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Sample records for automatic local gabor

  1. Automatic localization of the nipple in mammograms using Gabor filters and the Radon transform

    NASA Astrophysics Data System (ADS)

    Chakraborty, Jayasree; Mukhopadhyay, Sudipta; Rangayyan, Rangaraj M.; Sadhu, Anup; Azevedo-Marques, P. M.

    2013-02-01

    The nipple is an important landmark in mammograms. Detection of the nipple is useful for alignment and registration of mammograms in computer-aided diagnosis of breast cancer. In this paper, a novel approach is proposed for automatic detection of the nipple based on the oriented patterns of the breast tissues present in mammograms. The Radon transform is applied to the oriented patterns obtained by a bank of Gabor filters to detect the linear structures related to the tissue patterns. The detected linear structures are then used to locate the nipple position using the characteristics of convergence of the tissue patterns towards the nipple. The performance of the method was evaluated with 200 scanned-film images from the mini-MIAS database and 150 digital radiography (DR) images from a local database. Average errors of 5:84 mm and 6:36 mm were obtained with respect to the reference nipple location marked by a radiologist for the mini-MIAS and the DR images, respectively.

  2. Detection of local defects in textile webs using Gabor filters

    NASA Astrophysics Data System (ADS)

    Escofet, Jaume; Navarro, Rafael B.; Millan, Maria S.; Pladellorens, Josep M.

    1998-08-01

    A method of image analysis is proposed for detection of local defects in materials with periodic regular texture. A general improvement and enlargement of vision system capabilities for versatility, full automatism, computational efficiency, and robustness in their application to the industrial inspection of periodic textured-materials is pursued. In the proposed method, a multiscale and multiorientation Gabor filter scheme that imitates the early human vision process is applied to the sample under inspection. The designed algorithm automatically segments defects from the regular texture. A variety of examples of fabric inspection are presented. In all of them defects are successfully segmented from the texture background.

  3. Face Recognition Using Local Quantized Patterns and Gabor Filters

    NASA Astrophysics Data System (ADS)

    Khryashchev, V.; Priorov, A.; Stepanova, O.; Nikitin, A.

    2015-05-01

    The problem of face recognition in a natural or artificial environment has received a great deal of researchers' attention over the last few years. A lot of methods for accurate face recognition have been proposed. Nevertheless, these methods often fail to accurately recognize the person in difficult scenarios, e.g. low resolution, low contrast, pose variations, etc. We therefore propose an approach for accurate and robust face recognition by using local quantized patterns and Gabor filters. The estimation of the eye centers is used as a preprocessing stage. The evaluation of our algorithm on different samples from a standardized FERET database shows that our method is invariant to the general variations of lighting, expression, occlusion and aging. The proposed approach allows about 20% correct recognition accuracy increase compared with the known face recognition algorithms from the OpenCV library. The additional use of Gabor filters can significantly improve the robustness to changes in lighting conditions.

  4. Local fingerprint image reconstruction based on gabor filtering

    NASA Astrophysics Data System (ADS)

    Bakhtiari, Somayeh; Agaian, Sos S.; Jamshidi, Mo

    2012-06-01

    In this paper, we propose two solutions for fingerprint local image reconstruction based on Gabor filtering. Gabor filtering is a popular method for fingerprint image enhancement. However, the reliability of the information in the output image suffers, when the input image has a poor quality. This is the result of the spurious estimates of frequency and orientation by classical approaches, particularly in the scratch regions. In both techniques of this paper, the scratch marks are recognized initially using reliability image which is calculated using the gradient images. The first algorithm is based on an inpainting technique and the second method employs two different kernels for the scratch and the non-scratch parts of the image to calculate the gradient images. The simulation results show that both approaches allow the actual information of the image to be preserved while connecting discontinuities correctly by approximating the orientation matrix more genuinely.

  5. Automatic detection of echolocation clicks based on a Gabor model of their waveform.

    PubMed

    Madhusudhana, Shyam; Gavrilov, Alexander; Erbe, Christine

    2015-06-01

    Prior research has shown that echolocation clicks of several species of terrestrial and marine fauna can be modelled as Gabor-like functions. Here, a system is proposed for the automatic detection of a variety of such signals. By means of mathematical formulation, it is shown that the output of the Teager-Kaiser Energy Operator (TKEO) applied to Gabor-like signals can be approximated by a Gaussian function. Based on the inferences, a detection algorithm involving the post-processing of the TKEO outputs is presented. The ratio of the outputs of two moving-average filters, a Gaussian and a rectangular filter, is shown to be an effective detection parameter. Detector performance is assessed using synthetic and real (taken from MobySound database) recordings. The detection method is shown to work readily with a variety of echolocation clicks and in various recording scenarios. The system exhibits low computational complexity and operates several times faster than real-time. Performance comparisons are made to other publicly available detectors including pamguard. PMID:26093399

  6. An Automatic 3D Facial Landmarking Algorithm Using 2D Gabor Wavelets.

    PubMed

    de Jong, Markus A; Wollstein, Andreas; Ruff, Clifford; Dunaway, David; Hysi, Pirro; Spector, Tim; Fan Liu; Niessen, Wiro; Koudstaal, Maarten J; Kayser, Manfred; Wolvius, Eppo B; Bohringer, Stefan

    2016-02-01

    In this paper, we present a novel approach to automatic 3D facial landmarking using 2D Gabor wavelets. Our algorithm considers the face to be a surface and uses map projections to derive 2D features from raw data. Extracted features include texture, relief map, and transformations thereof. We extend an established 2D landmarking method for simultaneous evaluation of these data. The method is validated by performing landmarking experiments on two data sets using 21 landmarks and compared with an active shape model implementation. On average, landmarking error for our method was 1.9 mm, whereas the active shape model resulted in an average landmarking error of 2.3 mm. A second study investigating facial shape heritability in related individuals concludes that automatic landmarking is on par with manual landmarking for some landmarks. Our algorithm can be trained in 30 min to automatically landmark 3D facial data sets of any size, and allows for fast and robust landmarking of 3D faces. PMID:26540684

  7. Multiple local feature representations and their fusion based on an SVR model for iris recognition using optimized Gabor filters

    NASA Astrophysics Data System (ADS)

    He, Fei; Liu, Yuanning; Zhu, Xiaodong; Huang, Chun; Han, Ye; Dong, Hongxing

    2014-12-01

    Gabor descriptors have been widely used in iris texture representations. However, fixed basic Gabor functions cannot match the changing nature of diverse iris datasets. Furthermore, a single form of iris feature cannot overcome difficulties in iris recognition, such as illumination variations, environmental conditions, and device variations. This paper provides multiple local feature representations and their fusion scheme based on a support vector regression (SVR) model for iris recognition using optimized Gabor filters. In our iris system, a particle swarm optimization (PSO)- and a Boolean particle swarm optimization (BPSO)-based algorithm is proposed to provide suitable Gabor filters for each involved test dataset without predefinition or manual modulation. Several comparative experiments on JLUBR-IRIS, CASIA-I, and CASIA-V4-Interval iris datasets are conducted, and the results show that our work can generate improved local Gabor features by using optimized Gabor filters for each dataset. In addition, our SVR fusion strategy may make full use of their discriminative ability to improve accuracy and reliability. Other comparative experiments show that our approach may outperform other popular iris systems.

