atmosukarto and Shapiro in International workshop on structural, syntactic, and statistical pattern recognition, 2008; Atmosukarto and Shapiro in ACM multimedia information retrieval, 2008). The salient views are selected by choosing views with multiple salient points on the silhouette of the object. Silhouette-based similarity measures from Chen et al. (Comput Graph Forum 22(3):223–232, 2003) are then used to calculate the similarity between two 3D objects. Retrieval experiments were performed on three datasets: the Heads dataset, the SHREC2008 dataset, and the Princeton dataset. Experimental results show that the retrieval results using the salient views are comparable to the existing light field descriptor method (Chen et al. in Comput Graph Forum 22(3):223–232, 2003), and our method achieves a 15-fold speedup in the feature extraction computation time. PMID:23833704

  7. Sexual Dimorphism Analysis and Gender Classification in 3D Human Face

    NASA Astrophysics Data System (ADS)

    Hu, Yuan; Lu, Li; Yan, Jingqi; Liu, Zhi; Shi, Pengfei

    In this paper, we present the sexual dimorphism analysis in 3D human face and perform gender classification based on the result of sexual dimorphism analysis. Four types of features are extracted from a 3D human-face image. By using statistical methods, the existence of sexual dimorphism is demonstrated in 3D human face based on these features. The contributions of each feature to sexual dimorphism are quantified according to a novel criterion. The best gender classification rate is 94% by using SVMs and Matcher Weighting fusion method.This research adds to the knowledge of 3D faces in sexual dimorphism and affords a foundation that could be used to distinguish between male and female in 3D faces.

  8. 3D texture analysis of solitary pulmonary nodules using co-occurrence matrix from volumetric lung CT images

    NASA Astrophysics Data System (ADS)

    Dhara, Ashis Kumar; Mukhopadhyay, Sudipta; Khandelwal, Niranjan

    2013-02-01

    In this paper we have investigated a new approach for texture features extraction using co-occurrence matrix from volumetric lung CT image. Traditionally texture analysis is performed in 2D and is suitable for images collected from 2D imaging modality. The use of 3D imaging modalities provide the scope of texture analysis from 3D object and 3D texture feature are more realistic to represent 3D object. In this work, Haralick's texture features are extended in 3D and computed from volumetric data considering 26 neighbors. The optimal texture features to characterize the internal structure of Solitary Pulmonary Nodules (SPN) are selected based on area under curve (AUC) values of ROC curve and p values from 2-tailed Student's t-test. The selected texture feature in 3D to represent SPN can be used in efficient Computer Aided Diagnostic (CAD) design plays an important role in fast and accurate lung cancer screening. The reduced number of input features to the CAD system will decrease the computational time and classification errors caused by irrelevant features. In the present work, SPN are classified from Ground Glass Nodule (GGN) using Artificial Neural Network (ANN) classifier considering top five 3D texture features and top five 2D texture features separately. The classification is performed on 92 SPN and 25 GGN from Imaging Database Resources Initiative (IDRI) public database and classification accuracy using 3D texture features and 2D texture features provide 97.17% and 89.1% respectively.

  9. Prominent rocks - 3D

    NASA Technical Reports Server (NTRS)

    1997-01-01

    Many prominent rocks near the Sagan Memorial Station are featured in this image, taken in stereo by the Imager for Mars Pathfinder (IMP) on Sol 3. 3D glasses are necessary to identify surface detail. Wedge is at lower left; Shark, Half-Dome, and Pumpkin are at center. Flat Top, about four inches high, is at lower right. The horizon in the distance is one to two kilometers away.

    Mars Pathfinder is the second in NASA's Discovery program of low-cost spacecraft with highly focused science goals. The Jet Propulsion Laboratory, Pasadena, CA, developed and manages the Mars Pathfinder mission for NASA's Office of Space Science, Washington, D.C. JPL is an operating division of the California Institute of Technology (Caltech). The Imager for Mars Pathfinder (IMP) was developed by the University of Arizona Lunar and Planetary Laboratory under contract to JPL. Peter Smith is the Principal Investigator.

    Click below to see the left and right views individually. [figure removed for brevity, see original site] Left [figure removed for brevity, see original site] Right

  10. 3D ear identification based on sparse representation.

    PubMed

    Zhang, Lin; Ding, Zhixuan; Li, Hongyu; Shen, Ying

    2014-01-01

    Biometrics based personal authentication is an effective way for automatically recognizing, with a high confidence, a person's identity. Recently, 3D ear shape has attracted tremendous interests in research field due to its richness of feature and ease of acquisition. However, the existing ICP (Iterative Closet Point)-based 3D ear matching methods prevalent in the literature are not quite efficient to cope with the one-to-many identification case. In this paper, we aim to fill this gap by proposing a novel effective fully automatic 3D ear identification system. We at first propose an accurate and efficient template-based ear detection method. By utilizing such a method, the extracted ear regions are represented in a common canonical coordinate system determined by the ear contour template, which facilitates much the following stages of feature extraction and classification. For each extracted 3D ear, a feature vector is generated as its representation by making use of a PCA-based local feature descriptor. At the stage of classification, we resort to the sparse representation based classification approach, which actually solves an l1-minimization problem. To the best of our knowledge, this is the first work introducing the sparse representation framework into the field of 3D ear identification. Extensive experiments conducted on a benchmark dataset corroborate the effectiveness and efficiency of the proposed approach. The associated Matlab source code and the evaluation results have been made publicly online available at http://sse.tongji.edu.cn/linzhang/ear/srcear/srcear.htm. PMID:24740247

  11. Research on the feature extraction and pattern recognition of the distributed optical fiber sensing signal

    NASA Astrophysics Data System (ADS)

    Wang, Bingjie; Sun, Qi; Pi, Shaohua; Wu, Hongyan

    2014-09-01

    In this paper, feature extraction and pattern recognition of the distributed optical fiber sensing signal have been studied. We adopt Mel-Frequency Cepstral Coefficient (MFCC) feature extraction, wavelet packet energy feature extraction and wavelet packet Shannon entropy feature extraction methods to obtain sensing signals (such as speak, wind, thunder and rain signals, etc.) characteristic vectors respectively, and then perform pattern recognition via RBF neural network. Performances of these three feature extraction methods are compared according to the results. We choose MFCC characteristic vector to be 12-dimensional. For wavelet packet feature extraction, signals are decomposed into six layers by Daubechies wavelet packet transform, in which 64 frequency constituents as characteristic vector are respectively extracted. In the process of pattern recognition, the value of diffusion coefficient is introduced to increase the recognition accuracy, while keeping the samples for testing algorithm the same. Recognition results show that wavelet packet Shannon entropy feature extraction method yields the best recognition accuracy which is up to 97%; the performance of 12-dimensional MFCC feature extraction method is less satisfactory; the performance of wavelet packet energy feature extraction method is the worst.

  12. Designing 3D Mesenchymal Stem Cell Sheets Merging Magnetic and Fluorescent Features: When Cell Sheet Technology Meets Image-Guided Cell Therapy

    PubMed Central

    Rahmi, Gabriel; Pidial, Laetitia; Silva, Amanda K. A.; Blondiaux, Eléonore; Meresse, Bertrand; Gazeau, Florence; Autret, Gwennhael; Balvay, Daniel; Cuenod, Charles André; Perretta, Silvana; Tavitian, Bertrand; Wilhelm, Claire; Cellier, Christophe; Clément, Olivier

    2016-01-01

    Cell sheet technology opens new perspectives in tissue regeneration therapy by providing readily implantable, scaffold-free 3D tissue constructs. Many studies have focused on the therapeutic effects of cell sheet implantation while relatively little attention has concerned the fate of the implanted cells in vivo. The aim of the present study was to track longitudinally the cells implanted in the cell sheets in vivo in target tissues. To this end we (i) endowed bone marrow-derived mesenchymal stem cells (BMMSCs) with imaging properties by double labeling with fluorescent and magnetic tracers, (ii) applied BMMSC cell sheets to a digestive fistula model in mice, (iii) tracked the BMMSC fate in vivo by MRI and probe-based confocal laser endomicroscopy (pCLE), and (iv) quantified healing of the fistula. We show that image-guided longitudinal follow-up can document both the fate of the cell sheet-derived BMMSCs and their healing capacity. Moreover, our theranostic approach informs on the mechanism of action, either directly by integration of cell sheet-derived BMMSCs into the host tissue or indirectly through the release of signaling molecules in the host tissue. Multimodal imaging and clinical evaluation converged to attest that cell sheet grafting resulted in minimal clinical inflammation, improved fistula healing, reduced tissue fibrosis and enhanced microvasculature density. At the molecular level, cell sheet transplantation induced an increase in the expression of anti-inflammatory cytokines (TGF-ß2 and IL-10) and host intestinal growth factors involved in tissue repair (EGF and VEGF). Multimodal imaging is useful for tracking cell sheets and for noninvasive follow-up of their regenerative properties. PMID:27022420

  13. 3D Imaging.

    ERIC Educational Resources Information Center

    Hastings, S. K.

    2002-01-01

    Discusses 3 D imaging as it relates to digital representations in virtual library collections. Highlights include X-ray computed tomography (X-ray CT); the National Science Foundation (NSF) Digital Library Initiatives; output peripherals; image retrieval systems, including metadata; and applications of 3 D imaging for libraries and museums. (LRW)

  14. Feature Extraction Of Retinal Images Interfaced With A Rule-Based Expert System

    NASA Astrophysics Data System (ADS)

    Ishag, Na seem; Connell, Kevin; Bolton, John

    1988-12-01

    Feature vectors are automatically extracted from a library of digital retinal images after considerable image processing. Main features extracted are location of optic disc, cup-to-disc ratio using Hough transform techniques and histogram and binary enhancement algorithms, and blood vessel locations. These feature vectors are used to form a relational data base of the images. Relational operations are then used to extract pertinent information from the data base to form replies to queries from the rule-based expert system.

  15. SNL3dFace

    2007-07-20

    This software distribution contains MATLAB and C++ code to enable identity verification using 3D images that may or may not contain a texture component. The code is organized to support system performance testing and system capability demonstration through the proper configuration of the available user interface. Using specific algorithm parameters the face recognition system has been demonstrated to achieve a 96.6% verification rate (Pd) at 0.001 false alarm rate. The system computes robust facial featuresmore » of a 3D normalized face using Principal Component Analysis (PCA) and Fisher Linear Discriminant Analysis (FLDA). A 3D normalized face is obtained by alighning each face, represented by a set of XYZ coordinated, to a scaled reference face using the Iterative Closest Point (ICP) algorithm. The scaled reference face is then deformed to the input face using an iterative framework with parameters that control the deformed surface regulation an rate of deformation. A variety of options are available to control the information that is encoded by the PCA. Such options include the XYZ coordinates, the difference of each XYZ coordinates from the reference, the Z coordinate, the intensity/texture values, etc. In addition to PCA/FLDA feature projection this software supports feature matching to obtain similarity matrices for performance analysis. In addition, this software supports visualization of the STL, MRD, 2D normalized, and PCA synthetic representations in a 3D environment.« less

  16. Comments on the paper 'A novel 3D wavelet-based filter forvisualizing features in noisy biological data', by Moss et al.

    SciTech Connect

    Luengo Hendriks, Cris L.; Knowles, David W.

    2006-02-04

    Moss et al.(2005) describe, in a recent paper, a filter thatthey use to detect lines. We noticed that the wavelet on which thisfilter is based is a difference of uniform filters. This filter is anapproximation to the second derivative operator, which is commonlyimplemented as the Laplace of Gaussian (or Marr-Hildreth) operator (Marr&Hildreth, 1980; Jahne, 2002), Figure 1. We have compared Moss'filter with 1) the Laplace of Gaussian operator, 2) an approximation ofthe Laplace of Gaussian using uniform filters, and 3) a few common noisereduction filters. The Laplace-like operators detect lines by suppressingimage features both larger and smaller than the filter size. The noisereduction filters only suppress image features smaller than the filtersize. By estimating the signal to noise ratio (SNR) and mean squaredifference (MSD) of the filtered results, we found that the filterproposed by Moss et al. does not outperform the Laplace of Gaussianoperator. We also found that for images with extreme noise content, linedetection filters perform better than the noise reduction filters whentrying to enhance line structures. In less extreme cases of noise, thestandard noise reduction filters perform significantly better than boththe Laplace of Gaussian and Moss' filter.

  17. Incorporation of texture-based features in optimal graph-theoretic approach with application to the 3D segmentation of intraretinal surfaces in SD-OCT volumes

    NASA Astrophysics Data System (ADS)

    Antony, Bhavna J.; Abràmoff, Michael D.; Sonka, Milan; Kwon, Young H.; Garvin, Mona K.

    2012-02-01

    While efficient graph-theoretic approaches exist for the optimal (with respect to a cost function) and simultaneous segmentation of multiple surfaces within volumetric medical images, the appropriate design of cost functions remains an important challenge. Previously proposed methods have used simple cost functions or optimized a combination of the same, but little has been done to design cost functions using learned features from a training set, in a less biased fashion. Here, we present a method to design cost functions for the simultaneous segmentation of multiple surfaces using the graph-theoretic approach. Classified texture features were used to create probability maps, which were incorporated into the graph-search approach. The efficiency of such an approach was tested on 10 optic nerve head centered optical coherence tomography (OCT) volumes obtained from 10 subjects that presented with glaucoma. The mean unsigned border position error was computed with respect to the average of manual tracings from two independent observers and compared to our previously reported results. A significant improvement was noted in the overall means which reduced from 9.25 +/- 4.03μm to 6.73 +/- 2.45μm (p < 0.01) and is also comparable with the inter-observer variability of 8.85 +/- 3.85μm.

  18. 3D seismic image processing for interpretation

    NASA Astrophysics Data System (ADS)

    Wu, Xinming

    Extracting fault, unconformity, and horizon surfaces from a seismic image is useful for interpretation of geologic structures and stratigraphic features. Although interpretation of these surfaces has been automated to some extent by others, significant manual effort is still required for extracting each type of these geologic surfaces. I propose methods to automatically extract all the fault, unconformity, and horizon surfaces from a 3D seismic image. To a large degree, these methods just involve image processing or array processing which is achieved by efficiently solving partial differential equations. For fault interpretation, I propose a linked data structure, which is simpler than triangle or quad meshes, to represent a fault surface. In this simple data structure, each sample of a fault corresponds to exactly one image sample. Using this linked data structure, I extract complete and intersecting fault surfaces without holes from 3D seismic images. I use the same structure in subsequent processing to estimate fault slip vectors. I further propose two methods, using precomputed fault surfaces and slips, to undo faulting in seismic images by simultaneously moving fault blocks and faults themselves. For unconformity interpretation, I first propose a new method to compute a unconformity likelihood image that highlights both the termination areas and the corresponding parallel unconformities and correlative conformities. I then extract unconformity surfaces from the likelihood image and use these surfaces as constraints to more accurately estimate seismic normal vectors that are discontinuous near the unconformities. Finally, I use the estimated normal vectors and use the unconformities as constraints to compute a flattened image, in which seismic reflectors are all flat and vertical gaps correspond to the unconformities. Horizon extraction is straightforward after computing a map of image flattening; we can first extract horizontal slices in the flattened space

  19. Case study: Beauty and the Beast 3D: benefits of 3D viewing for 2D to 3D conversion

    NASA Astrophysics Data System (ADS)

    Handy Turner, Tara

    2010-02-01

    From the earliest stages of the Beauty and the Beast 3D conversion project, the advantages of accurate desk-side 3D viewing was evident. While designing and testing the 2D to 3D conversion process, the engineering team at Walt Disney Animation Studios proposed a 3D viewing configuration that not only allowed artists to "compose" stereoscopic 3D but also improved efficiency by allowing artists to instantly detect which image features were essential to the stereoscopic appeal of a shot and which features had minimal or even negative impact. At a time when few commercial 3D monitors were available and few software packages provided 3D desk-side output, the team designed their own prototype devices and collaborated with vendors to create a "3D composing" workstation. This paper outlines the display technologies explored, final choices made for Beauty and the Beast 3D, wish-lists for future development and a few rules of thumb for composing compelling 2D to 3D conversions.

  20. A novel murmur-based heart sound feature extraction technique using envelope-morphological analysis

    NASA Astrophysics Data System (ADS)

    Yao, Hao-Dong; Ma, Jia-Li; Fu, Bin-Bin; Wang, Hai-Yang; Dong, Ming-Chui

    2015-07-01

    Auscultation of heart sound (HS) signals serves as an important primary approach to diagnose cardiovascular diseases (CVDs) for centuries. Confronting the intrinsic drawbacks of traditional HS auscultation, computer-aided automatic HS auscultation based on feature extraction technique has witnessed explosive development. Yet, most existing HS feature extraction methods adopt acoustic or time-frequency features which exhibit poor relationship with diagnostic information, thus restricting the performance of further interpretation and analysis. Tackling such a bottleneck problem, this paper innovatively proposes a novel murmur-based HS feature extraction method since murmurs contain massive pathological information and are regarded as the first indications of pathological occurrences of heart valves. Adapting discrete wavelet transform (DWT) and Shannon envelope, the envelope-morphological characteristics of murmurs are obtained and three features are extracted accordingly. Validated by discriminating normal HS and 5 various abnormal HS signals with extracted features, the proposed method provides an attractive candidate in automatic HS auscultation.

  1. The Feasibility of 3d Point Cloud Generation from Smartphones

    NASA Astrophysics Data System (ADS)

    Alsubaie, N.; El-Sheimy, N.

    2016-06-01

    This paper proposes a new technique for increasing the accuracy of direct geo-referenced image-based 3D point cloud generated from low-cost sensors in smartphones. The smartphone's motion sensors are used to directly acquire the Exterior Orientation Parameters (EOPs) of the captured images. These EOPs, along with the Interior Orientation Parameters (IOPs) of the camera/ phone, are used to reconstruct the image-based 3D point cloud. However, because smartphone motion sensors suffer from poor GPS accuracy, accumulated drift and high signal noise, inaccurate 3D mapping solutions often result. Therefore, horizontal and vertical linear features, visible in each image, are extracted and used as constraints in the bundle adjustment procedure. These constraints correct the relative position and orientation of the 3D mapping solution. Once the enhanced EOPs are estimated, the semi-global matching algorithm (SGM) is used to generate the image-based dense 3D point cloud. Statistical analysis and assessment are implemented herein, in order to demonstrate the feasibility of 3D point cloud generation from the consumer-grade sensors in smartphones.

  2. TRACE 3-D documentation

    SciTech Connect

    Crandall, K.R.

    1987-08-01

    TRACE 3-D is an interactive beam-dynamics program that calculates the envelopes of a bunched beam, including linear space-charge forces, through a user-defined transport system. TRACE 3-D provides an immediate graphics display of the envelopes and the phase-space ellipses and allows nine types of beam-matching options. This report describes the beam-dynamics calculations and gives detailed instruction for using the code. Several examples are described in detail.

  3. Enantioselective synthesis and olfactory evaluation of bicyclic alpha- and gamma-ionone derivatives: the 3D arrangement of key molecular features relevant to the violet odor of ionones.

    PubMed

    Luparia, Marco; Legnani, Laura; Porta, Alessio; Zanoni, Giuseppe; Toma, Lucio; Vidari, Giovanni

    2009-09-18

    Violet smelling ionones 1-3, occurring in the headspace of different flowers, are well-known perfumery raw materials. With the goal to recognize the still ill-defined spatial arrangement of structural features relevant to the binding of ionones to olfactory G-protein coupled receptors, through B3LYP/6-31G(d) modeling studies we identified bicyclic compounds 7-9 as conformationally constrained 13-alkyl-substituted analogues of monocyclic alpha- and gamma-ionones. They were thus synthesized to evaluate the olfactory properties. The enantioselective syntheses of 7-9 entailed two common key steps: (i) a Diels-Alder reaction to construct the octalinic core and (ii) a Julia-Lythgoe olefination to install the alpha,beta-enone side chain. The odor thresholds of synthetic 7 and 9 were significantly lower than the corresponding parent ionones, and 9 showed the lowest threshold value among violet-smelling odorants examined so far. Modeling studies suggested a nearly identical spatial orientation of key hydrophobic and polar moieties of compounds 1, 3, and 4-9. Presumably, interaction of these moieties with ionone olfactory receptors (ORs) triggers a similar receptor code that is ultimately interpreted by the human brain as a pleasant woody-violet smell. These results open the way to studies aimed at identifying and modeling complementary binding sites on alpha-helical domains of ionone receptor proteins. PMID:19743882

  4. 3D photo mosaicing of Tagiri shallow vent field by an autonomous underwater vehicle (3rd report) - Mosaicing method based on navigation data and visual features -

    NASA Astrophysics Data System (ADS)

    Maki, Toshihiro; Ura, Tamaki; Singh, Hanumant; Sakamaki, Takashi

    Large-area seafloor imaging will bring significant benefits to various fields such as academics, resource survey, marine development, security, and search-and-rescue. The authors have proposed a navigation method of an autonomous underwater vehicle for seafloor imaging, and verified its performance through mapping tubeworm colonies with the area of 3,000 square meters using the AUV Tri-Dog 1 at Tagiri vent field, Kagoshima bay in Japan (Maki et al., 2008, 2009). This paper proposes a post-processing method to build a natural photo mosaic from a number of pictures taken by an underwater platform. The method firstly removes lens distortion, invariances of color and lighting from each image, and then ortho-rectification is performed based on camera pose and seafloor estimated by navigation data. The image alignment is based on both navigation data and visual characteristics, implemented as an expansion of the image based method (Pizarro et al., 2003). Using the two types of information realizes an image alignment that is consistent both globally and locally, as well as making the method applicable to data sets with little visual keys. The method was evaluated using a data set obtained by the AUV Tri-Dog 1 at the vent field in Sep. 2009. A seamless, uniformly illuminated photo mosaic covering the area of around 500 square meters was created from 391 pictures, which covers unique features of the field such as bacteria mats and tubeworm colonies.

  5. TACO3D. 3-D Finite Element Heat Transfer Code

    SciTech Connect

    Mason, W.E.

    1992-03-04

    TACO3D is a three-dimensional, finite-element program for heat transfer analysis. An extension of the two-dimensional TACO program, it can perform linear and nonlinear analyses and can be used to solve either transient or steady-state problems. The program accepts time-dependent or temperature-dependent material properties, and materials may be isotropic or orthotropic. A variety of time-dependent and temperature-dependent boundary conditions and loadings are available including temperature, flux, convection, and radiation boundary conditions and internal heat generation. Additional specialized features treat enclosure radiation, bulk nodes, and master/slave internal surface conditions (e.g., contact resistance). Data input via a free-field format is provided. A user subprogram feature allows for any type of functional representation of any independent variable. A profile (bandwidth) minimization option is available. The code is limited to implicit time integration for transient solutions. TACO3D has no general mesh generation capability. Rows of evenly-spaced nodes and rows of sequential elements may be generated, but the program relies on separate mesh generators for complex zoning. TACO3D does not have the ability to calculate view factors internally. Graphical representation of data in the form of time history and spatial plots is provided through links to the POSTACO and GRAPE postprocessor codes.

  6. Extraction of facial features as indicators of stress and anxiety.

    PubMed

    Pediaditis, M; Giannakakis, G; Chiarugi, F; Manousos, D; Pampouchidou, A; Christinaki, E; Iatraki, G; Kazantzaki, E; Simos, P G; Marias, K; Tsiknakis, M

    2015-08-01

    Stress and anxiety heavily affect the human wellbeing and health. Under chronic stress, the human body and mind suffers by constantly mobilizing all of its resources for defense. Such a stress response can also be caused by anxiety. Moreover, excessive worrying and high anxiety can lead to depression and even suicidal thoughts. The typical tools for assessing these psycho-somatic states are questionnaires, but due to their shortcomings, by being subjective and prone to bias, new more robust methods based on facial expression analysis have emerged. Going beyond the typical detection of 6 basic emotions, this study aims to elaborate a set of facial features for the detection of stress and/or anxiety. It employs multiple methods that target each facial region individually. The features are selected and the classification performance is measured based on a dataset consisting 23 subjects. The results showed that with feature sets of 9 and 10 features an overall accuracy of 73% is reached. PMID:26737099

  7. Extraction of morphotectonic features from DEMs: Development and applications for study areas in Hungary and NW Greece

    NASA Astrophysics Data System (ADS)

    Jordan, G.; Meijninger, B. M. L.; Hinsbergen, D. J. J. van; Meulenkamp, J. E.; Dijk, P. M. van

    2005-11-01

    A procedure for the consistent application of digital terrain analysis methods to identify tectonic phenomena from geomorphology is developed and presented through two case studies. Based on the study of landforms related to faults, geomorphological characteristics are translated into mathematical and numerical algorithms. Topographic features represented by digital elevation models of the test areas were extracted, described and interpreted in terms of structural geology and geomorphology. Digital terrain modelling was carried out by means of the combined use of: (1) numerical differential geometry methods, (2) digital drainage network analysis, (3) digital geomorphometry, (4) digital image processing, (5) lineament extraction and analysis, (6) spatial and statistical analysis and (7) digital elevation model-specific digital methods, such as shaded relief models, digital cross-sections and 3D surface modelling. A sequential modelling scheme was developed and implemented to analyse two selected study sites, in Hungary and NW Greece on local and regional scales. Structural information from other sources, such as geological and geophysical maps, remotely sensed images and field observations were analysed with geographic information system techniques. Digital terrain analysis methods applied in the proposed way in this study could extract morphotectonic features from DEMs along known faults and they contributed to the tectonic interpretation of the study areas.

  8. Photogrammetric measurement of 3D freeform millimetre-sized objects with micro features: an experimental validation of the close-range camera calibration model for narrow angles of view

    NASA Astrophysics Data System (ADS)

    Percoco, Gianluca; Sánchez Salmerón, Antonio J.

    2015-09-01

    The measurement of millimetre and micro-scale features is performed by high-cost systems based on technologies with narrow working ranges to accurately control the position of the sensors. Photogrammetry would lower the costs of 3D inspection of micro-features and would be applicable to the inspection of non-removable micro parts of large objects too. Unfortunately, the behaviour of photogrammetry is not known when photogrammetry is applied to micro-features. In this paper, the authors address these issues towards the application of digital close-range photogrammetry (DCRP) to the micro-scale, taking into account that in literature there are research papers stating that an angle of view (AOV) around 10° is the lower limit to the application of the traditional pinhole close-range calibration model (CRCM), which is the basis of DCRP. At first a general calibration procedure is introduced, with the aid of an open-source software library, to calibrate narrow AOV cameras with the CRCM. Subsequently the procedure is validated using a reflex camera with a 60 mm macro lens, equipped with extension tubes (20 and 32 mm) achieving magnification of up to 2 times approximately, to verify literature findings with experimental photogrammetric 3D measurements of millimetre-sized objects with micro-features. The limitation experienced by the laser printing technology, used to produce the bi-dimensional pattern on common paper, has been overcome using an accurate pattern manufactured with a photolithographic process. The results of the experimental activity prove that the CRCM is valid for AOVs down to 3.4° and that DCRP results are comparable with the results of existing and more expensive commercial techniques.

  9. Combination of heterogeneous EEG feature extraction methods and stacked sequential learning for sleep stage classification.

    PubMed

    Herrera, L J; Fernandes, C M; Mora, A M; Migotina, D; Largo, R; Guillen, A; Rosa, A C

    2013-06-01

    This work proposes a methodology for sleep stage classification based on two main approaches: the combination of features extracted from electroencephalogram (EEG) signal by different extraction methods, and the use of stacked sequential learning to incorporate predicted information from nearby sleep stages in the final classifier. The feature extraction methods used in this work include three representative ways of extracting information from EEG signals: Hjorth features, wavelet transformation and symbolic representation. Feature selection was then used to evaluate the relevance of individual features from this set of methods. Stacked sequential learning uses a second-layer classifier to improve the classification by using previous and posterior first-layer predicted stages as additional features providing information to the model. Results show that both approaches enhance the sleep stage classification accuracy rate, thus leading to a closer approximation to the experts' opinion. PMID:23627659

  10. Comparison of half and full-leaf shape feature extraction for leaf classification

    NASA Astrophysics Data System (ADS)

    Sainin, Mohd Shamrie; Ahmad, Faudziah; Alfred, Rayner

    2016-08-01

    Shape is the main information for leaf feature that most of the current literatures in leaf identification utilize the whole leaf for feature extraction and to be used in the leaf identification process. In this paper, study of half-leaf features extraction for leaf identification is carried out and the results are compared with the results obtained from the leaf identification based on a full-leaf features extraction. Identification and classification is based on shape features that are represented as cosines and sinus angles. Six single classifiers obtained from WEKA and seven ensemble methods are used to compare their performance accuracies over this data. The classifiers were trained using 65 leaves in order to classify 5 different species of preliminary collection of Malaysian medicinal plants. The result shows that half-leaf features extraction can be used for leaf identification without decreasing the predictive accuracy.

  11. 3D shape decomposition and comparison for gallbladder modeling

    NASA Astrophysics Data System (ADS)

    Huang, Weimin; Zhou, Jiayin; Liu, Jiang; Zhang, Jing; Yang, Tao; Su, Yi; Law, Gim Han; Chui, Chee Kong; Chang, Stephen

    2011-03-01

    This paper presents an approach to gallbladder shape comparison by using 3D shape modeling and decomposition. The gallbladder models can be used for shape anomaly analysis and model comparison and selection in image guided robotic surgical training, especially for laparoscopic cholecystectomy simulation. The 3D shape of a gallbladder is first represented as a surface model, reconstructed from the contours segmented in CT data by a scheme of propagation based voxel learning and classification. To better extract the shape feature, the surface mesh is further down-sampled by a decimation filter and smoothed by a Taubin algorithm, followed by applying an advancing front algorithm to further enhance the regularity of the mesh. Multi-scale curvatures are then computed on the regularized mesh for the robust saliency landmark localization on the surface. The shape decomposition is proposed based on the saliency landmarks and the concavity, measured by the distance from the surface point to the convex hull. With a given tolerance the 3D shape can be decomposed and represented as 3D ellipsoids, which reveal the shape topology and anomaly of a gallbladder. The features based on the decomposed shape model are proposed for gallbladder shape comparison, which can be used for new model selection. We have collected 19 sets of abdominal CT scan data with gallbladders, some shown in normal shape and some in abnormal shapes. The experiments have shown that the decomposed shapes reveal important topology features.

  12. Efficient feature extraction from wide-area motion imagery by MapReduce in Hadoop

    NASA Astrophysics Data System (ADS)

    Cheng, Erkang; Ma, Liya; Blaisse, Adam; Blasch, Erik; Sheaff, Carolyn; Chen, Genshe; Wu, Jie; Ling, Haibin

    2014-06-01

    Wide-Area Motion Imagery (WAMI) feature extraction is important for applications such as target tracking, traffic management and accident discovery. With the increasing amount of WAMI collections and feature extraction from the data, a scalable framework is needed to handle the large amount of information. Cloud computing is one of the approaches recently applied in large scale or big data. In this paper, MapReduce in Hadoop is investigated for large scale feature extraction tasks for WAMI. Specifically, a large dataset of WAMI images is divided into several splits. Each split has a small subset of WAMI images. The feature extractions of WAMI images in each split are distributed to slave nodes in the Hadoop system. Feature extraction of each image is performed individually in the assigned slave node. Finally, the feature extraction results are sent to the Hadoop File System (HDFS) to aggregate the feature information over the collected imagery. Experiments of feature extraction with and without MapReduce are conducted to illustrate the effectiveness of our proposed Cloud-Enabled WAMI Exploitation (CAWE) approach.

  13. Liquid-liquid extraction and reversed phase chromatographic behaviour of some 3d metal ions using bis(2,4,4-trimethylpentyl)dithiophosphinic acid (Cyanex 301).

    PubMed

    Panesar, K S; Singh, O V; Tandon, S N

    1994-08-01

    Studies have been carried out on the extraction behavior of some metal ions of the first transition series using bis(2,4,4-trimethylpentyl)dithiophosphinic acid (Cyanex 301) from mineral acid media. The effect of various parameters influencing the extraction such as the nature of the diluent, concentration of the acid and the extractant on the distribution has been investigated. Based on the distribution data some binary separations have been proposed. A flow sheet of a scheme is given for the recovery of manganese free cobalt from a spent catalyst used in the manufacture of poly(ethyleneterepthalate). PMID:18966076

  14. Radiochromic 3D Detectors

    NASA Astrophysics Data System (ADS)

    Oldham, Mark

    2015-01-01

    Radiochromic materials exhibit a colour change when exposed to ionising radiation. Radiochromic film has been used for clinical dosimetry for many years and increasingly so recently, as films of higher sensitivities have become available. The two principle advantages of radiochromic dosimetry include greater tissue equivalence (radiologically) and the lack of requirement for development of the colour change. In a radiochromic material, the colour change arises direct from ionising interactions affecting dye molecules, without requiring any latent chemical, optical or thermal development, with important implications for increased accuracy and convenience. It is only relatively recently however, that 3D radiochromic dosimetry has become possible. In this article we review recent developments and the current state-of-the-art of 3D radiochromic dosimetry, and the potential for a more comprehensive solution for the verification of complex radiation therapy treatments, and 3D dose measurement in general.

  15. 3D visual discomfort predictor: analysis of horizontal disparity and neural activity statistics.

    PubMed

    Park, Jincheol; Oh, Heeseok; Lee, Sanghoon; Bovik, Alan Conrad

    2015-03-01

    Being able to predict the degree of visual discomfort that is felt when viewing stereoscopic 3D (S3D) images is an important goal toward ameliorating causative factors, such as excessive horizontal disparity, misalignments or mismatches between the left and right views of stereo pairs, or conflicts between different depth cues. Ideally, such a model should account for such factors as capture and viewing geometries, the distribution of disparities, and the responses of visual neurons. When viewing modern 3D displays, visual discomfort is caused primarily by changes in binocular vergence while accommodation in held fixed at the viewing distance to a flat 3D screen. This results in unnatural mismatches between ocular fixations and ocular focus that does not occur in normal direct 3D viewing. This accommodation vergence conflict can cause adverse effects, such as headaches, fatigue, eye strain, and reduced visual ability. Binocular vision is ultimately realized by means of neural mechanisms that subserve the sensorimotor control of eye movements. Realizing that the neuronal responses are directly implicated in both the control and experience of 3D perception, we have developed a model-based neuronal and statistical framework called the 3D visual discomfort predictor (3D-VDP)that automatically predicts the level of visual discomfort that is experienced when viewing S3D images. 3D-VDP extracts two types of features: 1) coarse features derived from the statistics of binocular disparities and 2) fine features derived by estimating the neural activity associated with the processing of horizontal disparities. In particular, we deploy a model of horizontal disparity processing in the extrastriate middle temporal region of occipital lobe. We compare the performance of 3D-VDP with other recent discomfort prediction algorithms with respect to correlation against recorded subjective visual discomfort scores,and show that 3D-VDP is statistically superior to the other methods. PMID

  16. PROCESSING OF SCANNED IMAGERY FOR CARTOGRAPHIC FEATURE EXTRACTION.

    USGS Publications Warehouse

    Benjamin, Susan P.; Gaydos, Leonard

    1984-01-01

    Digital cartographic data are usually captured by manually digitizing a map or an interpreted photograph or by automatically scanning a map. Both techniques first require manual photointerpretation to describe features of interest. A new approach, bypassing the laborious photointerpretation phase, is being explored using direct digital image analysis. Aerial photographs are scanned and color separated to create raster data. These are then enhanced and classified using several techniques to identify roads and buildings. Finally, the raster representation of these features is refined and vectorized. 11 refs.