  8. Score level fusion scheme based on adaptive local Gabor features for face-iris-fingerprint multimodal biometric

    NASA Astrophysics Data System (ADS)

    He, Fei; Liu, Yuanning; Zhu, Xiaodong; Huang, Chun; Han, Ye; Chen, Ying

    2014-05-01

    A multimodal biometric system has been considered a promising technique to overcome the defects of unimodal biometric systems. We have introduced a fusion scheme to gain a better understanding and fusion method for a face-iris-fingerprint multimodal biometric system. In our case, we use particle swarm optimization to train a set of adaptive Gabor filters in order to achieve the proper Gabor basic functions for each modality. For a closer analysis of texture information, two different local Gabor features for each modality are produced by the corresponding Gabor coefficients. Next, all matching scores of the two Gabor features for each modality are projected to a single-scalar score via a trained, supported, vector regression model for a final decision. A large-scale dataset is formed to validate the proposed scheme using the Facial Recognition Technology database-fafb and CASIA-V3-Interval together with FVC2004-DB2a datasets. The experimental results demonstrate that as well as achieving further powerful local Gabor features of multimodalities and obtaining better recognition performance by their fusion strategy, our architecture also outperforms some state-of-the-art individual methods and other fusion approaches for face-iris-fingerprint multimodal biometric systems.

  9. Automatic target classification of man-made objects in synthetic aperture radar images using Gabor wavelet and neural network

    NASA Astrophysics Data System (ADS)

    Vasuki, Perumal; Roomi, S. Mohamed Mansoor

    2013-01-01

    Processing of synthetic aperture radar (SAR) images has led to the development of automatic target classification approaches. These approaches help to classify individual and mass military ground vehicles. This work aims to develop an automatic target classification technique to classify military targets like truck/tank/armored car/cannon/bulldozer. The proposed method consists of three stages via preprocessing, feature extraction, and neural network (NN). The first stage removes speckle noise in a SAR image by the identified frost filter and enhances the image by histogram equalization. The second stage uses a Gabor wavelet to extract the image features. The third stage classifies the target by an NN classifier using image features. The proposed work performs better than its counterparts, like K-nearest neighbor (KNN). The proposed work performs better on databases like moving and stationary target acquisition and recognition against the earlier methods by KNN.

  10. Study on local Gabor binary patterns for face representation and recognition

    NASA Astrophysics Data System (ADS)

    Ge, Wei; Han, Chunling; Quan, Wei

    2015-12-01

    More recently, Local Binary Patterns(LBP) has received much attention in face representation and recognition. The original LBP operator could describe the spatial structure information, which are the variety edge or variety angle features of local facial images essentially, they are important factors of classify different faces. But the scale and orientation of the edge features include more detail information which could be used to classify different persons efficiently, while original LBP operator could not to extract the information. In this paper, based on the introduction of original LBP-based facial representation and recognition, the histogram sequences of local Gabor binary patterns are used to representation facial image. Principal Component Analysis (PCA) method is used to classification the histogram sequences, which have been converted to vectors. Recognition experimental results show that the method we used in this paper increases nearly 6% than the classification performance of original LBP operator.

  11. Automatic adaptive parameterization in local phase feature-based bone segmentation in ultrasound.

    PubMed

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

    2011-10-01

    Intensity-invariant local phase features based on Log-Gabor filters have been recently shown to produce highly accurate localizations of bone surfaces from three-dimensional (3-D) ultrasound. A key challenge, however, remains in the proper selection of filter parameters, whose values have so far been chosen empirically and kept fixed for a given image. Since Log-Gabor filter responses widely change when varying the filter parameters, actual parameter selection can significantly affect the quality of extracted features. This article presents a novel method for contextual parameter selection that autonomously adapts to image content. Our technique automatically selects the scale, bandwidth and orientation parameters of Log-Gabor filters for optimizing local phase symmetry. The proposed approach incorporates principle curvature computed from the Hessian matrix and directional filter banks in a phase scale-space framework. Evaluations performed on carefully designed in vitro experiments demonstrate 35% improvement in accuracy of bone surface localization compared with empirically-set parameterization results. Results from a pilot in vivo study on human subjects, scanned in the operating room, show similar improvements. PMID:21821346

  12. Local gradient Gabor pattern (LGGP) with applications in face recognition, cross-spectral matching, and soft biometrics

    NASA Astrophysics Data System (ADS)

    Chen, Cunjian; Ross, Arun

    2013-05-01

    Researchers in face recognition have been using Gabor filters for image representation due to their robustness to complex variations in expression and illumination. Numerous methods have been proposed to model the output of filter responses by employing either local or global descriptors. In this work, we propose a novel but simple approach for encoding Gradient information on Gabor-transformed images to represent the face, which can be used for identity, gender and ethnicity assessment. Extensive experiments on the standard face benchmark FERET (Visible versus Visible), as well as the heterogeneous face dataset HFB (Near-infrared versus Visible), suggest that the matching performance due to the proposed descriptor is comparable against state-of-the-art descriptor-based approaches in face recognition applications. Furthermore, the same feature set is used in the framework of a Collaborative Representation Classification (CRC) scheme for deducing soft biometric traits such as gender and ethnicity from face images in the AR, Morph and CAS-PEAL databases.

  13. Locally connected adaptive Gabor filter for real-time motion compensation

    NASA Astrophysics Data System (ADS)

    Li, Hau

    1994-07-01

    Software has been developed to implement the Gabor motion detection algorithm. This software consists of utility functions, algorithm modules, and test pattern generators for the experiments and verification of the spatial and temporal selectivity. Based on the theoretical analysis, the optical flow was computed for several artificially generated test patterns. These test patterns are designed to test the concept of spatial and orientation selectivity. The patterns were generated by using virtual reality technique based on three-dimensional computer graphics. In addition to the algorithm development and verification, we have also started work on the design and verification of the electronics basic building blocks for the VLSI implementation. This early start of the hardware design concurrent with the algorithm analysis and verification will further ensure the quality of the work in both hardware and software. In order to benchmark the VLSI chips, a hardware prototype board is under design and construction. This board will be used to compare the performance of digital approach vs. analog approach, analog approach based on the standard off-the-shelf components vs. analog customer-design VLSI approach.