  17. Extraction of terrain features from digital elevation models

    USGS Publications Warehouse

    Price, Curtis V.; Wolock, David M.; Ayers, Mark A.

    1989-01-01

    Digital elevation models (DEMs) are being used to determine variable inputs for hydrologic models in the Delaware River basin. Recently developed software for analysis of DEMs has been applied to watershed and streamline delineation. The results compare favorably with similar delineations taken from topographic maps. Additionally, output from this software has been used to extract other hydrologic information from the DEM, including flow direction, channel location, and an index describing the slope and shape of a watershed.

  18. Forest classification using extracted PolSAR features from Compact Polarimetry data

    NASA Astrophysics Data System (ADS)

    Aghabalaei, Amir; Maghsoudi, Yasser; Ebadi, Hamid

    2016-05-01

    This study investigates the ability of extracted Polarimetric Synthetic Aperture RADAR (PolSAR) features from Compact Polarimetry (CP) data for forest classification. The CP is a new mode that is recently proposed in Dual Polarimetry (DP) imaging system. It has several important advantages in comparison with Full Polarimetry (FP) mode such as reduction ability in complexity, cost, mass, data rate of a SAR system. Two strategies are employed for PolSAR feature extraction. In first strategy, the features are extracted using 2 × 2 covariance matrices of CP modes simulated by RADARSAT-2 C-band FP mode. In second strategy, they are extracted using 3 × 3 covariance matrices reconstructed from the CP modes called Pseudo Quad (PQ) modes. In each strategy, the extracted PolSAR features are combined and optimal features are selected by Genetic Algorithm (GA) and then a Support Vector Machine (SVM) classifier is applied. Finally, the results are compared with the FP mode. Results of this study show that the PolSAR features extracted from π / 4 CP mode, as well as combining the PolSAR features extracted from CP or PQ modes provide a better overall accuracy in classification of forest.

  19. Feature Extraction of Motion from Time-series Data by using Attractors

    NASA Astrophysics Data System (ADS)

    Akiduki, Takuma; Zhang, Zhong; Imamura, Takashi; Miyake, Tetsuo

    In this paper, a new method of motion analysis using attractors in nonlinear dynamical systems is discussed. The attractor is defined as a set of spatially-expanded trajectories of time-series data of a human motion in a state space. Using the attractor representation in the state space, a method of feature extraction from time-series data of human motions is proposed. The time-series data of human motions are captured by wearable inertial sensors. First, a design method of a dynamical system, which encodes time-series data of motions in attractors, is introduced. Next, an example of feature extraction using our approach is demonstrated for a simple upper limb movement. Finally, the physical meaning of the extracted features is discussed. As a result, the extracted features by attractors can describe the characteristics of the human motion, such as posture and quickness, effectively in the spatiotemporal continuity feature space.

  20. Individual 3D region-of-interest atlas of the human brain: knowledge-based class image analysis for extraction of anatomical objects

    NASA Astrophysics Data System (ADS)

    Wagenknecht, Gudrun; Kaiser, Hans-Juergen; Sabri, Osama; Buell, Udalrich

    2000-06-01

    After neural network-based classification of tissue types, the second step of atlas extraction is knowledge-based class image analysis to get anatomically meaningful objects. Basic algorithms are region growing, mathematical morphology operations, and template matching. A special algorithm was designed for each object. The class label of each voxel and the knowledge about the relative position of anatomical objects to each other and to the sagittal midplane of the brain can be utilized for object extraction. User interaction is only necessary to define starting, mid- and end planes for most object extractions and to determine the number of iterations for erosion and dilation operations. Extraction can be done for the following anatomical brain regions: cerebrum; cerebral hemispheres; cerebellum; brain stem; white matter (e.g., centrum semiovale); gray matter [cortex, frontal, parietal, occipital, temporal lobes, cingulum, insula, basal ganglia (nuclei caudati, putamen, thalami)]. For atlas- based quantification of functional data, anatomical objects can be convoluted with the point spread function of functional data to take into account the different resolutions of morphological and functional modalities. This method allows individual atlas extraction from MRI image data of a patient without the need of warping individual data to an anatomical or statistical MRI brain atlas.

  1. Topology dictionary for 3D video understanding.

    PubMed

    Tung, Tony; Matsuyama, Takashi

    2012-08-01

    This paper presents a novel approach that achieves 3D video understanding. 3D video consists of a stream of 3D models of subjects in motion. The acquisition of long sequences requires large storage space (2 GB for 1 min). Moreover, it is tedious to browse data sets and extract meaningful information. We propose the topology dictionary to encode and describe 3D video content. The model consists of a topology-based shape descriptor dictionary which can be generated from either extracted patterns or training sequences. The model relies on 1) topology description and classification using Reeb graphs, and 2) a Markov motion graph to represent topology change states. We show that the use of Reeb graphs as the high-level topology descriptor is relevant. It allows the dictionary to automatically model complex sequences, whereas other strategies would require prior knowledge on the shape and topology of the captured subjects. Our approach serves to encode 3D video sequences, and can be applied for content-based description and summarization of 3D video sequences. Furthermore, topology class labeling during a learning process enables the system to perform content-based event recognition. Experiments were carried out on various 3D videos. We showcase an application for 3D video progressive summarization using the topology dictionary. PMID:22745004

  2. Biosensor method and system based on feature vector extraction

    DOEpatents

    Greenbaum, Elias; Rodriguez, Jr., Miguel; Qi, Hairong; Wang, Xiaoling

    2013-07-02

    A system for biosensor-based detection of toxins includes providing at least one time-dependent control signal generated by a biosensor in a gas or liquid medium, and obtaining a time-dependent biosensor signal from the biosensor in the gas or liquid medium to be monitored or analyzed for the presence of one or more toxins selected from chemical, biological or radiological agents. The time-dependent biosensor signal is processed to obtain a plurality of feature vectors using at least one of amplitude statistics and a time-frequency analysis. At least one parameter relating to toxicity of the gas or liquid medium is then determined from the feature vectors based on reference to the control signal.

  3. Biosensor method and system based on feature vector extraction

    DOEpatents

    Greenbaum, Elias; Rodriguez, Jr., Miguel; Qi, Hairong; Wang, Xiaoling

    2012-04-17

    A method of biosensor-based detection of toxins comprises the steps of providing at least one time-dependent control signal generated by a biosensor in a gas or liquid medium, and obtaining a time-dependent biosensor signal from the biosensor in the gas or liquid medium to be monitored or analyzed for the presence of one or more toxins selected from chemical, biological or radiological agents. The time-dependent biosensor signal is processed to obtain a plurality of feature vectors using at least one of amplitude statistics and a time-frequency analysis. At least one parameter relating to toxicity of the gas or liquid medium is then determined from the feature vectors based on reference to the control signal.

  4. Hand veins feature extraction using DT-CNNS

    NASA Astrophysics Data System (ADS)

    Malki, Suleyman; Spaanenburg, Lambert

    2007-05-01

    As the identification process is based on the unique patterns of the users, biometrics technologies are expected to provide highly secure authentication systems. The existing systems using fingerprints or retina patterns are, however, very vulnerable. One's fingerprints are accessible as soon as the person touches a surface, while a high resolution camera easily captures the retina pattern. Thus, both patterns can easily be "stolen" and forged. Beside, technical considerations decrease the usability for these methods. Due to the direct contact with the finger, the sensor gets dirty, which decreases the authentication success ratio. Aligning the eye with a camera to capture the retina pattern gives uncomfortable feeling. On the other hand, vein patterns of either a palm of the hand or a single finger offer stable, unique and repeatable biometrics features. A fingerprint-based identification system using Cellular Neural Networks has already been proposed by Gao. His system covers all stages of a typical fingerprint verification procedure from Image Preprocessing to Feature Matching. This paper performs a critical review of the individual algorithmic steps. Notably, the operation of False Feature Elimination is applied only once instead of 3 times. Furthermore, the number of iterations is limited to 1 for all used templates. Hence, the computational need of the feedback contribution is removed. Consequently the computational effort is drastically reduced without a notable chance in quality. This allows a full integration of the detection mechanism. The system is prototyped on a Xilinx Virtex II Pro P30 FPGA.

  5. The fuzzy Hough Transform-feature extraction in medical images

    SciTech Connect

    Philip, K.P.; Dove, E.L.; Stanford, W.; Chandran, K.B. ); McPherson, D.D.; Gotteiner, N.L. . Dept. of Internal Medicine)

    1994-06-01

    Identification of anatomical features is a necessary step for medical image analysis. Automatic methods for feature identification using conventional pattern recognition techniques typically classify an object as a member of a predefined class of objects, but do not attempt to recover the exact or approximate shape of that object. For this reason, such techniques are usually not sufficient to identify the borders of organs when individual geometry varies in local detail, even though the general geometrical shape is similar. The authors present an algorithm that detects features in an image based on approximate geometrical models. The algorithm is based on the traditional and generalized Hough Transforms but includes notions from fuzzy set theory. The authors use the new algorithm to roughly estimate the actual locations of boundaries of an internal organ, and from this estimate, to determine a region of interest around the organ. Based on this rough estimate of the border location, and the derived region of interest, the authors find the final estimate of the true borders with other image processing techniques. The authors present results that demonstrate that the algorithm was successfully used to estimate the approximate location of the chest wall in humans, and of the left ventricular contours of a dog heart obtained from cine-computed tomographic images. The authors use this fuzzy Hough Transform algorithm as part of a larger procedures to automatically identify the myocardial contours of the heart. This algorithm may also allow for more rapid image processing and clinical decision making in other medical imaging applications.

  6. Semantic control of feature extraction from natural scenes.

    PubMed

    Neri, Peter

    2014-02-01

    In the early stages of image analysis, visual cortex represents scenes as spatially organized maps of locally defined features (e.g., edge orientation). As image reconstruction unfolds and features are assembled into larger constructs, cortex attempts to recover semantic content for object recognition. It is conceivable that higher level representations may feed back onto early processes and retune their properties to align with the semantic structure projected by the scene; however, there is no clear evidence to either support or discard the applicability of this notion to the human visual system. Obtaining such evidence is challenging because low and higher level processes must be probed simultaneously within the same experimental paradigm. We developed a methodology that targets both levels of analysis by embedding low-level probes within natural scenes. Human observers were required to discriminate probe orientation while semantic interpretation of the scene was selectively disrupted via stimulus inversion or reversed playback. We characterized the orientation tuning properties of the perceptual process supporting probe discrimination; tuning was substantially reshaped by semantic manipulation, demonstrating that low-level feature detectors operate under partial control from higher level modules. The manner in which such control was exerted may be interpreted as a top-down predictive strategy whereby global semantic content guides and refines local image reconstruction. We exploit the novel information gained from data to develop mechanistic accounts of unexplained phenomena such as the classic face inversion effect. PMID:24501376

  7. A Model for Extracting Personal Features of an Electroencephalogram and Its Evaluation Method

    NASA Astrophysics Data System (ADS)

    Ito, Shin-Ichi; Mitsukura, Yasue; Fukumi, Minoru

    This paper introduces a model for extracting features of an electroencephalogram (EEG) and a method for evaluating the model. In general, it is known that an EEG contains personal features. However, extraction of these personal features has not been reported. The analyzed frequency components of an EEG can be classified as the components that contain significant number of features and the ones that do not contain any. From the viewpoint of these feature differences, we propose the model for extracting features of the EEG. The model assumes a latent structure and employs factor analysis by considering the model error as personal error. We consider the EEG feature as a first factor loading, which is calculated by eigenvalue decomposition. Furthermore, we use a k-nearest neighbor (kNN) algorithm for evaluating the proposed model and extracted EEG features. In general, the distance metric used is Euclidean distance. We believe that the distance metric used depends on the characteristic of the extracted EEG feature and on the subject. Therefore, depending on the subject, we use one of the three distance metrics: Euclidean distance, cosine distance, and correlation coefficient. Finally, in order to show the effectiveness of the proposed model, we perform a computer simulation using real EEG data.

  8. Contextual Classification of Point Cloud Data by Exploiting Individual 3d Neigbourhoods

    NASA Astrophysics Data System (ADS)

    Weinmann, M.; Schmidt, A.; Mallet, C.; Hinz, S.; Rottensteiner, F.; Jutzi, B.

    2015-03-01

    The fully automated analysis of 3D point clouds is of great importance in photogrammetry, remote sensing and computer vision. For reliably extracting objects such as buildings, road inventory or vegetation, many approaches rely on the results of a point cloud classification, where each 3D point is assigned a respective semantic class label. Such an assignment, in turn, typically involves statistical methods for feature extraction and machine learning. Whereas the different components in the processing workflow have extensively, but separately been investigated in recent years, the respective connection by sharing the results of crucial tasks across all components has not yet been addressed. This connection not only encapsulates the interrelated issues of neighborhood selection and feature extraction, but also the issue of how to involve spatial context in the classification step. In this paper, we present a novel and generic approach for 3D scene analysis which relies on (i) individually optimized 3D neighborhoods for (ii) the extraction of distinctive geometric features and (iii) the contextual classification of point cloud data. For a labeled benchmark dataset, we demonstrate the beneficial impact of involving contextual information in the classification process and that using individual 3D neighborhoods of optimal size significantly increases the quality of the results for both pointwise and contextual classification.

  9. Feature Extraction for Mental Fatigue and Relaxation States Based on Systematic Evaluation Considering Individual Difference

    NASA Astrophysics Data System (ADS)

    Chen, Lanlan; Sugi, Takenao; Shirakawa, Shuichiro; Zou, Junzhong; Nakamura, Masatoshi

    Feature extraction for mental fatigue and relaxation states is helpful to understand the mechanisms of mental fatigue and search effective relaxation technique in sustained work environments. Experiment data of human states are often affected by external and internal factors, which increase the difficulties to extract common features. The aim of this study is to explore appropriate methods to eliminate individual difference and enhance common features. Mental fatigue and relaxation experiments are executed on 12 subjects. An integrated and evaluation system is proposed, which consists of subjective evaluation (visual analogue scale), calculation performance and neurophysiological signals especially EEG signals. With consideration of individual difference, the common features of multi-estimators testify the effectiveness of relaxation in sustained mental work. Relaxation technique can be practically applied to prevent accumulation of mental fatigue and keep mental health. The proposed feature extraction methods are widely applicable to obtain common features and release the restriction for subjection selection and experiment design.

  10. Embedded prediction in feature extraction: application to single-trial EEG discrimination.

    PubMed

    Hsu, Wei-Yen

    2013-01-01

    In this study, an analysis system embedding neuron-fuzzy prediction in feature extraction is proposed for brain-computer interface (BCI) applications. Wavelet-fractal features combined with neuro-fuzzy predictions are applied for feature extraction in motor imagery (MI) discrimination. The features are extracted from the electroencephalography (EEG) signals recorded from participants performing left and right MI. Time-series predictions are performed by training 2 adaptive neuro-fuzzy inference systems (ANFIS) for respective left and right MI data. Features are then calculated from the difference in multi-resolution fractal feature vector (MFFV) between the predicted and actual signals through a window of EEG signals. Finally, the support vector machine is used for classification. The proposed method estimates its performance in comparison with the linear adaptive autoregressive (AAR) model and the AAR time-series prediction of 6 participants from 2 data sets. The results indicate that the proposed method is promising in MI classification. PMID:23248335

  11. Computing 3-D structure of rigid objects using stereo and motion

    NASA Technical Reports Server (NTRS)

    Nguyen, Thinh V.

    1987-01-01

    Work performed as a step toward an intelligent automatic machine vision system for 3-D imaging is discussed. The problem considered is the quantitative 3-D reconstruction of rigid objects. Motion and stereo are the two clues considered in this system. The system basically consists of three processes: the low level process to extract image features, the middle level process to establish the correspondence in the stereo (spatial) and motion (temporal) modalities, and the high level process to compute the 3-D coordinates of the corner points by integrating the spatial and temporal correspondences.

  12. Geometric feature extraction by a multimarked point process.

    PubMed

    Lafarge, Florent; Gimel'farb, Georgy; Descombes, Xavier

    2010-09-01

    This paper presents a new stochastic marked point process for describing images in terms of a finite library of geometric objects. Image analysis based on conventional marked point processes has already produced convincing results but at the expense of parameter tuning, computing time, and model specificity. Our more general multimarked point process has simpler parametric setting, yields notably shorter computing times, and can be applied to a variety of applications. Both linear and areal primitives extracted from a library of geometric objects are matched to a given image using a probabilistic Gibbs model, and a Jump-Diffusion process is performed to search for the optimal object configuration. Experiments with remotely sensed images and natural textures show that the proposed approach has good potential. We conclude with a discussion about the insertion of more complex object interactions in the model by studying the compromise between model complexity and efficiency. PMID:20634555

  13. A Novel Feature Extraction Method with Feature Selection to Identify Golgi-Resident Protein Types from Imbalanced Data

    PubMed Central

    Yang, Runtao; Zhang, Chengjin; Gao, Rui; Zhang, Lina

    2016-01-01

    The Golgi Apparatus (GA) is a major collection and dispatch station for numerous proteins destined for secretion, plasma membranes and lysosomes. The dysfunction of GA proteins can result in neurodegenerative diseases. Therefore, accurate identification of protein subGolgi localizations may assist in drug development and understanding the mechanisms of the GA involved in various cellular processes. In this paper, a new computational method is proposed for identifying cis-Golgi proteins from trans-Golgi proteins. Based on the concept of Common Spatial Patterns (CSP), a novel feature extraction technique is developed to extract evolutionary information from protein sequences. To deal with the imbalanced benchmark dataset, the Synthetic Minority Over-sampling Technique (SMOTE) is adopted. A feature selection method called Random Forest-Recursive Feature Elimination (RF-RFE) is employed to search the optimal features from the CSP based features and g-gap dipeptide composition. Based on the optimal features, a Random Forest (RF) module is used to distinguish cis-Golgi proteins from trans-Golgi proteins. Through the jackknife cross-validation, the proposed method achieves a promising performance with a sensitivity of 0.889, a specificity of 0.880, an accuracy of 0.885, and a Matthew’s Correlation Coefficient (MCC) of 0.765, which remarkably outperforms previous methods. Moreover, when tested on a common independent dataset, our method also achieves a significantly improved performance. These results highlight the promising performance of the proposed method to identify Golgi-resident protein types. Furthermore, the CSP based feature extraction method may provide guidelines for protein function predictions. PMID:26861308

  14. A Novel Feature Extraction Method with Feature Selection to Identify Golgi-Resident Protein Types from Imbalanced Data.