  14. Gabor filter based fingerprint image enhancement

    NASA Astrophysics Data System (ADS)

    Wang, Jin-Xiang

    2013-03-01

    Fingerprint recognition technology has become the most reliable biometric technology due to its uniqueness and invariance, which has been most convenient and most reliable technique for personal authentication. The development of Automated Fingerprint Identification System is an urgent need for modern information security. Meanwhile, fingerprint preprocessing algorithm of fingerprint recognition technology has played an important part in Automatic Fingerprint Identification System. This article introduces the general steps in the fingerprint recognition technology, namely the image input, preprocessing, feature recognition, and fingerprint image enhancement. As the key to fingerprint identification technology, fingerprint image enhancement affects the accuracy of the system. It focuses on the characteristics of the fingerprint image, Gabor filters algorithm for fingerprint image enhancement, the theoretical basis of Gabor filters, and demonstration of the filter. The enhancement algorithm for fingerprint image is in the windows XP platform with matlab.65 as a development tool for the demonstration. The result shows that the Gabor filter is effective in fingerprint image enhancement technology.

  15. Theory, implementation and applications of nonstationary Gabor frames

    PubMed Central

    Balazs, P.; Dörfler, M.; Jaillet, F.; Holighaus, N.; Velasco, G.

    2011-01-01

    Signal analysis with classical Gabor frames leads to a fixed time–frequency resolution over the whole time–frequency plane. To overcome the limitations imposed by this rigidity, we propose an extension of Gabor theory that leads to the construction of frames with time–frequency resolution changing over time or frequency. We describe the construction of the resulting nonstationary Gabor frames and give the explicit formula for the canonical dual frame for a particular case, the painless case. We show that wavelet transforms, constant-Q transforms and more general filter banks may be modeled in the framework of nonstationary Gabor frames. Further, we present the results in the finite-dimensional case, which provides a method for implementing the above-mentioned transforms with perfect reconstruction. Finally, we elaborate on two applications of nonstationary Gabor frames in audio signal processing, namely a method for automatic adaptation to transients and an algorithm for an invertible constant-Q transform. PMID:22267893

  16. Gabor wavelets for texture edge extraction

    NASA Astrophysics Data System (ADS)

    Shao, Juliang; Foerstner, Wolfgang

    1994-08-01

    Textures in images have a natural order, both in orientation and multiple narrow-band frequency, which requires the user to employ multichannel local spatial/frequency filtering and orientation selectivity, and to have a multiscale characteristic. Each channel covers one part of a whole frequency domain, which indicates different information for the different texton. Gabor filter, as a near orthogonal wavelet used in this paper, has orientation selectivity, multiscale property, linear phase, and good localization both in spatial and frequency domains, which are suitable for texture analysis. Gabor filters are employed for clustering the similarity of the same type of textons. Gaussian filters are also used for detection of normal image edges. Then hybrid texture and nontexture gradient measurement is based on fusion of the difference of amplitude of the filter responses between Gabor and Gaussian filters at neighboring pixels by mainly using average squared gradient. Normalization, based on the noise response and based on maximum response, is computed.

  17. Gabor representation with oversampling

    NASA Astrophysics Data System (ADS)

    Zibulski, Meir; Zeevi, Yehoshua Y.

    1992-11-01

    An approach for characterizing the properties of the basis functions of the Gabor representation in the context of oversampling is presented. The approach is based on the concept of frames and utilizes the Piecewise Zak Transform (PZT). The frame operator associated with the Gabor-type frame, the so-called Weyl-Heisenberg frame, is examined for a rational oversampling rate by representing the frame operator as a matrix-valued function in the PZT domain. Completeness and frame properties of the Gabor representation functions are examined in relation to the properties of the matrix-valued function. The frame bounds are calculated by means of the eigenvalues of the matrix-valued function, and the dual-frame, which is used in calculation of the expansion coefficients, is expressed by means of the inverse matrix.

  18. Dennis Gabor: inventor of...

    NASA Astrophysics Data System (ADS)

    Greguss, Pal

    2000-10-01

    The scope of this presentation is to give a brief survey on the more than 60 patents Dennis Gabor has obtained over a period of six decades. This means inventions related to light sources, cathode ray tubes, material sciences as well as the creation of thermionic electric generators, emphasizing, however, those that are strongly related to optics, holography and telecommunication. It is interesting to follow, how the idea of holography emerged in Gabor's endeavor to improve electron microscopy, and how these endeavors created side effects, such as the idea of flat display tubes or his invention to the production and projection of photographic pictures with stereoscopic effects. Derived as early as 1940. This idea culminated then in his patent entitled three dimensional picture projection in 1966, which already exploited the possibilities inherent in holography.

  19. Pseudo-Gabor wavelet for face recognition

    NASA Astrophysics Data System (ADS)

    Xie, Xudong; Liu, Wentao; Lam, Kin-Man

    2013-04-01

    An efficient face-recognition algorithm is proposed, which not only possesses the advantages of linear subspace analysis approaches-such as low computational complexity-but also has the advantage of a high recognition performance with the wavelet-based algorithms. Based on the linearity of Gabor-wavelet transformation and some basic assumptions on face images, we can extract pseudo-Gabor features from the face images without performing any complex Gabor-wavelet transformations. The computational complexity can therefore be reduced while a high recognition performance is still maintained by using the principal component analysis (PCA) method. The proposed algorithm is evaluated based on the Yale database, the Caltech database, the ORL database, the AR database, and the Facial Recognition Technology database, and is compared with several different face recognition methods such as PCA, Gabor wavelets plus PCA, kernel PCA, locality preserving projection, and dual-tree complex wavelet transformation plus PCA. Experiments show that consistent and promising results are obtained.

  20. Superfast computations of dual and tight Gabor atoms

    NASA Astrophysics Data System (ADS)

    Qiu, Sigang

    1995-09-01

    We consider a class of Gabor-type matrices and develop simplified Gabor-type matrix operations. As applications to discrete Gabor transforms, we propose `superfast' algorithms for determining the inverse of Gabor frame operators and the square roots of the Gabor frame operators as well as the dual Gabor and tight Gabor atoms. Besides, we summarize briefly some additional results.

  1. Gabor: frequency, time, and memory.

    PubMed

    Korpel, A

    1982-10-15

    Dennis Gabor is well-known as the inventor of holography. Less well-known, perhaps, are his contributions to other areas. Yet they are important and, like holography, characteristic of his foresight. In the field of communications, Gabor investigated the classic dichotomy of time and frequency. Guided by analogies to quantum mechanics, he postulated a set of elementary signals and made brilliant use of time-frequency diagrams to analyze communication systems. Applying his theories to acoustics, he researched the mechanism of hearing, defining acoustical quanta in the process and inventing early prototype frequency compressors and expanders. In a completely different field, Gabor, inspired by some early work of Longuet-Higgins on models for holographic temporal recall in the brain, suggested novel approaches which contributed significantly to the understanding of associative memories. In this paper we describe Gabor's pioneering work in these areas and trace the subsequent development by himself and others. PMID:20396288

  2. Log-Gabor Weber descriptor for face recognition

    NASA Astrophysics Data System (ADS)

    Li, Jing; Sang, Nong; Gao, Changxin

    2015-09-01

    The Log-Gabor transform, which is suitable for analyzing gradually changing data such as in iris and face images, has been widely used in image processing, pattern recognition, and computer vision. In most cases, only the magnitude or phase information of the Log-Gabor transform is considered. However, the complementary effect taken by combining magnitude and phase information simultaneously for an image-feature extraction problem has not been systematically explored in the existing works. We propose a local image descriptor for face recognition, called Log-Gabor Weber descriptor (LGWD). The novelty of our LGWD is twofold: (1) to fully utilize the information from the magnitude or phase feature of multiscale and orientation Log-Gabor transform, we apply the Weber local binary pattern operator to each transform response. (2) The encoded Log-Gabor magnitude and phase information are fused at the feature level by utilizing kernel canonical correlation analysis strategy, considering that feature level information fusion is effective when the modalities are correlated. Experimental results on the AR, Extended Yale B, and UMIST face databases, compared with those available from recent experiments reported in the literature, show that our descriptor yields a better performance than state-of-the art methods.

  3. Systolic array architecture for real-time Gabor decomposition

    NASA Astrophysics Data System (ADS)

    Iyengar, Giridharan; Panchanathan, Sethuraman

    1992-11-01

    In this paper, we propose a combined systolic array--content addressable memory architecture for image compression using Gabor decomposition. Gabor decomposition is attractive for image compression since the basis functions match the human visual profiles. Gabor functions also achieve the lowest bound on the joint entropy of data. However these functions are not orthogonal and hence an analytic solution for the decomposition does not exist. Recently it has been shown that Gabor decomposition can be computed as a multiplication between a transform matrix and a vector of image data. Systolic arrays are attractive for matrix multiplication problems and content addressable memories (CAM) offer fast means of data access. For an n X n image, the proposed architecture for Gabor decomposition consists of a linear systolic array of n processing elements each with a local CAM. Simulations and complexity studies show that this architecture can achieve real-time performance with current technology. This architecture is modular and regular and hence it can be implemented in VLSI as a codec.

  4. Block-circulant Gabor-matrix structure and discrete Gabor transforms

    NASA Astrophysics Data System (ADS)

    Qiu, Sigang

    1995-10-01

    We develop the block-circulant structure of Gabor matrices, and establish that Gabor matrices are unitarily block-diagonalizable simultaneously. It opens a new way of implementing the discrete Gabor transforms. For the most interesting cases, if the product ab of the lattice constants divides the signal length N (in particlary, in the critical-sampling cases), we prove that the Gabor operators are simultaneously unitarily equivalent to non-negative pointwise multiplication operators. This leads to fast computations of the inverse of the Gabor operator and the square root of the inverse of the Gabor operator, as well as the dual Gabor wavelet and the tight Gabor wavelet. Gabor syntheses turn out to be simple, and we can also easily predetermine the stability of Gabor reconstructions.

  5. Class of discrete Gabor expansion

    NASA Astrophysics Data System (ADS)

    Li, Shidong; Healy, Dennis M., Jr.

    1994-03-01

    We present a new approach to studying a discrete Gabor expansion (DGE). We show that, in general, DGE is not the usual biorthogonal decomposition, but belongs to a larger and looser decomposition scheme which we call pseudo frame decomposition. It includes the DGE scheme proposed as a special case. The standard dual frame decomposition is also a special case. We derive algorithms using techniques for Gabor sequences to compute 'biorthogonal' sequences through proper matrix representation. Our algorithms involve solutions to a linear system to obtain the 'biorthogonal' windows. This approach provides a much broader mathematical view of the DGE, and therefore, establishes a wider mathematical foundation towards the theory of DGE. The general algorithm derived also provides a whole class of discrete Gabor expansions, among which 'good' ones can be generated. Simulation results are also provided.

  6. Automatic segmentation of abdominal vessels for improved pancreas localization

    NASA Astrophysics Data System (ADS)

    Farag, Amal; Liu, Jiamin; Summers, Ronald M.

    2014-03-01

    Accurate automatic detection and segmentation of abdominal organs from CT images is important for quantitative and qualitative organ tissue analysis as well as computer-aided diagnosis. The large variability of organ locations, the spatial interaction between organs that appear similar in medical scans and orientation and size variations are among the major challenges making the task very difficult. The pancreas poses these challenges in addition to its flexibility which allows for the shape of the tissue to vastly change. Due to the close proximity of the pancreas to numerous surrounding organs within the abdominal cavity the organ shifts according to the conditions of the organs within the abdomen, as such the pancreas is constantly changing. Combining these challenges with typically found patient-to-patient variations and scanning conditions the pancreas becomes harder to localize. In this paper we focus on three abdominal vessels that almost always abut the pancreas tissue and as such useful landmarks to identify the relative location of the pancreas. The splenic and portal veins extend from the hila of the spleen and liver, respectively, travel through the abdominal cavity and join at a position close to the head of the pancreas known as the portal confluence. A third vein, the superior mesenteric vein, anastomoses with the other two veins at the portal confluence. An automatic segmentation framework for obtaining the splenic vein, portal confluence and superior mesenteric vein is proposed using 17 contrast enhanced computed-tomography datasets. The proposed method uses outputs from the multi-organ multi-atlas label fusion and Frangi vesselness filter to obtain automatic seed points for vessel tracking and generation of statistical models of the desired vessels. The approach shows ability to identify the vessels and improve localization of the pancreas within the abdomen.

  7. Automatic finger joint synovitis localization in ultrasound images

    NASA Astrophysics Data System (ADS)

    Nurzynska, Karolina; Smolka, Bogdan

    2016-04-01

    A long-lasting inflammation of joints results between others in many arthritis diseases. When not cured, it may influence other organs and general patients' health. Therefore, early detection and running proper medical treatment are of big value. The patients' organs are scanned with high frequency acoustic waves, which enable visualization of interior body structures through an ultrasound sonography (USG) image. However, the procedure is standardized, different projections result in a variety of possible data, which should be analyzed in short period of time by a physician, who is using medical atlases as a guidance. This work introduces an efficient framework based on statistical approach to the finger joint USG image, which enables automatic localization of skin and bone regions, which are then used for localization of the finger joint synovitis area. The processing pipeline realizes the task in real-time and proves high accuracy when compared to annotation prepared by the expert.