    PubMed

    Yang, Runtao; Zhang, Chengjin; Gao, Rui; Zhang, Lina

    2016-01-01

    The Golgi Apparatus (GA) is a major collection and dispatch station for numerous proteins destined for secretion, plasma membranes and lysosomes. The dysfunction of GA proteins can result in neurodegenerative diseases. Therefore, accurate identification of protein subGolgi localizations may assist in drug development and understanding the mechanisms of the GA involved in various cellular processes. In this paper, a new computational method is proposed for identifying cis-Golgi proteins from trans-Golgi proteins. Based on the concept of Common Spatial Patterns (CSP), a novel feature extraction technique is developed to extract evolutionary information from protein sequences. To deal with the imbalanced benchmark dataset, the Synthetic Minority Over-sampling Technique (SMOTE) is adopted. A feature selection method called Random Forest-Recursive Feature Elimination (RF-RFE) is employed to search the optimal features from the CSP based features and g-gap dipeptide composition. Based on the optimal features, a Random Forest (RF) module is used to distinguish cis-Golgi proteins from trans-Golgi proteins. Through the jackknife cross-validation, the proposed method achieves a promising performance with a sensitivity of 0.889, a specificity of 0.880, an accuracy of 0.885, and a Matthew's Correlation Coefficient (MCC) of 0.765, which remarkably outperforms previous methods. Moreover, when tested on a common independent dataset, our method also achieves a significantly improved performance. These results highlight the promising performance of the proposed method to identify Golgi-resident protein types. Furthermore, the CSP based feature extraction method may provide guidelines for protein function predictions. PMID:26861308

  15. 3D microscope

    NASA Astrophysics Data System (ADS)

    Iizuka, Keigo

    2008-02-01

    In order to circumvent the fact that only one observer can view the image from a stereoscopic microscope, an attachment was devised for displaying the 3D microscopic image on a large LCD monitor for viewing by multiple observers in real time. The principle of operation, design, fabrication, and performance are presented, along with tolerance measurements relating to the properties of the cellophane half-wave plate used in the design.

  16. Comparison study of feature extraction methods in structural damage pattern recognition

    NASA Astrophysics Data System (ADS)

    Liu, Wenjia; Chen, Bo; Swartz, R. Andrew

    2011-04-01

    This paper compares the performance of various feature extraction methods applied to structural sensor measurements acquired in-situ, from a decommissioned bridge under realistic damage scenarios. Three feature extraction methods are applied to sensor data to generate feature vectors for normal and damaged structure data patterns. The investigated feature extraction methods include identification of both time domain methods as well as frequency domain methods. The evaluation of the feature extraction methods is performed by examining distance values among different patterns, distance values among feature vectors in the same pattern, and pattern recognition success rate. The test data used in the comparison study are from the System Identification to Monitor Civil Engineering Structures (SIMCES) Z24 Bridge damage detection tests, a rigorous instrumentation campaign that recorded the dynamic performance of a concrete box-girder bridge under progressively increasing damage scenarios. A number of progressive damage test case data sets, including undamaged cases and pier settlement cases (different depths), are used to test the separation of feature vectors among different patterns and the pattern recognition success rate for different feature extraction methods is reported.

  17. Singular value decomposition based feature extraction approaches for classifying faults of induction motors

    NASA Astrophysics Data System (ADS)

    Kang, Myeongsu; Kim, Jong-Myon

    2013-12-01

    This paper proposes singular value decomposition (SVD)-based feature extraction methods for fault classification of an induction motor: a short-time energy (STE) plus SVD technique in the time-domain analysis, and a discrete cosine transform (DCT) plus SVD technique in the frequency-domain analysis. To early identify induction motor faults, the extracted features are utilized as the inputs of multi-layer support vector machines (MLSVMs). Since SVMs perform well with the radial basis function (RBF) kernel for appropriately categorizing the faults of the induction motor, it is important to explore the impact of the σ values for the RBF kernel, which affects the classification accuracy. Likewise, this paper quantitatively evaluates the classification accuracy with different numbers of features, because the number of features affects the classification accuracy. According to the experimental results, although SVD-based features are effective for a noiseless environment, the STE plus SVD feature extraction approach is more effective with and without sensor noise in terms of the classification accuracy than the DCT plus SVD feature extraction approach. To demonstrate the improved classification of the proposed approach for identifying faults of the induction motor, the proposed SVD based feature extraction approach is compared with other state-of-the art methods and yields higher classification accuracies for both noiseless and noisy environments than conventional approaches.

  18. Fragmentary area repairing on the edge of 3D laser point cloud based on edge extracting of images and LS-SVM

    NASA Astrophysics Data System (ADS)

    Zhao, Ziming; Hao, Xiangyang; Liu, Songlin; Zhao, Song

    2011-06-01

    In the process of hole-repairing in point cloud, it's difficult to repair by the indeterminate boundary of fragmentary area in the edge of point cloud. In view of this condition, the article advances a method of Fragmentary area repairing on the edge of point cloud based on edge extracting of image and LS-SVM. After the registration of point cloud and corresponding image, the sub-pixel edge can be extracted from the image. Then project the training points and sub-pixel edge to the characteristic plane that has being constructed to confirm the bound and position for re-sampling. At last get the equation of fragmentary area to accomplish the repairing by Least-Squares Support Vector Machines. The experimental results demonstrate that the method guarantees accurate fine repairing.

  19. A Review of Feature Extraction Software for Microarray Gene Expression Data

    PubMed Central

    Tan, Ching Siang; Ting, Wai Soon; Mohamad, Mohd Saberi; Chan, Weng Howe; Deris, Safaai; Ali Shah, Zuraini

    2014-01-01

    When gene expression data are too large to be processed, they are transformed into a reduced representation set of genes. Transforming large-scale gene expression data into a set of genes is called feature extraction. If the genes extracted are carefully chosen, this gene set can extract the relevant information from the large-scale gene expression data, allowing further analysis by using this reduced representation instead of the full size data. In this paper, we review numerous software applications that can be used for feature extraction. The software reviewed is mainly for Principal Component Analysis (PCA), Independent Component Analysis (ICA), Partial Least Squares (PLS), and Local Linear Embedding (LLE). A summary and sources of the software are provided in the last section for each feature extraction method. PMID:25250315

  20. Automated Development of Feature Extraction Tools for Planetary Science Image Datasets

    NASA Astrophysics Data System (ADS)

    Plesko, C.; Brumby, S.; Asphaug, E.

    2003-03-01

    We explore development of feature extraction algorithms for Mars Orbiter Camera narrow angle data using GENIE machine learning software. The algorithms are successful at detecting craters within the images, and generalize well to a new image.

  1. Sparse representation of transients in wavelet basis and its application in gearbox fault feature extraction

    NASA Astrophysics Data System (ADS)

    Fan, Wei; Cai, Gaigai; Zhu, Z. K.; Shen, Changqing; Huang, Weiguo; Shang, Li

    2015-05-01

    Vibration signals from a defective gearbox are often associated with important measurement information useful for gearbox fault diagnosis. The extraction of transient features from the vibration signals has always been a key issue for detecting the localized fault. In this paper, a new transient feature extraction technique is proposed for gearbox fault diagnosis based on sparse representation in wavelet basis. With the proposed method, both the impulse time and the period of transients can be effectively identified, and thus the transient features can be extracted. The effectiveness of the proposed method is verified by the simulated signals as well as the practical gearbox vibration signals. Comparison study shows that the proposed method outperforms empirical mode decomposition (EMD) in transient feature extraction.

  2. Micromotion feature extraction of radar target using tracking pulses with adaptive pulse repetition frequency adjustment

    NASA Astrophysics Data System (ADS)

    Chen, Yijun; Zhang, Qun; Ma, Changzheng; Luo, Ying; Yeo, Tat Soon

    2014-01-01

    In multifunction phased array radar systems, different activities (e.g., tracking, searching, imaging, feature extraction, recognition, etc.) would need to be performed simultaneously. To relieve the conflict of the radar resource distribution, a micromotion feature extraction method using tracking pulses with adaptive pulse repetition frequencies (PRFs) is proposed in this paper. In this method, the idea of a varying PRF is utilized to solve the frequency-domain aliasing problem of the micro-Doppler signal. With appropriate atom set construction, the micromotion feature can be extracted and the image of the target can be obtained based on the Orthogonal Matching Pursuit algorithm. In our algorithm, the micromotion feature of a radar target is extracted from the tracking pulses and the quality of the constructed image is fed back into the radar system to adaptively adjust the PRF of the tracking pulses. Finally, simulation results illustrate the effectiveness of the proposed method.

  3. Software for 3D radiotherapy dosimetry. Validation

    NASA Astrophysics Data System (ADS)

    Kozicki, Marek; Maras, Piotr; Karwowski, Andrzej C.

    2014-08-01

    The subject of this work is polyGeVero® software (GeVero Co., Poland), which has been developed to fill the requirements of fast calculations of 3D dosimetry data with the emphasis on polymer gel dosimetry for radiotherapy. This software comprises four workspaces that have been prepared for: (i) calculating calibration curves and calibration equations, (ii) storing the calibration characteristics of the 3D dosimeters, (iii) calculating 3D dose distributions in irradiated 3D dosimeters, and (iv) comparing 3D dose distributions obtained from measurements with the aid of 3D dosimeters and calculated with the aid of treatment planning systems (TPSs). The main features and functions of the software are described in this work. Moreover, the core algorithms were validated and the results are presented. The validation was performed using the data of the new PABIGnx polymer gel dosimeter. The polyGeVero® software simplifies and greatly accelerates the calculations of raw 3D dosimetry data. It is an effective tool for fast verification of TPS-generated plans for tumor irradiation when combined with a 3D dosimeter. Consequently, the software may facilitate calculations by the 3D dosimetry community. In this work, the calibration characteristics of the PABIGnx obtained through four calibration methods: multi vial, cross beam, depth dose, and brachytherapy, are discussed as well.

  4. Dimensional accuracy of 3D printed vertebra

    NASA Astrophysics Data System (ADS)

    Ogden, Kent; Ordway, Nathaniel; Diallo, Dalanda; Tillapaugh-Fay, Gwen; Aslan, Can

    2014-03-01

    3D printer applications in the biomedical sciences and medical imaging are expanding and will have an increasing impact on the practice of medicine. Orthopedic and reconstructive surgery has been an obvious area for development of 3D printer applications as the segmentation of bony anatomy to generate printable models is relatively straightforward. There are important issues that should be addressed when using 3D printed models for applications that may affect patient care; in particular the dimensional accuracy of the printed parts needs to be high to avoid poor decisions being made prior to surgery or therapeutic procedures. In this work, the dimensional accuracy of 3D printed vertebral bodies derived from CT data for a cadaver spine is compared with direct measurements on the ex-vivo vertebra and with measurements made on the 3D rendered vertebra using commercial 3D image processing software. The vertebra was printed on a consumer grade 3D printer using an additive print process using PLA (polylactic acid) filament. Measurements were made for 15 different anatomic features of the vertebral body, including vertebral body height, endplate width and depth, pedicle height and width, and spinal canal width and depth, among others. It is shown that for the segmentation and printing process used, the results of measurements made on the 3D printed vertebral body are substantially the same as those produced by direct measurement on the vertebra and measurements made on the 3D rendered vertebra.

  5. Rolling bearing feature frequency extraction using extreme average envelope decomposition

    NASA Astrophysics Data System (ADS)

    Shi, Kunju; Liu, Shulin; Jiang, Chao; Zhang, Hongli

    2015-12-01

    The vibration signal contains a wealth of sensitive information which reflects the running status of the equipment. It is one of the most important steps for precise diagnosis to decompose the signal and extracts the effective information properly. The traditional classical adaptive signal decomposition method, such as EMD, exists the problems of mode mixing, low decomposition accuracy etc. Aiming at those problems, EAED(extreme average envelope decomposition) method is presented based on EMD. EAED method has three advantages. Firstly, it is completed through midpoint envelopment method rather than using maximum and minimum envelopment respectively as used in EMD. Therefore, the average variability of the signal can be described accurately. Secondly, in order to reduce the envelope errors during the signal decomposition, replacing two envelopes with one envelope strategy is presented. Thirdly, the similar triangle principle is utilized to calculate the time of extreme average points accurately. Thus, the influence of sampling frequency on the calculation results can be significantly reduced. Experimental results show that EAED could separate out single frequency components from a complex signal gradually. EAED could not only isolate three kinds of typical bearing fault characteristic of vibration frequency components but also has fewer decomposition layers. EAED replaces quadratic enveloping to an envelope which ensuring to isolate the fault characteristic frequency under the condition of less decomposition layers. Therefore, the precision of signal decomposition is improved.

  6. 3D Modeling By Consolidation Of Independent Geometries Extracted From Point Clouds - The Case Of The Modeling Of The Turckheim's Chapel (Alsace, France)

    NASA Astrophysics Data System (ADS)

    Koehl, M.; Fabre, Ph.; Schlussel, B.

    2014-06-01

    Turckheim is a small town located in Alsace, north-east of France. In the heart of the Alsatian vineyard, this city has many historical monuments including its old church. To understand the effectiveness of the project described in this paper, it is important to have a look at the history of this church. Indeed there are many historical events that explain its renovation and even its partial reconstruction. The first mention of a christian sanctuary in Turckheim dates back to 898. It will be replaced in the 12th century by a roman church (chapel), which subsists today as the bell tower. Touched by a lightning in 1661, the tower then was enhanced. In 1736, it was repaired following damage sustained in a tornado. In 1791, the town installs an organ to the church. Last milestone, the church is destroyed by fire in 1978. The organ, like the heart of the church will then have to be again restored (1983) with a simplified architecture. From this heavy and rich past, it unfortunately and as it is often the case, remains only very few documents and information available apart from facts stated in some sporadic writings. And with regard to the geometry, the positioning, the physical characteristics of the initial building, there are very little indication. Some assumptions of positions and right-of-way were well issued by different historians or archaeologists. The acquisition and 3D modeling project must therefore provide the current state of the edifice to serve as the basis of new investigations and for the generation of new hypotheses on the locations and historical shapes of this church and its original chapel (Fig. 1)

  7. Distribution Driven Extraction and Tracking of Features for Time-varying Data Analysis.

    PubMed

    Dutta, Soumya; Shen, Han-Wei

    2016-01-01

    Effective analysis of features in time-varying data is essential in numerous scientific applications. Feature extraction and tracking are two important tasks scientists rely upon to get insights about the dynamic nature of the large scale time-varying data. However, often the complexity of the scientific phenomena only allows scientists to vaguely define their feature of interest. Furthermore, such features can have varying motion patterns and dynamic evolution over time. As a result, automatic extraction and tracking of features becomes a non-trivial task. In this work, we investigate these issues and propose a distribution driven approach which allows us to construct novel algorithms for reliable feature extraction and tracking with high confidence in the absence of accurate feature definition. We exploit two key properties of an object, motion and similarity to the target feature, and fuse the information gained from them to generate a robust feature-aware classification field at every time step. Tracking of features is done using such classified fields which enhances the accuracy and robustness of the proposed algorithm. The efficacy of our method is demonstrated by successfully applying it on several scientific data sets containing a wide range of dynamic time-varying features. PMID:26529731

  8. A Novel Framework for Extracting Visual Feature-Based Keyword Relationships from an Image Database

    NASA Astrophysics Data System (ADS)

    Katsurai, Marie; Ogawa, Takahiro; Haseyama, Miki

    In this paper, a novel framework for extracting visual feature-based keyword relationships from an image database is proposed. From the characteristic that a set of relevant keywords tends to have common visual features, the keyword relationships in a target image database are extracted by using the following two steps. First, the relationship between each keyword and its corresponding visual features is modeled by using a classifier. This step enables detection of visual features related to each keyword. In the second step, the keyword relationships are extracted from the obtained results. Specifically, in order to measure the relevance between two keywords, the proposed method removes visual features related to one keyword from training images and monitors the performance of the classifier obtained for the other keyword. This measurement is the biggest difference from other conventional methods that focus on only keyword co-occurrences or visual similarities. Results of experiments conducted using an image database showed the effectiveness of the proposed method.

  9. [Image Feature Extraction and Discriminant Analysis of Xinjiang Uygur Medicine Based on Color Histogram].