  8. Automated vision system for fabric defect inspection using Gabor filters and PCNN.

    PubMed

    Li, Yundong; Zhang, Cheng

    2016-01-01

    In this study, an embedded machine vision system using Gabor filters and Pulse Coupled Neural Network (PCNN) is developed to identify defects of warp-knitted fabrics automatically. The system consists of smart cameras and a Human Machine Interface (HMI) controller. A hybrid detection algorithm combing Gabor filters and PCNN is running on the SOC processor of the smart camera. First, Gabor filters are employed to enhance the contrast of images captured by a CMOS sensor. Second, defect areas are segmented by PCNN with adaptive parameter setting. Third, smart cameras will notice the controller to stop the warp-knitting machine once defects are found out. Experimental results demonstrate that the hybrid method is superior to Gabor and wavelet methods on detection accuracy. Actual operations in a textile factory verify the effectiveness of the inspection system. PMID:27386251

  9. Structure of the Gabor matrix and efficient numerical algorithms for discrete Gabor expansions

    NASA Astrophysics Data System (ADS)

    Qiu, Sigang; Feichtinger, Hans G.

    1994-09-01

    The standard way to obtain suitable coefficients for the (non-orthogonal) Gabor expansion of a general signal for a given Gabor atom g and a pair of lattice constants in the (discrete) time/frequency plane, requires to compute the dual Gabor window function g- first. In this paper, we present an explicit description of the sparsity, the block and banded structure of the Gabor frame matrix G. On this basis efficient algorithms are developed for computing g- by solving the linear equation g- * G equals g with the conjugate- gradients method. Using the dual Gabor wavelet, a fast Gabor reconstruction algorithm with very low computational complexity is proposed.

  10. Structuring Lecture Videos by Automatic Projection Screen Localization and Analysis.

    PubMed

    Li, Kai; Wang, Jue; Wang, Haoqian; Dai, Qionghai

    2015-06-01

    We present a fully automatic system for extracting the semantic structure of a typical academic presentation video, which captures the whole presentation stage with abundant camera motions such as panning, tilting, and zooming. Our system automatically detects and tracks both the projection screen and the presenter whenever they are visible in the video. By analyzing the image content of the tracked screen region, our system is able to detect slide progressions and extract a high-quality, non-occluded, geometrically-compensated image for each slide, resulting in a list of representative images that reconstruct the main presentation structure. Afterwards, our system recognizes text content and extracts keywords from the slides, which can be used for keyword-based video retrieval and browsing. Experimental results show that our system is able to generate more stable and accurate screen localization results than commonly-used object tracking methods. Our system also extracts more accurate presentation structures than general video summarization methods, for this specific type of video. PMID:26357345

  11. Characterizations of Gabor-Gram matrices and efficient computations of discrete Gabor coefficients

    NASA Astrophysics Data System (ADS)

    Qiu, Sigang

    1995-09-01

    The motivation of this paper is to give a direct way for determining the crucial Gabor coefficients. Based on the characterized Gabor-Gram matrix structures, we are able to propose fast and direct computational algorithms. We derive also a new way for dual Gabor atoms.

  12. NABS: non-local automatic brain hemisphere segmentation.

    PubMed

    Romero, José E; Manjón, José V; Tohka, Jussi; Coupé, Pierrick; Robles, Montserrat

    2015-05-01

    In this paper, we propose an automatic method to segment the five main brain sub-regions (i.e. left/right hemispheres, left/right cerebellum and brainstem) from magnetic resonance images. The proposed method uses a library of pre-labeled brain images in a stereotactic space in combination with a non-local label fusion scheme for segmentation. The main novelty of the proposed method is the use of a multi-label block-wise label fusion strategy specifically designed to deal with the classification of main brain sub-volumes that process only specific parts of the brain images significantly reducing the computational burden. The proposed method has been quantitatively evaluated against manual segmentations. The evaluation showed that the proposed method was faster while producing more accurate segmentations than a current state-of-the-art method. We also present evidences suggesting that the proposed method was more robust against brain pathologies than the compared method. Finally, we demonstrate the clinical value of our method compared to the state-of-the-art approach in terms of the asymmetry quantification in Alzheimer's disease. PMID:25660644

  13. Complete Gabor transformation for signal representation.

    PubMed

    Yao, J

    1993-01-01

    Properties of the Gabor transformation used for image representation are discussed. The properties can be expressed in matrix notation, and the complete Gabor coefficients can be found by multiplying the inverse of the Gabor (1946) matrix and the signal vector. The Gabor matrix can be decomposed into the product of a sparse constant complex matrix and another sparse matrix that depends only on the window function. A fast algorithm is suggested to compute the inverse of the window function matrix, enabling discrete signals to be transformed into generalized nonorthogonal Gabor representations efficiently. A comparison is made between this method and the analytical method. The relation between the window function matrix and the biorthogonal functions is demonstrated. A numerical computation method for the biorthogonal functions is proposed. PMID:18296205

  14. Gabor-based anisotropic diffusion for speckle noise reduction in medical ultrasonography.

    PubMed

    Zhang, Qi; Han, Hong; Ji, Chunhong; Yu, Jinhua; Wang, Yuanyuan; Wang, Wenping

    2014-06-01

    In ultrasound (US), optical coherence tomography, synthetic aperture radar, and other coherent imaging systems, images are corrupted by multiplicative speckle noise that obscures image interpretation. An anisotropic diffusion (AD) method based on the Gabor transform, named Gabor-based anisotropic diffusion (GAD), is presented to suppress speckle in medical ultrasonography. First, an edge detector using the Gabor transform is proposed to capture directionality of tissue edges and discriminate edges from noise. Then the edge detector is embedded into the partial differential equation of AD to guide the diffusion process and iteratively denoise images. To enhance GAD's adaptability, parameters controlling diffusion are determined from a fully formed speckle region that is automatically detected. We evaluate the GAD on synthetic US images simulated with three models and clinical images acquired in vivo. Compared with seven existing speckle reduction methods, the GAD is superior to other methods in terms of noise reduction and detail preservation. PMID:24977366

  15. Computational frameworks for discrete Gabor analysis

    NASA Astrophysics Data System (ADS)

    Strohmer, Thomas

    1997-10-01

    The Gabor transform yields a discrete representation of a signal in the phase space. Since the Gabor transform is non-orthogonal, efficient reconstruction of a signal from its phase space samples is not straightforward and involves the computation of the so- called dual Gabor function. We present a unifying approach to the derivation of numerical algorithms for discrete Gabor analysis, based on unitary matrix factorization. The factorization point of view is notably useful for the design of efficient numerical algorithms. This presentation is the first systematic account of its kind. In particular, it is shown that different algorithms for the computation of the dual window correspond to different factorizations of the frame operator. Simple number theoretic conditions on the time-frequency lattice parameters imply additional structural properties of the frame operator.

  16. Signals embedded in the OBS records, in light of Gabor Spectral Analysis

    NASA Astrophysics Data System (ADS)

    Chang, T.; Wang, Y.; Chang, C.; Lee, C.

    2005-12-01

    Since the last decades, seismological survey has been expanded to marine area, with goal of making up the deficiency of seismogenic study outside the land. Although teleseismic data can resolve plate boundaries location and certain seismic parameters for great earthquake, local seismogenic frame can be merely emerged by the seismic network in situ. The Ocean Bottom Seismometer (OBS), therefore, is developing for this kind of purpose and becoming an important facility for seismological study. This work introduces a synthesized spectral method to analyze the seismograms recorded by 15 OBS deployed at the Okinawa trough in 14 days (Nov. 19 ~Dec. 2, 2003). Geological background of Okinawa trough is well known to correspond with the back-arc spreading in the regime of the Philippine Sea plate subducting northward beneath the Eurasia plate. As the complex affections at sea bottom, for instance, strong current, slope slumping, turbidite flow, and even sea animal attack, the OBS seismogram show a rather noisy sequence in comparison with the record on land. However, hundreds of tectonic earthquake can be extracted from such noisy records (done by Drs. Lin and Sibuet). Our job is to sort out the signals with the distinguishable sources by means of a systematically spectral analysis. The continuous wavelet transform and short-term Fourier transform, both taking Gaussian function as kernel, are synthesized as the Gabor transform in data process. The use of a limited Gaussian window along time axis with negligible low frequency error can largely enhance the stability of discrete Fourier spectrum. With a proper window factor selection, the Gabor transform can improve the resolution of spectrogram in time domain. We have converted the OBS records into spectrograms to detect the variation of signal causes. Up-to-date, some tremors signals and strong current oscillations have been told apart from these continuous records with varied frequency composing. We anticipate the further

  17. Gabor's signal expansion and the Zak transform.

    PubMed

    Bastiaans, M J

    1994-08-10

    Gabor's expansion of a signal into a discrete set of shifted and modulated versions of an elementary signal is introduced, and its relation to sampling of the sliding-window spectrum is shown. It is shown how Gabor's expansion coefficients can be found as samples of the sliding-window spectrum, in which the window function is related to the elementary signal in such a way that the set of shifted and modulated elementary signals is biorthonormal to the corresponding set of window functions. The Zak transform is introduced, and its intimate relationship to Gabor's signal expansion is demonstrated. It is shown how the Zak transform can be helpful in determining the window function that corresponds to a given elementary signal and how it can be used to find Gabor's expansion coefficients. The continuous-time and the discrete-time cases are considered, and, by sampling the continuous frequency variable that still occurs in the discrete-time case, the discrete Zak transform and the discrete Gabor transform are introduced. It is shown how the discrete transforms enable us to determine Gabor's expansion coefficients by a fast computer algorithm, which is analogous to the well-known fast Fourier-transform= algorithm. PMID:20935912

  18. Proposal of Local Automatic Weighing Attribute in CBIR.

    PubMed

    Jones Ferreira de Lucena, David; Costa Oliviera, Marcelo; Pamponet Machado, Aydano

    2015-01-01

    Lung cancer is the most common malignant lesion and the principal cause of cancer-related death worldwide. This problem encourages researchers to build computer-aided solutions to help diagnose lung cancer. Content-based image retrieval (CBIR) systems are very promising in this context due to a large number of image generated everyday. However, semantic gaps have limited CBIR applicability. This work proposes a new approach to automatically adjust CBIR attribute weights to reflect users' semantic interpretation on retrieval process, minimizing the semantic gap problem and improving retrieval accuracy. PMID:26262321

  19. Automatic Blocking Of QR and LU Factorizations for Locality

    SciTech Connect

    Yi, Q; Kennedy, K; You, H; Seymour, K; Dongarra, J

    2004-03-26

    QR and LU factorizations for dense matrices are important linear algebra computations that are widely used in scientific applications. To efficiently perform these computations on modern computers, the factorization algorithms need to be blocked when operating on large matrices to effectively exploit the deep cache hierarchy prevalent in today's computer memory systems. Because both QR (based on Householder transformations) and LU factorization algorithms contain complex loop structures, few compilers can fully automate the blocking of these algorithms. Though linear algebra libraries such as LAPACK provides manually blocked implementations of these algorithms, by automatically generating blocked versions of the computations, more benefit can be gained such as automatic adaptation of different blocking strategies. This paper demonstrates how to apply an aggressive loop transformation technique, dependence hoisting, to produce efficient blockings for both QR and LU with partial pivoting. We present different blocking strategies that can be generated by our optimizer and compare the performance of auto-blocked versions with manually tuned versions in LAPACK, both using reference BLAS, ATLAS BLAS and native BLAS specially tuned for the underlying machine architectures.

  20. Gabor domain optical coherence microscopy

    NASA Astrophysics Data System (ADS)

    Murali, Supraja

    Time domain Optical Coherence Tomography (TD-OCT), first reported in 1991, makes use of the low temporal coherence properties of a NIR broadband laser to create depth sectioning of up to 2mm under the surface using optical interferometry and point to point scanning. Prior and ongoing work in OCT in the research community has concentrated on improving axial resolution through the development of broadband sources and speed of image acquisition through new techniques such as Spectral domain OCT (SD-OCT). In SD-OCT, an entire depth scan is acquired at once with a low numerical aperture (NA) objective lens focused at a fixed point within the sample. In this imaging geometry, a longer depth of focus is achieved at the expense of lateral resolution, which is typically limited to 10 to 20 mum. Optical Coherence Microscopy (OCM), introduced in 1994, combined the advantages of high axial resolution obtained in OCT with high lateral resolution obtained by increasing the NA of the microscope placed in the sample arm. However, OCM presented trade-offs caused by the inverse quadratic relationship between the NA and the DOF of the optics used. For applications requiring high lateral resolution, such as cancer diagnostics, several solutions have been proposed including the periodic manual re-focusing of the objective lens in the time domain as well as the spectral domain C-mode configuration in order to overcome the loss in lateral resolution outside the DOF. In this research, we report for the first time, high speed, sub-cellular imaging (lateral resolution of 2 mum) in OCM using a Gabor domain image processing algorithm with a custom designed and fabricated dynamic focus microscope interfaced to a Ti:Sa femtosecond laser centered at 800 nm within an SD-OCM configuration. It is envisioned that this technology will provide a non-invasive replacement for the current practice of multiple biopsies for skin cancer diagnosis. The research reported here presents three important advances