    PubMed

    Hamit, Murat; Yun, Weikang; Yan, Chuanbo; Kutluk, Abdugheni; Fang, Yang; Alip, Elzat

    2015-06-01

    Image feature extraction is an important part of image processing and it is an important field of research and application of image processing technology. Uygur medicine is one of Chinese traditional medicine and researchers pay more attention to it. But large amounts of Uygur medicine data have not been fully utilized. In this study, we extracted the image color histogram feature of herbal and zooid medicine of Xinjiang Uygur. First, we did preprocessing, including image color enhancement, size normalizition and color space transformation. Then we extracted color histogram feature and analyzed them with statistical method. And finally, we evaluated the classification ability of features by Bayes discriminant analysis. Experimental results showed that high accuracy for Uygur medicine image classification was obtained by using color histogram feature. This study would have a certain help for the content-based medical image retrieval for Xinjiang Uygur medicine. PMID:26485983

  10. Extracting full-field dynamic strain on a wind turbine rotor subjected to arbitrary excitations using 3D point tracking and a modal expansion technique

    NASA Astrophysics Data System (ADS)

    Baqersad, Javad; Niezrecki, Christopher; Avitabile, Peter

    2015-09-01

    Health monitoring of rotating structures such as wind turbines and helicopter rotors is generally performed using conventional sensors that provide a limited set of data at discrete locations near or on the hub. These sensors usually provide no data on the blades or inside them where failures might occur. Within this paper, an approach was used to extract the full-field dynamic strain on a wind turbine assembly subject to arbitrary loading conditions. A three-bladed wind turbine having 2.3-m long blades was placed in a semi-built-in boundary condition using a hub, a machining chuck, and a steel block. For three different test cases, the turbine was excited using (1) pluck testing, (2) random impacts on blades with three impact hammers, and (3) random excitation by a mechanical shaker. The response of the structure to the excitations was measured using three-dimensional point tracking. A pair of high-speed cameras was used to measure displacement of optical targets on the structure when the blades were vibrating. The measured displacements at discrete locations were expanded and applied to the finite element model of the structure to extract the full-field dynamic strain. The results of the paper show an excellent correlation between the strain predicted using the proposed approach and the strain measured with strain-gages for each of the three loading conditions. The approach used in this paper to predict the strain showed higher accuracy than the digital image correlation technique. The new expansion approach is able to extract dynamic strain all over the entire structure, even inside the structure beyond the line of sight of the measurement system. Because the method is based on a non-contacting measurement approach, it can be readily applied to a variety of structures having different boundary and operating conditions, including rotating blades.

  11. A featureless approach to 3D polyhedral building modeling from aerial images.

    PubMed

    Hammoudi, Karim; Dornaika, Fadi

    2011-01-01

    This paper presents a model-based approach for reconstructing 3D polyhedral building models from aerial images. The proposed approach exploits some geometric and photometric properties resulting from the perspective projection of planar structures. Data are provided by calibrated aerial images. The novelty of the approach lies in its featurelessness and in its use of direct optimization based on image rawbrightness. The proposed framework avoids feature extraction and matching. The 3D polyhedral model is directly estimated by optimizing an objective function that combines an image-based dissimilarity measure and a gradient score over several aerial images. The optimization process is carried out by the Differential Evolution algorithm. The proposed approach is intended to provide more accurate 3D reconstruction than feature-based approaches. Fast 3D model rectification and updating can take advantage of the proposed method. Several results and evaluations of performance from real and synthetic images show the feasibility and robustness of the proposed approach. PMID:22346575

  12. A Featureless Approach to 3D Polyhedral Building Modeling from Aerial Images

    PubMed Central

    Hammoudi, Karim; Dornaika, Fadi

    2011-01-01

    This paper presents a model-based approach for reconstructing 3D polyhedral building models from aerial images. The proposed approach exploits some geometric and photometric properties resulting from the perspective projection of planar structures. Data are provided by calibrated aerial images. The novelty of the approach lies in its featurelessness and in its use of direct optimization based on image rawbrightness. The proposed framework avoids feature extraction and matching. The 3D polyhedral model is directly estimated by optimizing an objective function that combines an image-based dissimilarity measure and a gradient score over several aerial images. The optimization process is carried out by the Differential Evolution algorithm. The proposed approach is intended to provide more accurate 3D reconstruction than feature-based approaches. Fast 3D model rectification and updating can take advantage of the proposed method. Several results and evaluations of performance from real and synthetic images show the feasibility and robustness of the proposed approach. PMID:22346575

  13. Multiviewer 3D monitor

    NASA Astrophysics Data System (ADS)

    Kostrzewski, Andrew A.; Aye, Tin M.; Kim, Dai Hyun; Esterkin, Vladimir; Savant, Gajendra D.

    1998-09-01

    Physical Optics Corporation has developed an advanced 3-D virtual reality system for use with simulation tools for training technical and military personnel. This system avoids such drawbacks of other virtual reality (VR) systems as eye fatigue, headaches, and alignment for each viewer, all of which are due to the need to wear special VR goggles. The new system is based on direct viewing of an interactive environment. This innovative holographic multiplexed screen technology makes it unnecessary for the viewer to wear special goggles.

  14. 3D Audio System

    NASA Technical Reports Server (NTRS)

    1992-01-01

    Ames Research Center research into virtual reality led to the development of the Convolvotron, a high speed digital audio processing system that delivers three-dimensional sound over headphones. It consists of a two-card set designed for use with a personal computer. The Convolvotron's primary application is presentation of 3D audio signals over headphones. Four independent sound sources are filtered with large time-varying filters that compensate for motion. The perceived location of the sound remains constant. Possible applications are in air traffic control towers or airplane cockpits, hearing and perception research and virtual reality development.

  15. Novel 3D ultrasound image-based biomarkers based on a feature selection from a 2D standardized vessel wall thickness map: a tool for sensitive assessment of therapies for carotid atherosclerosis

    NASA Astrophysics Data System (ADS)

    Chiu, Bernard; Li, Bing; Chow, Tommy W. S.

    2013-09-01

    With the advent of new therapies and management strategies for carotid atherosclerosis, there is a parallel need for measurement tools or biomarkers to evaluate the efficacy of these new strategies. 3D ultrasound has been shown to provide reproducible measurements of plaque area/volume and vessel wall volume. However, since carotid atherosclerosis is a focal disease that predominantly occurs at bifurcations, biomarkers based on local plaque change may be more sensitive than global volumetric measurements in demonstrating efficacy of new therapies. The ultimate goal of this paper is to develop a biomarker that is based on the local distribution of vessel-wall-plus-plaque thickness change (VWT-Change) that has occurred during the course of a clinical study. To allow comparison between different treatment groups, the VWT-Change distribution of each subject must first be mapped to a standardized domain. In this study, we developed a technique to map the 3D VWT-Change distribution to a 2D standardized template. We then applied a feature selection technique to identify regions on the 2D standardized map on which subjects in different treatment groups exhibit greater difference in VWT-Change. The proposed algorithm was applied to analyse the VWT-Change of 20 subjects in a placebo-controlled study of the effect of atorvastatin (Lipitor). The average VWT-Change for each subject was computed (i) over all points in the 2D map and (ii) over feature points only. For the average computed over all points, 97 subjects per group would be required to detect an effect size of 25% that of atorvastatin in a six-month study. The sample size is reduced to 25 subjects if the average were computed over feature points only. The introduction of this sensitive quantification technique for carotid atherosclerosis progression/regression would allow many proof-of-principle studies to be performed before a more costly and longer study involving a larger population is held to confirm the treatment

  16. Spectral Regression Based Fault Feature Extraction for Bearing Accelerometer Sensor Signals

    PubMed Central

    Xia, Zhanguo; Xia, Shixiong; Wan, Ling; Cai, Shiyu

    2012-01-01

    Bearings are not only the most important element but also a common source of failures in rotary machinery. Bearing fault prognosis technology has been receiving more and more attention recently, in particular because it plays an increasingly important role in avoiding the occurrence of accidents. Therein, fault feature extraction (FFE) of bearing accelerometer sensor signals is essential to highlight representative features of bearing conditions for machinery fault diagnosis and prognosis. This paper proposes a spectral regression (SR)-based approach for fault feature extraction from original features including time, frequency and time-frequency domain features of bearing accelerometer sensor signals. SR is a novel regression framework for efficient regularized subspace learning and feature extraction technology, and it uses the least squares method to obtain the best projection direction, rather than computing the density matrix of features, so it also has the advantage in dimensionality reduction. The effectiveness of the SR-based method is validated experimentally by applying the acquired vibration signals data to bearings. The experimental results indicate that SR can reduce the computation cost and preserve more structure information about different bearing faults and severities, and it is demonstrated that the proposed feature extraction scheme has an advantage over other similar approaches. PMID:23202017

  17. Spectral regression based fault feature extraction for bearing accelerometer sensor signals.

    PubMed

    Xia, Zhanguo; Xia, Shixiong; Wan, Ling; Cai, Shiyu

    2012-01-01

    Bearings are not only the most important element but also a common source of failures in rotary machinery. Bearing fault prognosis technology has been receiving more and more attention recently, in particular because it plays an increasingly important role in avoiding the occurrence of accidents. Therein, fault feature extraction (FFE) of bearing accelerometer sensor signals is essential to highlight representative features of bearing conditions for machinery fault diagnosis and prognosis. This paper proposes a spectral regression (SR)-based approach for fault feature extraction from original features including time, frequency and time-frequency domain features of bearing accelerometer sensor signals. SR is a novel regression framework for efficient regularized subspace learning and feature extraction technology, and it uses the least squares method to obtain the best projection direction, rather than computing the density matrix of features, so it also has the advantage in dimensionality reduction. The effectiveness of the SR-based method is validated experimentally by applying the acquired vibration signals data to bearings. The experimental results indicate that SR can reduce the computation cost and preserve more structure information about different bearing faults and severities, and it is demonstrated that the proposed feature extraction scheme has an advantage over other similar approaches. PMID:23202017

  18. Using outcrop observations, 3D discrete feature network (DFN) fluid-flow simulations, and subsurface data to constrain the impact of normal faults and opening mode fractures on fluid flow in an active asphalt mine

    NASA Astrophysics Data System (ADS)

    Wilson, C. E.; Aydin, A.; Durlofsky, L.; Karimi-Fard, M.; Brownlow, D. T.

    2008-12-01

    An active quarry near Uvalde, TX which mines asphaltic limestone from the Anacacho Formation offers an ideal setting to study fluid-flow in fractured and faulted carbonate rocks. Semi-3D exposures of normal faults and fractures in addition to visual evidence of asphalt concentrations in the quarry help constrain relationships between geologic structures and the flow and transport of hydrocarbons. Furthermore, a subsurface dataset which includes thin sections and measured asphalt concentration from the surrounding region provides a basis to estimate asphalt concentrations and constrain the depositional architecture of both the previously mined portions of the quarry and the un-mined surrounding rock volume. We characterized a series of normal faults and opening mode fractures at the quarry and documented a correlation between the intensity and distribution of these structures with increased concentrations of asphalt. The three-dimensional depositional architecture of the Anacacho Formation was characterized using the subsurface thin sections. Then outcrop exposures of faults, fractured beds, and stratigraphic contacts were mapped and their three-dimensional positions were recorded with differential gps devices. These two datasets were assimilated and a quarry-scale, geologically realistic, three-dimensional Discrete Feature Network (DFN) which represents the geometries and material properties of the matrix, normal faults, and fractures within the quarry was constructed. We then performed two-point flux, control-volume finite- difference fluid-flow simulations with the DFN to investigate the 3D flow and transport of fluids. The results were compared and contrasted with available asphalt concentration estimates from the mine and the aforementioned data from the surrounding drill cores.

  19. Recording stereoscopic 3D neurosurgery with a head-mounted 3D camera system.

    PubMed

    Lee, Brian; Chen, Brian R; Chen, Beverly B; Lu, James Y; Giannotta, Steven L

    2015-06-01

    Stereoscopic three-dimensional (3D) imaging can present more information to the viewer and further enhance the learning experience over traditional two-dimensional (2D) video. Most 3D surgical videos are recorded from the operating microscope and only feature the crux, or the most important part of the surgery, leaving out other crucial parts of surgery including the opening, approach, and closing of the surgical site. In addition, many other surgeries including complex spine, trauma, and intensive care unit procedures are also rarely recorded. We describe and share our experience with a commercially available head-mounted stereoscopic 3D camera system to obtain stereoscopic 3D recordings of these seldom recorded aspects of neurosurgery. The strengths and limitations of using the GoPro(®) 3D system as a head-mounted stereoscopic 3D camera system in the operating room are reviewed in detail. Over the past several years, we have recorded in stereoscopic 3D over 50 cranial and spinal surgeries and created a library for education purposes. We have found the head-mounted stereoscopic 3D camera system to be a valuable asset to supplement 3D footage from a 3D microscope. We expect that these comprehensive 3D surgical videos will become an important facet of resident education and ultimately lead to improved patient care. PMID:25620087

  20. RAG-3D: a search tool for RNA 3D substructures.

    PubMed

    Zahran, Mai; Sevim Bayrak, Cigdem; Elmetwaly, Shereef; Schlick, Tamar

    2015-10-30

    To address many challenges in RNA structure/function prediction, the characterization of RNA's modular architectural units is required. Using the RNA-As-Graphs (RAG) database, we have previously explored the existence of secondary structure (2D) submotifs within larger RNA structures. Here we present RAG-3D-a dataset of RNA tertiary (3D) structures and substructures plus a web-based search tool-designed to exploit graph representations of RNAs for the goal of searching for similar 3D structural fragments. The objects in RAG-3D consist of 3D structures translated into 3D graphs, cataloged based on the connectivity between their secondary structure elements. Each graph is additionally described in terms of its subgraph building blocks. The RAG-3D search tool then compares a query RNA 3D structure to those in the database to obtain structurally similar structures and substructures. This comparison reveals conserved 3D RNA features and thus may suggest functional connections. Though RNA search programs based on similarity in sequence, 2D, and/or 3D structural elements are available, our graph-based search tool may be advantageous for illuminating similarities that are not obvious; using motifs rather than sequence space also reduces search times considerably. Ultimately, such substructuring could be useful for RNA 3D structure prediction, structure/function inference and inverse folding. PMID:26304547

  1. 3D Surgical Simulation

    PubMed Central

    Cevidanes, Lucia; Tucker, Scott; Styner, Martin; Kim, Hyungmin; Chapuis, Jonas; Reyes, Mauricio; Proffit, William; Turvey, Timothy; Jaskolka, Michael

    2009-01-01

    This paper discusses the development of methods for computer-aided jaw surgery. Computer-aided jaw surgery allows us to incorporate the high level of precision necessary for transferring virtual plans into the operating room. We also present a complete computer-aided surgery (CAS) system developed in close collaboration with surgeons. Surgery planning and simulation include construction of 3D surface models from Cone-beam CT (CBCT), dynamic cephalometry, semi-automatic mirroring, interactive cutting of bone and bony segment repositioning. A virtual setup can be used to manufacture positioning splints for intra-operative guidance. The system provides further intra-operative assistance with the help of a computer display showing jaw positions and 3D positioning guides updated in real-time during the surgical procedure. The CAS system aids in dealing with complex cases with benefits for the patient, with surgical practice, and for orthodontic finishing. Advanced software tools for diagnosis and treatment planning allow preparation of detailed operative plans, osteotomy repositioning, bone reconstructions, surgical resident training and assessing the difficulties of the surgical procedures prior to the surgery. CAS has the potential to make the elaboration of the surgical plan a more flexible process, increase the level of detail and accuracy of the plan, yield higher operative precision and control, and enhance documentation of cases. Supported by NIDCR DE017727, and DE018962 PMID:20816308

  2. 3D-patterned polymer brush surfaces

    NASA Astrophysics Data System (ADS)

    Zhou, Xuechang; Liu, Xuqing; Xie, Zhuang; Zheng, Zijian

    2011-12-01

    Polymer brush-based three-dimensional (3D) structures are emerging as a powerful platform to engineer a surface by providing abundant spatially distributed chemical and physical properties. In this feature article, we aim to give a summary of the recent progress on the fabrication of 3D structures with polymer brushes, with a particular focus on the micro- and nanoscale. We start with a brief introduction on polymer brushes and the challenges to prepare their 3D structures. Then, we highlight the recent advances of the fabrication approaches on the basis of traditional polymerization time and grafting density strategies, and a recently developed feature density strategy. Finally, we provide some perspective outlooks on the future directions of engineering the 3D structures with polymer brushes.

  3. Feature Extraction on Brain Computer Interfaces using Discrete Dyadic Wavelet Transform: Preliminary Results

    NASA Astrophysics Data System (ADS)

    Gareis, I.; Gentiletti, G.; Acevedo, R.; Rufiner, L.

    2011-09-01

    The purpose of this work is to evaluate different feature extraction alternatives to detect the event related evoked potential signal on brain computer interfaces, trying to minimize the time employed and the classification error, in terms of sensibility and specificity of the method, looking for alternatives to coherent averaging. In this context the results obtained performing the feature extraction using discrete dyadic wavelet transform using different mother wavelets are presented. For the classification a single layer perceptron was used. The results obtained with and without the wavelet decomposition were compared; showing an improvement on the classification rate, the specificity and the sensibility for the feature vectors obtained using some mother wavelets.

  4. Invariant feature extraction for color image mosaic by graph card processing

    NASA Astrophysics Data System (ADS)

    Liu, Jin; Chen, Lin; Li, Deren

    2009-10-01

    Image mosaic can be widely used in remote measuring, scout in battlefield and Panasonic image demonstration. In this project, we find a general method for video (or sequence images) mosaic by techniques, such as extracting invariant features, gpu processing, multi-color feature selection, ransac algorithm for homograph matching. In order to match the image sequence automatically without influence of rotation, scale and contrast transform, local invariant feature descriptor have been extracted by graph card unit. The gpu mosaic algorithm performs very well that can be compare to slow CPU version of mosaic program with little cost time.