  1. Gabor-based kernel PCA with fractional power polynomial models for face recognition.

    PubMed

    Liu, Chengjun

    2004-05-01

    This paper presents a novel Gabor-based kernel Principal Component Analysis (PCA) method by integrating the Gabor wavelet representation of face images and the kernel PCA method for face recognition. Gabor wavelets first derive desirable facial features characterized by spatial frequency, spatial locality, and orientation selectivity to cope with the variations due to illumination and facial expression changes. The kernel PCA method is then extended to include fractional power polynomial models for enhanced face recognition performance. A fractional power polynomial, however, does not necessarily define a kernel function, as it might not define a positive semidefinite Gram matrix. Note that the sigmoid kernels, one of the three classes of widely used kernel functions (polynomial kernels, Gaussian kernels, and sigmoid kernels), do not actually define a positive semidefinite Gram matrix either. Nevertheless, the sigmoid kernels have been successfully used in practice, such as in building support vector machines. In order to derive real kernel PCA features, we apply only those kernel PCA eigenvectors that are associated with positive eigenvalues. The feasibility of the Gabor-based kernel PCA method with fractional power polynomial models has been successfully tested on both frontal and pose-angled face recognition, using two data sets from the FERET database and the CMU PIE database, respectively. The FERET data set contains 600 frontal face images of 200 subjects, while the PIE data set consists of 680 images across five poses (left and right profiles, left and right half profiles, and frontal view) with two different facial expressions (neutral and smiling) of 68 subjects. The effectiveness of the Gabor-based kernel PCA method with fractional power polynomial models is shown in terms of both absolute performance indices and comparative performance against the PCA method, the kernel PCA method with polynomial kernels, the kernel PCA method with fractional power

  2. Iterative local-global energy minimization for automatic extraction of objects of interest.

    PubMed

    Hua, Gang; Liu, Zicheng; Zhang, Zhengyou; Wu, Ying

    2006-10-01

    We propose a novel global-local variational energy to automatically extract objects of interest from images. Previous formulations only incorporate local region potentials, which are sensitive to incorrectly classified pixels during iteration. We introduce a global likelihood potential to achieve better estimation of the foreground and background models and, thus, better extraction results. Extensive experiments demonstrate its efficacy. PMID:16986550

  3. Automatic pattern localization across layout database and photolithography mask

    NASA Astrophysics Data System (ADS)

    Morey, Philippe; Brault, Frederic; Beisser, Eric; Ache, Oliver; Röth, Klaus-Dieter

    2016-03-01

    Advanced process photolithography masks require more and more controls for registration versus design and critical dimension uniformity (CDU). The distribution of the measurement points should be distributed all over the whole mask and may be denser in areas critical to wafer overlay requirements. This means that some, if not many, of theses controls should be made inside the customer die and may use non-dedicated patterns. It is then mandatory to access the original layout database to select patterns for the metrology process. Finding hundreds of relevant patterns in a database containing billions of polygons may be possible, but in addition, it is mandatory to create the complete metrology job fast and reliable. Combining, on one hand, a software expertise in mask databases processing and, on the other hand, advanced skills in control and registration equipment, we have developed a Mask Dataprep Station able to select an appropriate number of measurement targets and their positions in a huge database and automatically create measurement jobs on the corresponding area on the mask for the registration metrology system. In addition, the required design clips are generated from the database in order to perform the rendering procedure on the metrology system. This new methodology has been validated on real production line for the most advanced process. This paper presents the main challenges that we have faced, as well as some results on the global performances.

  4. Automatic localization of vertebrae based on convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Shen, Wei; Yang, Feng; Mu, Wei; Yang, Caiyun; Yang, Xin; Tian, Jie

    2015-03-01

    Localization of the vertebrae is of importance in many medical applications. For example, the vertebrae can serve as the landmarks in image registration. They can also provide a reference coordinate system to facilitate the localization of other organs in the chest. In this paper, we propose a new vertebrae localization method using convolutional neural networks (CNN). The main advantage of the proposed method is the removal of hand-crafted features. We construct two training sets to train two CNNs that share the same architecture. One is used to distinguish the vertebrae from other tissues in the chest, and the other is aimed at detecting the centers of the vertebrae. The architecture contains two convolutional layers, both of which are followed by a max-pooling layer. Then the output feature vector from the maxpooling layer is fed into a multilayer perceptron (MLP) classifier which has one hidden layer. Experiments were performed on ten chest CT images. We used leave-one-out strategy to train and test the proposed method. Quantitative comparison between the predict centers and ground truth shows that our convolutional neural networks can achieve promising localization accuracy without hand-crafted features.

  5. Hamiltonian deformations of Gabor frames: First steps

    PubMed Central

    de Gosson, Maurice A.

    2015-01-01

    Gabor frames can advantageously be redefined using the Heisenberg–Weyl operators familiar from harmonic analysis and quantum mechanics. Not only does this redefinition allow us to recover in a very simple way known results of symplectic covariance, but it immediately leads to the consideration of a general deformation scheme by Hamiltonian isotopies (i.e. arbitrary paths of non-linear symplectic mappings passing through the identity). We will study in some detail an associated weak notion of Hamiltonian deformation of Gabor frames, using ideas from semiclassical physics involving coherent states and Gaussian approximations. We will thereafter discuss possible applications and extensions of our method, which can be viewed – as the title suggests – as the very first steps towards a general deformation theory for Gabor frames. PMID:25892903

  6. Matrix reformulation of the Gabor transform

    NASA Astrophysics Data System (ADS)

    Balart, Rogelio

    1992-06-01

    We have observed that if one restricts the von Neumann lattice to N points on the time axis and M points in the frequency axis there are, by definition, only MN independent Gabor coefficients. If the data is sampled such that there are exactly MN samples, then the forward and inverse Gabor transforms should be representable as linear transformations in CMN, the MN-dimensional vector space over the complex numbers, and the relationships that hold become matrix equations. These matrix equations are formulated, and some conclusions are drawn about the relative merits of using some methods as opposed to others, i.e., speed versus accuracy as well as whether or not the coefficients that are obtained via some methods are true Gabor coefficients.

  7. Matrix reformulation of the Gabor transform

    NASA Astrophysics Data System (ADS)

    Balart, Rogelio

    1991-12-01

    We have observed that if one restricts the von Neumann lattice to N points on the time axis and M points in the frequency axis there are, by definition, only MN independent Gabor coefficients. If the data is sampled such that there are exactly MN samples, then the forward and inverse Gabor transforms should be representable as linear transformations in CMN, the MN-dimensional vector space over the complex numbers, and the relationships that hold become matrix equations. These matrix equations are formulated, and some conclusions are drawn about the relative merits of using some methods as opposed to others, i.e., speed versus accuracy, as well as whether or not the coefficients that are obtained via some methods are true Gabor coefficients.