  5. Biometric person authentication method using features extracted from pen holding style

    NASA Astrophysics Data System (ADS)

    Hashimoto, Yuuki; Muramatsu, Daigo; Ogata, Hiroyuki

    2010-04-01

    The manner of holding a pen is distinctive among people. Therefore, pen holding style is useful for person authentication. In this paper, we propose a biometric person authentication method using features extracted from images of pen holding style. Images of the pen holding style are captured by a camera, and several features are extracted from the captured images. These features are compared with a reference dataset to calculate dissimilarity scores, and these scores are combined for verification using a three-layer perceptron. Preliminary experiments were performed by using a private database. The proposed system yielded an equal error rate (EER) of 2.6%.

  6. An Improved Version of TOPAZ 3D

    SciTech Connect

    Krasnykh, Anatoly

    2003-07-29

    An improved version of the TOPAZ 3D gun code is presented as a powerful tool for beam optics simulation. In contrast to the previous version of TOPAZ 3D, the geometry of the device under test is introduced into TOPAZ 3D directly from a CAD program, such as Solid Edge or AutoCAD. In order to have this new feature, an interface was developed, using the GiD software package as a meshing code. The article describes this method with two models to illustrate the results.

  7. Ultrasonic echo waveshape features extraction based on QPSO-matching pursuit for online wear debris discrimination

    NASA Astrophysics Data System (ADS)

    Xu, Chao; Zhang, Peilin; Wang, Huaiguang; Li, Yining; Lv, Chun

    2015-08-01

    The ultrasonic echoes reflected from debris in lubricant contain a lot of useful information, which can represent the size, material and geometric characteristics of the debris. Our preliminary simulation investigations and physical model analysis results show that the waveshape features are feasible and essential to discriminate debris in lubricant. An accurate waveshape features extraction method of debris echoes is presented based on the matching pursuit (MP). The dictionary of Gabor functions, which is suitable for ultrasonic signal processing, is adopted for MP. To seek faster and more accurate calculation of MP, quantum-behaved particle swarm optimization (QPSO) is introduced to optimize the MP algorithm. The simulation and experimental results reveal that the proposed method can effectively extract the waveshape features of debris echoes and air bubble echoes. Utilizing the extracted waveshape features, the debris with different shapes and air bubble can be distinguished.

  8. Remote measurement methods for 3-D modeling purposes using BAE Systems' Software

    NASA Astrophysics Data System (ADS)

    Walker, Stewart; Pietrzak, Arleta

    2015-06-01

    Efficient, accurate data collection from imagery is the key to an economical generation of useful geospatial products. Incremental developments of traditional geospatial data collection and the arrival of new image data sources cause new software packages to be created and existing ones to be adjusted to enable such data to be processed. In the past, BAE Systems' digital photogrammetric workstation, SOCET SET®, met fin de siècle expectations in data processing and feature extraction. Its successor, SOCET GXP®, addresses today's photogrammetric requirements and new data sources. SOCET GXP is an advanced workstation for mapping and photogrammetric tasks, with automated functionality for triangulation, Digital Elevation Model (DEM) extraction, orthorectification and mosaicking, feature extraction and creation of 3-D models with texturing. BAE Systems continues to add sensor models to accommodate new image sources, in response to customer demand. New capabilities added in the latest version of SOCET GXP facilitate modeling, visualization and analysis of 3-D features.

  9. Recognition of a Phase-Sensitivity OTDR Sensing System Based on Morphologic Feature Extraction

    PubMed Central

    Sun, Qian; Feng, Hao; Yan, Xueying; Zeng, Zhoumo

    2015-01-01

    This paper proposes a novel feature extraction method for intrusion event recognition within a phase-sensitive optical time-domain reflectometer (Φ-OTDR) sensing system. Feature extraction of time domain signals in these systems is time-consuming and may lead to inaccuracies due to noise disturbances. The recognition accuracy and speed of current systems cannot meet the requirements of Φ-OTDR online vibration monitoring systems. In the method proposed in this paper, the time-space domain signal is used for feature extraction instead of the time domain signal. Feature vectors are obtained from morphologic features of time-space domain signals. A scatter matrix is calculated for the feature selection. Experiments show that the feature extraction method proposed in this paper can greatly improve recognition accuracies, with a lower computation time than traditional methods, i.e., a recognition accuracy of 97.8% can be achieved with a recognition time of below 1 s, making it is very suitable for Φ-OTDR system online vibration monitoring. PMID:26131671

  10. Fault diagnosis of rotating machinery with a novel statistical feature extraction and evaluation method

    NASA Astrophysics Data System (ADS)

    Li, Wei; Zhu, Zhencai; Jiang, Fan; Zhou, Gongbo; Chen, Guoan

    2015-01-01

    Fault diagnosis of rotating machinery is receiving more and more attentions. Vibration signals of rotating machinery are commonly analyzed to extract features of faults, and the features are identified with classifiers, e.g. artificial neural networks (ANNs) and support vector machines (SVMs). Due to nonlinear behaviors and unknown noises in machinery, the extracted features are varying from sample to sample, which may result in false classifications. It is also difficult to analytically ensure the accuracy of fault diagnosis. In this paper, a feature extraction and evaluation method is proposed for fault diagnosis of rotating machinery. Based on the central limit theory, an extraction procedure is given to obtain the statistical features with the help of existing signal processing tools. The obtained statistical features approximately obey normal distributions. They can significantly improve the performance of fault classification, and it is verified by taking ANN and SVM classifiers as examples. Then the statistical features are evaluated with a decoupling technique and compared with thresholds to make the decision on fault classification. The proposed evaluation method only requires simple algebraic computation, and the accuracy of fault classification can be analytically guaranteed in terms of the so-called false classification rate (FCR). An experiment is carried out to verify the effectiveness of the proposed method, where the unbalanced fault of rotor, inner race fault, outer race fault and ball fault of bearings are considered.

  11. 3D Reconstruction of Coronary Artery Vascular Smooth Muscle Cells

    PubMed Central

    Luo, Tong; Chen, Huan; Kassab, Ghassan S.

    2016-01-01

    Aims The 3D geometry of individual vascular smooth muscle cells (VSMCs), which are essential for understanding the mechanical function of blood vessels, are currently not available. This paper introduces a new 3D segmentation algorithm to determine VSMC morphology and orientation. Methods and Results A total of 112 VSMCs from six porcine coronary arteries were used in the analysis. A 3D semi-automatic segmentation method was developed to reconstruct individual VSMCs from cell clumps as well as to extract the 3D geometry of VSMCs. A new edge blocking model was introduced to recognize cell boundary while an edge growing was developed for optimal interpolation and edge verification. The proposed methods were designed based on Region of Interest (ROI) selected by user and interactive responses of limited key edges. Enhanced cell boundary features were used to construct the cell’s initial boundary for further edge growing. A unified framework of morphological parameters (dimensions and orientations) was proposed for the 3D volume data. Virtual phantom was designed to validate the tilt angle measurements, while other parameters extracted from 3D segmentations were compared with manual measurements to assess the accuracy of the algorithm. The length, width and thickness of VSMCs were 62.9±14.9μm, 4.6±0.6μm and 6.2±1.8μm (mean±SD). In longitudinal-circumferential plane of blood vessel, VSMCs align off the circumferential direction with two mean angles of -19.4±9.3° and 10.9±4.7°, while an out-of-plane angle (i.e., radial tilt angle) was found to be 8±7.6° with median as 5.7°. Conclusions A 3D segmentation algorithm was developed to reconstruct individual VSMCs of blood vessel walls based on optical image stacks. The results were validated by a virtual phantom and manual measurement. The obtained 3D geometries can be utilized in mathematical models and leads a better understanding of vascular mechanical properties and function. PMID:26882342

  12. 3D polarimetric purity

    NASA Astrophysics Data System (ADS)

    Gil, José J.; San José, Ignacio

    2010-11-01

    From our previous definition of the indices of polarimetric purity for 3D light beams [J.J. Gil, J.M. Correas, P.A. Melero and C. Ferreira, Monogr. Semin. Mat. G. de Galdeano 31, 161 (2004)], an analysis of their geometric and physical interpretation is presented. It is found that, in agreement with previous results, the first parameter is a measure of the degree of polarization, whereas the second parameter (called the degree of directionality) is a measure of the mean angular aperture of the direction of propagation of the corresponding light beam. This pair of invariant, non-dimensional, indices of polarimetric purity contains complete information about the polarimetric purity of a light beam. The overall degree of polarimetric purity is obtained as a weighted quadratic average of the degree of polarization and the degree of directionality.

  13. 3D field harmonics

    SciTech Connect

    Caspi, S.; Helm, M.; Laslett, L.J.

    1991-03-30

    We have developed an harmonic representation for the three dimensional field components within the windings of accelerator magnets. The form by which the field is presented is suitable for interfacing with other codes that make use of the 3D field components (particle tracking and stability). The field components can be calculated with high precision and reduced cup time at any location (r,{theta},z) inside the magnet bore. The same conductor geometry which is used to simulate line currents is also used in CAD with modifications more readily available. It is our hope that the format used here for magnetic fields can be used not only as a means of delivering fields but also as a way by which beam dynamics can suggest correction to the conductor geometry. 5 refs., 70 figs.

  14. 'Bonneville' in 3-D!

    NASA Technical Reports Server (NTRS)

    2004-01-01

    The Mars Exploration Rover Spirit took this 3-D navigation camera mosaic of the crater called 'Bonneville' after driving approximately 13 meters (42.7 feet) to get a better vantage point. Spirit's current position is close enough to the edge to see the interior of the crater, but high enough and far enough back to get a view of all of the walls. Because scientists and rover controllers are so pleased with this location, they will stay here for at least two more martian days, or sols, to take high resolution panoramic camera images of 'Bonneville' in its entirety. Just above the far crater rim, on the left side, is the rover's heatshield, which is visible as a tiny reflective speck.

  15. Efficacy Evaluation of Different Wavelet Feature Extraction Methods on Brain MRI Tumor Detection

    NASA Astrophysics Data System (ADS)

    Nabizadeh, Nooshin; John, Nigel; Kubat, Miroslav

    2014-03-01

    Automated Magnetic Resonance Imaging brain tumor detection and segmentation is a challenging task. Among different available methods, feature-based methods are very dominant. While many feature extraction techniques have been employed, it is still not quite clear which of feature extraction methods should be preferred. To help improve the situation, we present the results of a study in which we evaluate the efficiency of using different wavelet transform features extraction methods in brain MRI abnormality detection. Applying T1-weighted brain image, Discrete Wavelet Transform (DWT), Discrete Wavelet Packet Transform (DWPT), Dual Tree Complex Wavelet Transform (DTCWT), and Complex Morlet Wavelet Transform (CMWT) methods are applied to construct the feature pool. Three various classifiers as Support Vector Machine, K Nearest Neighborhood, and Sparse Representation-Based Classifier are applied and compared for classifying the selected features. The results show that DTCWT and CMWT features classified with SVM, result in the highest classification accuracy, proving of capability of wavelet transform features to be informative in this application.

  16. Nonparametric feature extraction for classification of hyperspectral images with limited training samples

    NASA Astrophysics Data System (ADS)

    Kianisarkaleh, Azadeh; Ghassemian, Hassan

    2016-09-01

    Feature extraction plays a crucial role in improvement of hyperspectral images classification. Nonparametric feature extraction methods show better performance compared to parametric ones when distribution of classes is non normal-like. Moreover, they can extract more features than parametric methods do. In this paper, a new nonparametric linear feature extraction method is introduced for classification of hyperspectral images. The proposed method has no free parameter and its novelty can be discussed in two parts. First, neighbor samples are specified by using Parzen window idea for determining local mean. Second, two new weighting functions are used. Samples close to class boundaries will have more weight in the between-class scatter matrix formation and samples close to class mean will have more weight in the within-class scatter matrix formation. The experimental results on three real hyperspectral data sets, Indian Pines, Salinas and Pavia University, demonstrate that the proposed method has better performance in comparison with some other nonparametric and parametric feature extraction methods.

  17. Enhanced Protein Fold Prediction Method Through a Novel Feature Extraction Technique.

    PubMed

    Wei, Leyi; Liao, Minghong; Gao, Xing; Zou, Quan

    2015-09-01

    Information of protein 3-dimensional (3D) structures plays an essential role in molecular biology, cell biology, biomedicine, and drug design. Protein fold prediction is considered as an immediate step for deciphering the protein 3D structures. Therefore, protein fold prediction is one of fundamental problems in structural bioinformatics. Recently, numerous taxonomic methods have been developed for protein fold prediction. Unfortunately, the overall prediction accuracies achieved by existing taxonomic methods are not satisfactory although much progress has been made. To address this problem, we propose a novel taxonomic method, called PFPA, which is featured by combining a novel feature set through an ensemble classifier. Particularly, the sequential evolution information from the profiles of PSI-BLAST and the local and global secondary structure information from the profiles of PSI-PRED are combined to construct a comprehensive feature set. Experimental results demonstrate that PFPA outperforms the state-of-the-art predictors. To be specific, when tested on the independent testing set of a benchmark dataset, PFPA achieves an overall accuracy of 73.6%, which is the leading accuracy ever reported. Moreover, PFPA performs well without significant performance degradation on three updated large-scale datasets, indicating the robustness and generalization of PFPA. Currently, a webserver that implements PFPA is freely available on http://121.192.180.204:8080/PFPA/Index.html. PMID:26335556

  18. RAG-3D: A search tool for RNA 3D substructures

    DOE PAGESBeta

    Zahran, Mai; Sevim Bayrak, Cigdem; Elmetwaly, Shereef; Schlick, Tamar

    2015-08-24

    In this study, to address many challenges in RNA structure/function prediction, the characterization of RNA's modular architectural units is required. Using the RNA-As-Graphs (RAG) database, we have previously explored the existence of secondary structure (2D) submotifs within larger RNA structures. Here we present RAG-3D—a dataset of RNA tertiary (3D) structures and substructures plus a web-based search tool—designed to exploit graph representations of RNAs for the goal of searching for similar 3D structural fragments. The objects in RAG-3D consist of 3D structures translated into 3D graphs, cataloged based on the connectivity between their secondary structure elements. Each graph is additionally describedmore » in terms of its subgraph building blocks. The RAG-3D search tool then compares a query RNA 3D structure to those in the database to obtain structurally similar structures and substructures. This comparison reveals conserved 3D RNA features and thus may suggest functional connections. Though RNA search programs based on similarity in sequence, 2D, and/or 3D structural elements are available, our graph-based search tool may be advantageous for illuminating similarities that are not obvious; using motifs rather than sequence space also reduces search times considerably. Ultimately, such substructuring could be useful for RNA 3D structure prediction, structure/function inference and inverse folding.« less

  19. RAG-3D: A search tool for RNA 3D substructures

    SciTech Connect

    Zahran, Mai; Sevim Bayrak, Cigdem; Elmetwaly, Shereef; Schlick, Tamar

    2015-08-24

    In this study, to address many challenges in RNA structure/function prediction, the characterization of RNA's modular architectural units is required. Using the RNA-As-Graphs (RAG) database, we have previously explored the existence of secondary structure (2D) submotifs within larger RNA structures. Here we present RAG-3D—a dataset of RNA tertiary (3D) structures and substructures plus a web-based search tool—designed to exploit graph representations of RNAs for the goal of searching for similar 3D structural fragments. The objects in RAG-3D consist of 3D structures translated into 3D graphs, cataloged based on the connectivity between their secondary structure elements. Each graph is additionally described in terms of its subgraph building blocks. The RAG-3D search tool then compares a query RNA 3D structure to those in the database to obtain structurally similar structures and substructures. This comparison reveals conserved 3D RNA features and thus may suggest functional connections. Though RNA search programs based on similarity in sequence, 2D, and/or 3D structural elements are available, our graph-based search tool may be advantageous for illuminating similarities that are not obvious; using motifs rather than sequence space also reduces search times considerably. Ultimately, such substructuring could be useful for RNA 3D structure prediction, structure/function inference and inverse folding.

  20. RAG-3D: a search tool for RNA 3D substructures

    PubMed Central

    Zahran, Mai; Sevim Bayrak, Cigdem; Elmetwaly, Shereef; Schlick, Tamar

    2015-01-01

    To address many challenges in RNA structure/function prediction, the characterization of RNA's modular architectural units is required. Using the RNA-As-Graphs (RAG) database, we have previously explored the existence of secondary structure (2D) submotifs within larger RNA structures. Here we present RAG-3D—a dataset of RNA tertiary (3D) structures and substructures plus a web-based search tool—designed to exploit graph representations of RNAs for the goal of searching for similar 3D structural fragments. The objects in RAG-3D consist of 3D structures translated into 3D graphs, cataloged based on the connectivity between their secondary structure elements. Each graph is additionally described in terms of its subgraph building blocks. The RAG-3D search tool then compares a query RNA 3D structure to those in the database to obtain structurally similar structures and substructures. This comparison reveals conserved 3D RNA features and thus may suggest functional connections. Though RNA search programs based on similarity in sequence, 2D, and/or 3D structural elements are available, our graph-based search tool may be advantageous for illuminating similarities that are not obvious; using motifs rather than sequence space also reduces search times considerably. Ultimately, such substructuring could be useful for RNA 3D structure prediction, structure/function inference and inverse folding. PMID:26304547

  1. Feature extraction based on contourlet transform and its application to surface inspection of metals

    NASA Astrophysics Data System (ADS)

    Ai, Yonghao; Xu, Ke

    2012-11-01

    Surface defects that affect the quality of metals are an important factor. Machine vision systems commonly perform surface inspection, and feature extraction of defects is essential. The rapidity and universality of the algorithm are two crucial issues in actual application. A new method of feature extraction based on contourlet transform and kernel locality preserving projections is proposed to extract sufficient and effective features from metal surface images. Image information at certain direction is important to recognition of defects, and contourlet transform is introduced for its flexible direction setting. Images of metal surfaces are decomposed into multiple directional subbands with contourlet transform. Then features of all subbands are extracted and combined into a high-dimensional feature vector, which is reduced to a low-dimensional feature vector by kernel locality preserving projections. The method is tested with a Brodatz database and two surface defect databases from industrial surface-inspection systems of continuous casting slabs and aluminum strips. Experimental results show that the proposed method performs better than the other three methods in accuracy and efficiency. The total classification rates of surface defects of continuous casting slabs and aluminum strips are up to 93.55% and 92.5%, respectively.

  2. Diffractive optical element for creating visual 3D images.

    PubMed

    Goncharsky, Alexander; Goncharsky, Anton; Durlevich, Svyatoslav

    2016-05-01

    A method is proposed to compute and synthesize the microrelief of a diffractive optical element to produce a new visual security feature - the vertical 3D/3D switch effect. The security feature consists in the alternation of two 3D color images when the diffractive element is tilted up/down. Optical security elements that produce the new security feature are synthesized using electron-beam technology. Sample optical security elements are manufactured that produce 3D to 3D visual switch effect when illuminated by white light. Photos and video records of the vertical 3D/3D switch effect of real optical elements are presented. The optical elements developed can be replicated using standard equipment employed for manufacturing security holograms. The new optical security feature is easy to control visually, safely protected against counterfeit, and designed to protect banknotes, documents, ID cards, etc. PMID:27137530

  3. A Relation Extraction Framework for Biomedical Text Using Hybrid Feature Set.

    PubMed

    Muzaffar, Abdul Wahab; Azam, Farooque; Qamar, Usman

    2015-01-01

    The information extraction from unstructured text segments is a complex task. Although manual information extraction often produces the best results, it is harder to manage biomedical data extraction manually because of the exponential increase in data size. Thus, there is a need for automatic tools and techniques for information extraction in biomedical text mining. Relation extraction is a significant area under biomedical information extraction that has gained much importance in the last two decades. A lot of work has been done on biomedical relation extraction focusing on rule-based and machine learning techniques. In the last decade, the focus has changed to hybrid approaches showing better results. This research presents a hybrid feature set for classification of relations between biomedical entities. The main contribution of this research is done in the semantic feature set where verb phrases are ranked using Unified Medical Language System (UMLS) and a ranking algorithm. Support Vector Machine and Naïve Bayes, the two effective machine learning techniques, are used to classify these relations. Our approach has been validated on the standard biomedical text corpus obtained from MEDLINE 2001. Conclusively, it can be articulated that our framework outperforms all state-of-the-art approaches used for relation extraction on the same corpus. PMID:26347797

  4. A Relation Extraction Framework for Biomedical Text Using Hybrid Feature Set

    PubMed Central

    Muzaffar, Abdul Wahab; Azam, Farooque; Qamar, Usman

    2015-01-01

    The information extraction from unstructured text segments is a complex task. Although manual information extraction often produces the best results, it is harder to manage biomedical data extraction manually because of the exponential increase in data size. Thus, there is a need for automatic tools and techniques for information extraction in biomedical text mining. Relation extraction is a significant area under biomedical information extraction that has gained much importance in the last two decades. A lot of work has been done on biomedical relation extraction focusing on rule-based and machine learning techniques. In the last decade, the focus has changed to hybrid approaches showing better results. This research presents a hybrid feature set for classification of relations between biomedical entities. The main contribution of this research is done in the semantic feature set where verb phrases are ranked using Unified Medical Language System (UMLS) and a ranking algorithm. Support Vector Machine and Naïve Bayes, the two effective machine learning techniques, are used to classify these relations. Our approach has been validated on the standard biomedical text corpus obtained from MEDLINE 2001. Conclusively, it can be articulated that our framework outperforms all state-of-the-art approaches used for relation extraction on the same corpus. PMID:26347797

  5. Focal-plane CMOS wavelet feature extraction for real-time pattern recognition

    NASA Astrophysics Data System (ADS)

    Olyaei, Ashkan; Genov, Roman

    2005-09-01

    Kernel-based pattern recognition paradigms such as support vector machines (SVM) require computationally intensive feature extraction methods for high-performance real-time object detection in video. The CMOS sensory parallel processor architecture presented here computes delta-sigma (ΔΣ)-modulated Haar wavelet transform on the focal plane in real time. The active pixel array is integrated with a bank of column-parallel first-order incremental oversampling analog-to-digital converters (ADCs). Each ADC performs distributed spatial focal-plane sampling and concurrent weighted average quantization. The architecture is benchmarked in SVM face detection on the MIT CBCL data set. At 90% detection rate, first-level Haar wavelet feature extraction yields a 7.9% reduction in the number of false positives when compared to classification with no feature extraction. The architecture yields 1.4 GMACS simulated computational throughput at SVGA imager resolution at 8-bit output depth.

  6. Evaluation of various feature extraction methods for landmine detection using hidden Markov models

    NASA Astrophysics Data System (ADS)

    Hamdi, Anis; Frigui, Hichem

    2012-06-01

    Hidden Markov Models (HMM) have proved to be eective for detecting buried land mines using data collected by a moving-vehicle-mounted ground penetrating radar (GPR). The general framework for a HMM-based landmine detector consists of building a HMM model for mine signatures and a HMM model for clutter signatures. A test alarm is assigned a condence proportional to the probability of that alarm being generated by the mine model and inversely proportional to its probability in the clutter model. The HMM models are built based on features extracted from GPR training signatures. These features are expected to capture the salient properties of the 3-dimensional alarms in a compact representation. The baseline HMM framework for landmine detection is based on gradient features. It models the time varying behavior of GPR signals, encoded using edge direction information, to compute the likelihood that a sequence of measurements is consistent with a buried landmine. In particular, the HMM mine models learns the hyperbolic shape associated with the signature of a buried mine by three states that correspond to the succession of an increasing edge, a at edge, and a decreasing edge. Recently, for the same application, other features have been used with dierent classiers. In particular, the Edge Histogram Descriptor (EHD) has been used within a K-nearest neighbor classier. Another descriptor is based on Gabor features and has been used within a discrete HMM classier. A third feature, that is closely related to the EHD, is the Bar histogram feature. This feature has been used within a Neural Networks classier for handwritten word recognition. In this paper, we propose an evaluation of the HMM based landmine detection framework with several feature extraction techniques. We adapt and evaluate the EHD, Gabor, Bar, and baseline gradient feature extraction methods. We compare the performance of these features using a large and diverse GPR data collection.

  7. A novel hybrid approach for the extraction of linear/cylindrical features from laser scanning data

    NASA Astrophysics Data System (ADS)

    Lari, Z.; Habib, A.

    2013-10-01

    However, the collected point cloud should undergo manipulation approaches to be utilized for diverse civil, industrial, and military applications. Different processing techniques have consequently been implemented for the extraction of low-level features from this data. Linear/cylindrical features are among the most important primitives that could be extracted from laser scanning data, especially those collected in industrial sites and urban areas. This paper presents a novel approach for the identification, parameterization, and segmentation of these features in a laser point cloud. In the first step of the proposed approach, the points which belong to linear/cylindrical features are detected and their appropriate representation models are chosen based on the principal component analysis of their local neighborhood. The approximate direction and position parameters of the identified linear/cylindrical features are then refined using an iterative line/cylinder fitting procedure. A parameter-domain segmentation method is finally applied to isolate the points which belong to individual linear/cylindrical features in direction and position attribute spaces, respectively. Experimental results from real datasets will demonstrate the feasibility of the proposed approach for the extraction of linear/cylindrical features from laser scanning data.

  8. Hybrid facial image feature extraction and recognition for non-invasive chronic fatigue syndrome diagnosis.

    PubMed

    Chen, Yunhua; Liu, Weijian; Zhang, Ling; Yan, Mingyu; Zeng, Yanjun

    2015-09-01

    Due to an absence of reliable biochemical markers, the diagnosis of chronic fatigue syndrome (CFS) mainly relies on the clinical symptoms, and the experience and skill of the doctors currently. To improve objectivity and reduce work intensity, a hybrid facial feature is proposed. First, several kinds of appearance features are identified in different facial regions according to clinical observations of traditional Chinese medicine experts, including vertical striped wrinkles on the forehead, puffiness of the lower eyelid, the skin colour of the cheeks, nose and lips, and the shape of the mouth corner. Afterwards, such features are extracted and systematically combined to form a hybrid feature. We divide the face into several regions based on twelve active appearance model (AAM) feature points, and ten straight lines across them. Then, Gabor wavelet filtering, CIELab color components, threshold-based segmentation and curve fitting are applied to extract features, and Gabor features are reduced by a manifold preserving projection method. Finally, an AdaBoost based score level fusion of multi-modal features is performed after classification of each feature. Despite that the subjects involved in this trial are exclusively Chinese, the method achieves an average accuracy of 89.04% on the training set and 88.32% on the testing set based on the K-fold cross-validation. In addition, the method also possesses desirable sensitivity and specificity on CFS prediction. PMID:26117650

  9. 'Diamond' in 3-D

    NASA Technical Reports Server (NTRS)

    2004-01-01

    This 3-D, microscopic imager mosaic of a target area on a rock called 'Diamond Jenness' was taken after NASA's Mars Exploration Rover Opportunity ground into the surface with its rock abrasion tool for a second time.

    Opportunity has bored nearly a dozen holes into the inner walls of 'Endurance Crater.' On sols 177 and 178 (July 23 and July 24, 2004), the rover worked double-duty on Diamond Jenness. Surface debris and the bumpy shape of the rock resulted in a shallow and irregular hole, only about 2 millimeters (0.08 inch) deep. The final depth was not enough to remove all the bumps and leave a neat hole with a smooth floor. This extremely shallow depression was then examined by the rover's alpha particle X-ray spectrometer.

    On Sol 178, Opportunity's 'robotic rodent' dined on Diamond Jenness once again, grinding almost an additional 5 millimeters (about 0.2 inch). The rover then applied its Moessbauer spectrometer to the deepened hole. This double dose of Diamond Jenness enabled the science team to examine the rock at varying layers. Results from those grindings are currently being analyzed.

    The image mosaic is about 6 centimeters (2.4 inches) across.

  10. Assessing 3d Photogrammetry Techniques in Craniometrics

    NASA Astrophysics Data System (ADS)

    Moshobane, M. C.; de Bruyn, P. J. N.; Bester, M. N.

    2016-06-01

    Morphometrics (the measurement of morphological features) has been revolutionized by the creation of new techniques to study how organismal shape co-varies with several factors such as ecophenotypy. Ecophenotypy refers to the divergence of phenotypes due to developmental changes induced by local environmental conditions, producing distinct ecophenotypes. None of the techniques hitherto utilized could explicitly address organismal shape in a complete biological form, i.e. three-dimensionally. This study investigates the use of the commercial software, Photomodeler Scanner® (PMSc®) three-dimensional (3D) modelling software to produce accurate and high-resolution 3D models. Henceforth, the modelling of Subantarctic fur seal (Arctocephalus tropicalis) and Antarctic fur seal (Arctocephalus gazella) skulls which could allow for 3D measurements. Using this method, sixteen accurate 3D skull models were produced and five metrics were determined. The 3D linear measurements were compared to measurements taken manually with a digital caliper. In addition, repetitive measurements were recorded by varying researchers to determine repeatability. To allow for comparison straight line measurements were taken with the software, assuming that close accord with all manually measured features would illustrate the model's accurate replication of reality. Measurements were not significantly different demonstrating that realistic 3D skull models can be successfully produced to provide a consistent basis for craniometrics, with the additional benefit of allowing non-linear measurements if required.

  11. 3D steerable wavelets in practice.

    PubMed

    Chenouard, Nicolas; Unser, Michael

    2012-11-01

    We introduce a systematic and practical design for steerable wavelet frames in 3D. Our steerable wavelets are obtained by applying a 3D version of the generalized Riesz transform to a primary isotropic wavelet frame. The novel transform is self-reversible (tight frame) and its elementary constituents (Riesz wavelets) can be efficiently rotated in any 3D direction by forming appropriate linear combinations. Moreover, the basis functions at a given location can be linearly combined to design custom (and adaptive) steerable wavelets. The features of the proposed method are illustrated with the processing and analysis of 3D biomedical data. In particular, we show how those wavelets can be used to characterize directional patterns and to detect edges by means of a 3D monogenic analysis. We also propose a new inverse-problem formalism along with an optimization algorithm for reconstructing 3D images from a sparse set of wavelet-domain edges. The scheme results in high-quality image reconstructions which demonstrate the feature-reduction ability of the steerable wavelets as well as their potential for solving inverse problems. PMID:22752138

  12. miRNAfe: A comprehensive tool for feature extraction in microRNA prediction.

    PubMed

    Yones, Cristian A; Stegmayer, Georgina; Kamenetzky, Laura; Milone, Diego H

    2015-12-01

    miRNAfe is a comprehensive tool to extract features from RNA sequences. It is freely available as a web service, allowing a single access point to almost all state-of-the-art feature extraction methods used today in a variety of works from different authors. It has a very simple user interface, where the user only needs to load a file containing the input sequences and select the features to extract. As a result, the user obtains a text file with the features extracted, which can be used to analyze the sequences or as input to a miRNA prediction software. The tool can calculate up to 80 features where many of them are multidimensional arrays. In order to simplify the web interface, the features have been divided into six pre-defined groups, each one providing information about: primary sequence, secondary structure, thermodynamic stability, statistical stability, conservation between genomes of different species and substrings analysis of the sequences. Additionally, pre-trained classifiers are provided for prediction in different species. All algorithms to extract the features have been validated, comparing the results with the ones obtained from software of the original authors. The source code is freely available for academic use under GPL license at http://sourceforge.net/projects/sourcesinc/files/mirnafe/0.90/. A user-friendly access is provided as web interface at http://fich.unl.edu.ar/sinc/web-demo/mirnafe/. A more configurable web interface can be accessed at http://fich.unl.edu.ar/sinc/web-demo/mirnafe-full/. PMID:26499212

  13. A Transform-Based Feature Extraction Approach for Motor Imagery Tasks Classification

    PubMed Central

    Khorshidtalab, Aida; Mesbah, Mostefa; Salami, Momoh J. E.

    2015-01-01

    In this paper, we present a new motor imagery classification method in the context of electroencephalography (EEG)-based brain–computer interface (BCI). This method uses a signal-dependent orthogonal transform, referred to as linear prediction singular value decomposition (LP-SVD), for feature extraction. The transform defines the mapping as the left singular vectors of the LP coefficient filter impulse response matrix. Using a logistic tree-based model classifier; the extracted features are classified into one of four motor imagery movements. The proposed approach was first benchmarked against two related state-of-the-art feature extraction approaches, namely, discrete cosine transform (DCT) and adaptive autoregressive (AAR)-based methods. By achieving an accuracy of 67.35%, the LP-SVD approach outperformed the other approaches by large margins (25% compared with DCT and 6 % compared with AAR-based methods). To further improve the discriminatory capability of the extracted features and reduce the computational complexity, we enlarged the extracted feature subset by incorporating two extra features, namely, Q- and the Hotelling’s \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$T^{2}$ \\end{document} statistics of the transformed EEG and introduced a new EEG channel selection method. The performance of the EEG classification based on the expanded feature set and channel selection method was compared with that of a number of the state-of-the-art classification methods previously reported with the BCI IIIa competition data set. Our method came second with an average accuracy of 81.38%. PMID:27170898

  14. Combining Feature Extraction Methods to Assist the Diagnosis of Alzheimer's Disease.

    PubMed

    Segovia, F; Górriz, J M; Ramírez, J; Phillips, C; For The Alzheimer's Disease Neuroimaging Initiative

    2016-01-01

    Neuroimaging data as (18)F-FDG PET is widely used to assist the diagnosis of Alzheimer's disease (AD). Looking for regions with hypoperfusion/ hypometabolism, clinicians may predict or corroborate the diagnosis of the patients. Modern computer aided diagnosis (CAD) systems based on the statistical analysis of whole neuroimages are more accurate than classical systems based on quantifying the uptake of some predefined regions of interests (ROIs). In addition, these new systems allow determining new ROIs and take advantage of the huge amount of information comprised in neuroimaging data. A major branch of modern CAD systems for AD is based on multivariate techniques, which analyse a neuroimage as a whole, considering not only the voxel intensities but also the relations among them. In order to deal with the vast dimensionality of the data, a number of feature extraction methods have been successfully applied. In this work, we propose a CAD system based on the combination of several feature extraction techniques. First, some commonly used feature extraction methods based on the analysis of the variance (as principal component analysis), on the factorization of the data (as non-negative matrix factorization) and on classical magnitudes (as Haralick features) were simultaneously applied to the original data. These feature sets were then combined by means of two different combination approaches: i) using a single classifier and a multiple kernel learning approach and ii) using an ensemble of classifier and selecting the final decision by majority voting. The proposed approach was evaluated using a labelled neuroimaging database along with a cross validation scheme. As conclusion, the proposed CAD system performed better than approaches using only one feature extraction technique. We also provide a fair comparison (using the same database) of the selected feature extraction methods. PMID:26567734

  15. Synthetic aperture radar target detection, feature extraction, and image formation techniques

    NASA Technical Reports Server (NTRS)

    Li, Jian

    1994-01-01

    This report presents new algorithms for target detection, feature extraction, and image formation with the synthetic aperture radar (SAR) technology. For target detection, we consider target detection with SAR and coherent subtraction. We also study how the image false alarm rates are related to the target template false alarm rates when target templates are used for target detection. For feature extraction from SAR images, we present a computationally efficient eigenstructure-based 2D-MODE algorithm for two-dimensional frequency estimation. For SAR image formation, we present a robust parametric data model for estimating high resolution range signatures of radar targets and for forming high resolution SAR images.

  16. Extraction, modelling, and use of linear features for restitution of airborne hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Lee, Changno; Bethel, James S.

    This paper presents an approach for the restitution of airborne hyperspectral imagery with linear features. The approach consisted of semi-automatic line extraction and mathematical modelling of the linear features. First, the line was approximately determined manually and refined using dynamic programming. The extracted lines could then be used as control data with the ground information of the lines, or as constraints with simple assumption for the ground information of the line. The experimental results are presented numerically in tables of RMS residuals of check points as well as visually in ortho-rectified images.

  17. Transient signal analysis based on Levenberg-Marquardt method for fault feature extraction of rotating machines

    NASA Astrophysics Data System (ADS)

    Wang, Shibin; Cai, Gaigai; Zhu, Zhongkui; Huang, Weiguo; Zhang, Xingwu

    2015-03-01

    Localized faults in rotating machines tend to result in shocks and thus excite transient components in vibration signals. An iterative extraction method is proposed for transient signal analysis based on transient modeling and parameter identification through Levenberg-Marquardt (LM) method, and eventually for fault feature extraction. For each iteration, a double-side asymmetric transient model is firstly built based on parametric Morlet wavelet, and then the LM method is introduced to identify the parameters of the model. With the implementation of the iterative procedure, transients are extracted from vibration signals one by one, and Wigner-Ville Distribution is applied to obtain time-frequency representation with satisfactory energy concentration but without cross-term. A simulation signal is used to test the performance of the proposed method in transient extraction, and the comparison study shows that the proposed method outperforms ensemble empirical mode decomposition and spectral kurtosis in extracting transient feature. Finally, the effectiveness of the proposed method is verified by the applications in transient analysis for bearing and gear fault feature extraction.

  18. An automated 3D reconstruction method of UAV images

    NASA Astrophysics Data System (ADS)

    Liu, Jun; Wang, He; Liu, Xiaoyang; Li, Feng; Sun, Guangtong; Song, Ping

    2015-10-01

    In this paper a novel fully automated 3D reconstruction approach based on low-altitude unmanned aerial vehicle system (UAVs) images will be presented, which does not require previous camera calibration or any other external prior knowledge. Dense 3D point clouds are generated by integrating orderly feature extraction, image matching, structure from motion (SfM) and multi-view stereo (MVS) algorithms, overcoming many of the cost, time limitations of rigorous photogrammetry techniques. An image topology analysis strategy is introduced to speed up large scene reconstruction by taking advantage of the flight-control data acquired by UAV. Image topology map can significantly reduce the running time of feature matching by limiting the combination of images. A high-resolution digital surface model of the study area is produced base on UAV point clouds by constructing the triangular irregular network. Experimental results show that the proposed approach is robust and feasible for automatic 3D reconstruction of low-altitude UAV images, and has great potential for the acquisition of spatial information at large scales mapping, especially suitable for rapid response and precise modelling in disaster emergency.

  19. Methods of EEG signal features extraction using linear analysis in frequency and time-frequency domains.

    PubMed

    Al-Fahoum, Amjed S; Al-Fraihat, Ausilah A

    2014-01-01

    Technically, a feature represents a distinguishing property, a recognizable measurement, and a functional component obtained from a section of a pattern. Extracted features are meant to minimize the loss of important information embedded in the signal. In addition, they also simplify the amount of resources needed to describe a huge set of data accurately. This is necessary to minimize the complexity of implementation, to reduce the cost of information processing, and to cancel the potential need to compress the information. More recently, a variety of methods have been widely used to extract the features from EEG signals, among these methods are time frequency distributions (TFD), fast fourier transform (FFT), eigenvector methods (EM), wavelet transform (WT), and auto regressive method (ARM), and so on. In general, the analysis of EEG signal has been the subject of several studies, because of its ability to yield an objective mode of recording brain stimulation which is widely used in brain-computer interface researches with application in medical diagnosis and rehabilitation engineering. The purposes of this paper, therefore, shall be discussing some conventional methods of EEG feature extraction methods, comparing their performances for specific task, and finally, recommending the most suitable method for feature extraction based on performance. PMID:24967316

  20. Enhancement of the Feature Extraction Capability in Global Damage Detection Using Wavelet Theory

    NASA Technical Reports Server (NTRS)

    Saleeb, Atef F.; Ponnaluru, Gopi Krishna

    2006-01-01

    The main objective of this study is to assess the specific capabilities of the defect energy parameter technique for global damage detection developed by Saleeb and coworkers. The feature extraction is the most important capability in any damage-detection technique. Features are any parameters extracted from the processed measurement data in order to enhance damage detection. The damage feature extraction capability was studied extensively by analyzing various simulation results. The practical significance in structural health monitoring is that the detection at early stages of small-size defects is always desirable. The amount of changes in the structure's response due to these small defects was determined to show the needed level of accuracy in the experimental methods. The arrangement of fine/extensive sensor network to measure required data for the detection is an "unlimited" ability, but there is a difficulty to place extensive number of sensors on a structure. Therefore, an investigation was conducted using the measurements of coarse sensor network. The white and the pink noises, which cover most of the frequency ranges that are typically encountered in the many measuring devices used (e.g., accelerometers, strain gauges, etc.) are added to the displacements to investigate the effect of noisy measurements in the detection technique. The noisy displacements and the noisy damage parameter values are used to study the signal feature reconstruction using wavelets. The enhancement of the feature extraction capability was successfully achieved by the wavelet theory.

  1. Methods of EEG Signal Features Extraction Using Linear Analysis in Frequency and Time-Frequency Domains

    PubMed Central

    Al-Fahoum, Amjed S.; Al-Fraihat, Ausilah A.

    2014-01-01

    Technically, a feature represents a distinguishing property, a recognizable measurement, and a functional component obtained from a section of a pattern. Extracted features are meant to minimize the loss of important information embedded in the signal. In addition, they also simplify the amount of resources needed to describe a huge set of data accurately. This is necessary to minimize the complexity of implementation, to reduce the cost of information processing, and to cancel the potential need to compress the information. More recently, a variety of methods have been widely used to extract the features from EEG signals, among these methods are time frequency distributions (TFD), fast fourier transform (FFT), eigenvector methods (EM), wavelet transform (WT), and auto regressive method (ARM), and so on. In general, the analysis of EEG signal has been the subject of several studies, because of its ability to yield an objective mode of recording brain stimulation which is widely used in brain-computer interface researches with application in medical diagnosis and rehabilitation engineering. The purposes of this paper, therefore, shall be discussing some conventional methods of EEG feature extraction methods, comparing their performances for specific task, and finally, recommending the most suitable method for feature extraction based on performance. PMID:24967316

  2. Application of multi-scale feature extraction to surface defect classification of hot-rolled steels

    NASA Astrophysics Data System (ADS)

    Xu, Ke; Ai, Yong-hao; Wu, Xiu-yong

    2013-01-01

    Feature extraction is essential to the classification of surface defect images. The defects of hot-rolled steels distribute in different directions. Therefore, the methods of multi-scale geometric analysis (MGA) were employed to decompose the image into several directional subbands at several scales. Then, the statistical features of each subband were calculated to produce a high-dimensional feature vector, which was reduced to a lower-dimensional vector by graph embedding algorithms. Finally, support vector machine (SVM) was used for defect classification. The multi-scale feature extraction method was implemented via curvelet transform and kernel locality preserving projections (KLPP). Experiment results show that the proposed method is effective for classifying the surface defects of hot-rolled steels and the total classification rate is up to 97.33%.

  3. 3D camera tracking from disparity images

    NASA Astrophysics Data System (ADS)

    Kim, Kiyoung; Woo, Woontack

    2005-07-01

    In this paper, we propose a robust camera tracking method that uses disparity images computed from known parameters of 3D camera and multiple epipolar constraints. We assume that baselines between lenses in 3D camera and intrinsic parameters are known. The proposed method reduces camera motion uncertainty encountered during camera tracking. Specifically, we first obtain corresponding feature points between initial lenses using normalized correlation method. In conjunction with matching features, we get disparity images. When the camera moves, the corresponding feature points, obtained from each lens of 3D camera, are robustly tracked via Kanade-Lukas-Tomasi (KLT) tracking algorithm. Secondly, relative pose parameters of each lens are calculated via Essential matrices. Essential matrices are computed from Fundamental matrix calculated using normalized 8-point algorithm with RANSAC scheme. Then, we determine scale factor of translation matrix by d-motion. This is required because the camera motion obtained from Essential matrix is up to scale. Finally, we optimize camera motion using multiple epipolar constraints between lenses and d-motion constraints computed from disparity images. The proposed method can be widely adopted in Augmented Reality (AR) applications, 3D reconstruction using 3D camera, and fine surveillance systems which not only need depth information, but also camera motion parameters in real-time.

  4. Feature extraction with deep neural networks by a generalized discriminant analysis.

    PubMed

    Stuhlsatz, André; Lippel, Jens; Zielke, Thomas

    2012-04-01

    We present an approach to feature extraction that is a generalization of the classical linear discriminant analysis (LDA) on the basis of deep neural networks (DNNs). As for LDA, discriminative features generated from independent Gaussian class conditionals are assumed. This modeling has the advantages that the intrinsic dimensionality of the feature space is bounded by the number of classes and that the optimal discriminant function is linear. Unfortunately, linear transformations are insufficient to extract optimal discriminative features from arbitrarily distributed raw measurements. The generalized discriminant analysis (GerDA) proposed in this paper uses nonlinear transformations that are learnt by DNNs in a semisupervised fashion. We show that the feature extraction based on our approach displays excellent performance on real-world recognition and detection tasks, such as handwritten digit recognition and face detection. In a series of experiments, we evaluate GerDA features with respect to dimensionality reduction, visualization, classification, and detection. Moreover, we show that GerDA DNNs can preprocess truly high-dimensional input data to low-dimensional representations that facilitate accurate predictions even if simple linear predictors or measures of similarity are used. PMID:24805043

  5. 3D fast wavelet network model-assisted 3D face recognition

    NASA Astrophysics Data System (ADS)

    Said, Salwa; Jemai, Olfa; Zaied, Mourad; Ben Amar, Chokri

    2015-12-01

    In last years, the emergence of 3D shape in face recognition is due to its robustness to pose and illumination changes. These attractive benefits are not all the challenges to achieve satisfactory recognition rate. Other challenges such as facial expressions and computing time of matching algorithms remain to be explored. In this context, we propose our 3D face recognition approach using 3D wavelet networks. Our approach contains two stages: learning stage and recognition stage. For the training we propose a novel algorithm based on 3D fast wavelet transform. From 3D coordinates of the face (x,y,z), we proceed to voxelization to get a 3D volume which will be decomposed by 3D fast wavelet transform and modeled after that with a wavelet network, then their associated weights are considered as vector features to represent each training face . For the recognition stage, an unknown identity face is projected on all the training WN to obtain a new vector features after every projection. A similarity score is computed between the old and the obtained vector features. To show the efficiency of our approach, experimental results were performed on all the FRGC v.2 benchmark.

  6. Linearly Supporting Feature Extraction for Automated Estimation of Stellar Atmospheric Parameters

    NASA Astrophysics Data System (ADS)

    Li, Xiangru; Lu, Yu; Comte, Georges; Luo, Ali; Zhao, Yongheng; Wang, Yongjun

    2015-05-01

    We describe a scheme to extract linearly supporting (LSU) features from stellar spectra to automatically estimate the atmospheric parameters {{T}{\\tt{eff} }}, log g, and [Fe/H]. “Linearly supporting” means that the atmospheric parameters can be accurately estimated from the extracted features through a linear model. The successive steps of the process are as follow: first, decompose the spectrum using a wavelet packet (WP) and represent it by the derived decomposition coefficients; second, detect representative spectral features from the decomposition coefficients using the proposed method Least Absolute Shrinkage and Selection Operator (LARS)bs; third, estimate the atmospheric parameters {{T}{\\tt{eff} }}, log g, and [Fe/H] from the detected features using a linear regression method. One prominent characteristic of this scheme is its ability to evaluate quantitatively the contribution of each detected feature to the atmospheric parameter estimate and also to trace back the physical significance of that feature. This work also shows that the usefulness of a component depends on both the wavelength and frequency. The proposed scheme has been evaluated on both real spectra from the Sloan Digital Sky Survey (SDSS)/SEGUE and synthetic spectra calculated from Kurucz's NEWODF models. On real spectra, we extracted 23 features to estimate {{T}{\\tt{eff} }}, 62 features for log g, and 68 features for [Fe/H]. Test consistencies between our estimates and those provided by the Spectroscopic Parameter Pipeline of SDSS show that the mean absolute errors (MAEs) are 0.0062 dex for log {{T}{\\tt{eff} }} (83 K for {{T}{\\tt{eff} }}), 0.2345 dex for log g, and 0.1564 dex for [Fe/H]. For the synthetic spectra, the MAE test accuracies are 0.0022 dex for log {{T}{\\tt{eff} }} (32 K for {{T}{\\tt{eff} }}), 0.0337 dex for log g, and 0.0268 dex for [Fe/H].

  7. Multi-view indoor human behavior recognition based on 3D skeleton

    NASA Astrophysics Data System (ADS)

    Peng, Ling; Lu, Tongwei; Min, Feng

    2015-12-01

    For the problems caused by viewpoint changes in activity recognition, a multi-view interior human behavior recognition method based on 3D framework is presented. First, Microsoft's Kinect device is used to obtain body motion video in the positive perspective, the oblique angle and the side perspective. Second, it extracts bone joints and get global human features and the local features of arms and legs at the same time to form 3D skeletal features set. Third, online dictionary learning on feature set is used to reduce the dimension of feature. Finally, linear support vector machine (LSVM) is used to obtain the results of behavior recognition. The experimental results show that this method has better recognition rate.

  8. 3D face analysis for demographic biometrics

    SciTech Connect

    Tokola, Ryan A; Mikkilineni, Aravind K; Boehnen, Chris Bensing

    2015-01-01

    Despite being increasingly easy to acquire, 3D data is rarely used for face-based biometrics applications beyond identification. Recent work in image-based demographic biometrics has enjoyed much success, but these approaches suffer from the well-known limitations of 2D representations, particularly variations in illumination, texture, and pose, as well as a fundamental inability to describe 3D shape. This paper shows that simple 3D shape features in a face-based coordinate system are capable of representing many biometric attributes without problem-specific models or specialized domain knowledge. The same feature vector achieves impressive results for problems as diverse as age estimation, gender classification, and race classification.

  9. 3-D Finite Element Heat Transfer

    1992-02-01

    TOPAZ3D is a three-dimensional implicit finite element computer code for heat transfer analysis. TOPAZ3D can be used to solve for the steady-state or transient temperature field on three-dimensional geometries. Material properties may be temperature-dependent and either isotropic or orthotropic. A variety of time-dependent and temperature-dependent boundary conditions can be specified including temperature, flux, convection, and radiation. By implementing the user subroutine feature, users can model chemical reaction kinetics and allow for any type of functionalmore » representation of boundary conditions and internal heat generation. TOPAZ3D can solve problems of diffuse and specular band radiation in an enclosure coupled with conduction in the material surrounding the enclosure. Additional features include thermal contact resistance across an interface, bulk fluids, phase change, and energy balances.« less

  10. Real-time implementation of optimized maximum noise fraction transform for feature extraction of hyperspectral images

    NASA Astrophysics Data System (ADS)

    Wu, Yuanfeng; Gao, Lianru; Zhang, Bing; Zhao, Haina; Li, Jun

    2014-01-01

    We present a parallel implementation of the optimized maximum noise fraction (G-OMNF) transform algorithm for feature extraction of hyperspectral images on commodity graphics processing units (GPUs). The proposed approach explored the algorithm data-level concurrency and optimized the computing flow. We first defined a three-dimensional grid, in which each thread calculates a sub-block data to easily facilitate the spatial and spectral neighborhood data searches in noise estimation, which is one of the most important steps involved in OMNF. Then, we optimized the processing flow and computed the noise covariance matrix before computing the image covariance matrix to reduce the original hyperspectral image data transmission. These optimization strategies can greatly improve the computing efficiency and can be applied to other feature extraction algorithms. The proposed parallel feature extraction algorithm was implemented on an Nvidia Tesla GPU using the compute unified device architecture and basic linear algebra subroutines library. Through the experiments on several real hyperspectral images, our GPU parallel implementation provides a significant speedup of the algorithm compared with the CPU implementation, especially for highly data parallelizable and arithmetically intensive algorithm parts, such as noise estimation. In order to further evaluate the effectiveness of G-OMNF, we used two different applications: spectral unmixing and classification for evaluation. Considering the sensor scanning rate and the data acquisition time, the proposed parallel implementation met the on-board real-time feature extraction.

  11. Automatic geomorphic feature extraction from lidar in flat and engineered landscapes

    NASA Astrophysics Data System (ADS)

    Passalacqua, P.; Belmont, P.; Foufoula, E.

    2011-12-01

    High resolution topography derived from light detection and ranging (lidar) technology enables detailed geomorphic observations to be made on spatially extensive landforms in a way that was previously not possible. This provides new opportunities to study the spatial organization of landscapes and channel network features, increase the accuracy of environmental transport models and inform decisions for targeting conservation practices. However, with the opportunity of increased resolution topography data over large areas come formidable challenges in terms of automatic geomorphic feature extraction, analysis, and interpretation. This is particularly true in low relief landscapes since the topographic gradients are low and both the landscape and the channel network are often heavily modified by humans. Recently, a comprehensive framework was developed for the automatic extraction of geomorphic features (channel network, channel heads and channel morphology) from high resolution topographic data by combining nonlinear diffusion and geodesic minimization principles. The feature extraction method was packaged in a software called GeoNet (which is publicly available). In this talk, we focus on the application of GeoNet to a variety of landscapes, and, in particular, to flat and engineered landscapes where the method has been recently extended to perform automated channel morphometric analysis (including extraction of cross-sections, detection of bank locations, and identificati