  8. Discrete Gabor Filters For Binocular Disparity Measurement

    NASA Technical Reports Server (NTRS)

    Weiman, Carl F. R.

    1995-01-01

    Discrete Gabor filters proposed for use in determining binocular disparity - difference between positions of same feature or object depicted in stereoscopic images produced by two side-by-side cameras aimed in parallel. Magnitude of binocular disparity used to estimate distance from cameras to feature or object. In one potential application, cameras charge-coupled-device video cameras in robotic vision system, and binocular disparities and distance estimates used as control inputs - for example, to control approaches to objects manipulated or to maintain safe distances from obstacles. Binocular disparities determined from phases of discretized Gabor transforms.

  9. Localization accuracy from automatic and semi-automatic rigid registration of locally-advanced lung cancer targets during image-guided radiation therapy

    SciTech Connect

    Robertson, Scott P.; Weiss, Elisabeth; Hugo, Geoffrey D.

    2012-01-15

    Purpose: To evaluate localization accuracy resulting from rigid registration of locally-advanced lung cancer targets using fully automatic and semi-automatic protocols for image-guided radiation therapy. Methods: Seventeen lung cancer patients, fourteen also presenting with involved lymph nodes, received computed tomography (CT) scans once per week throughout treatment under active breathing control. A physician contoured both lung and lymph node targets for all weekly scans. Various automatic and semi-automatic rigid registration techniques were then performed for both individual and simultaneous alignments of the primary gross tumor volume (GTV{sub P}) and involved lymph nodes (GTV{sub LN}) to simulate the localization process in image-guided radiation therapy. Techniques included ''standard'' (direct registration of weekly images to a planning CT), ''seeded'' (manual prealignment of targets to guide standard registration), ''transitive-based'' (alignment of pretreatment and planning CTs through one or more intermediate images), and ''rereferenced'' (designation of a new reference image for registration). Localization error (LE) was assessed as the residual centroid and border distances between targets from planning and weekly CTs after registration. Results: Initial bony alignment resulted in centroid LE of 7.3 {+-} 5.4 mm and 5.4 {+-} 3.4 mm for the GTV{sub P} and GTV{sub LN}, respectively. Compared to bony alignment, transitive-based and seeded registrations significantly reduced GTV{sub P} centroid LE to 4.7 {+-} 3.7 mm (p = 0.011) and 4.3 {+-} 2.5 mm (p < 1 x 10{sup -3}), respectively, but the smallest GTV{sub P} LE of 2.4 {+-} 2.1 mm was provided by rereferenced registration (p < 1 x 10{sup -6}). Standard registration significantly reduced GTV{sub LN} centroid LE to 3.2 {+-} 2.5 mm (p < 1 x 10{sup -3}) compared to bony alignment, with little additional gain offered by the other registration techniques. For simultaneous target alignment, centroid LE as low

  10. Automatism

    PubMed Central

    McCaldon, R. J.

    1964-01-01

    Individuals can carry out complex activity while in a state of impaired consciousness, a condition termed “automatism”. Consciousness must be considered from both an organic and a psychological aspect, because impairment of consciousness may occur in both ways. Automatism may be classified as normal (hypnosis), organic (temporal lobe epilepsy), psychogenic (dissociative fugue) or feigned. Often painstaking clinical investigation is necessary to clarify the diagnosis. There is legal precedent for assuming that all crimes must embody both consciousness and will. Jurists are loath to apply this principle without reservation, as this would necessitate acquittal and release of potentially dangerous individuals. However, with the sole exception of the defence of insanity, there is at present no legislation to prohibit release without further investigation of anyone acquitted of a crime on the grounds of “automatism”. PMID:14199824

  11. Automatic localization of cerebral cortical malformations using fractal analysis

    NASA Astrophysics Data System (ADS)

    De Luca, A.; Arrigoni, F.; Romaniello, R.; Triulzi, F. M.; Peruzzo, D.; Bertoldo, A.

    2016-08-01

    Malformations of cortical development (MCDs) encompass a variety of brain disorders affecting the normal development and organization of the brain cortex. The relatively low incidence and the extreme heterogeneity of these disorders hamper the application of classical group level approaches for the detection of lesions. Here, we present a geometrical descriptor for a voxel level analysis based on fractal geometry, then define two similarity measures to detect the lesions at single subject level. The pipeline was applied to 15 normal children and nine pediatric patients affected by MCDs following two criteria, maximum accuracy (WACC) and minimization of false positives (FPR), and proved that our lesion detection algorithm is able to detect and locate abnormalities of the brain cortex with high specificity (WACC  =  85%, FPR  =  96%), sensitivity (WACC  =  83%, FPR  =  63%) and accuracy (WACC  =  85%, FPR  =  90%). The combination of global and local features proves to be effective, making the algorithm suitable for the detection of both focal and diffused malformations. Compared to other existing algorithms, this method shows higher accuracy and sensitivity.

  12. Automatic localization of cerebral cortical malformations using fractal analysis.

    PubMed

    De Luca, A; Arrigoni, F; Romaniello, R; Triulzi, F M; Peruzzo, D; Bertoldo, A

    2016-08-21

    Malformations of cortical development (MCDs) encompass a variety of brain disorders affecting the normal development and organization of the brain cortex. The relatively low incidence and the extreme heterogeneity of these disorders hamper the application of classical group level approaches for the detection of lesions. Here, we present a geometrical descriptor for a voxel level analysis based on fractal geometry, then define two similarity measures to detect the lesions at single subject level. The pipeline was applied to 15 normal children and nine pediatric patients affected by MCDs following two criteria, maximum accuracy (WACC) and minimization of false positives (FPR), and proved that our lesion detection algorithm is able to detect and locate abnormalities of the brain cortex with high specificity (WACC  =  85%, FPR  =  96%), sensitivity (WACC  =  83%, FPR  =  63%) and accuracy (WACC  =  85%, FPR  =  90%). The combination of global and local features proves to be effective, making the algorithm suitable for the detection of both focal and diffused malformations. Compared to other existing algorithms, this method shows higher accuracy and sensitivity. PMID:27444964

  13. Jet noise analysis by Gabor spectrogram

    NASA Astrophysics Data System (ADS)

    Xu, Qiang

    2006-04-01

    A research was conducted to determine the functions of a set of nozzle pairs. The aeroacoustical performance of these pairs can be used to analyze the deformation of structure and change of jet condition. The jet noise signal was measured by a microphone placed in the radiation field of jet flow. In addition to some traditional methods used for analyzing noise both in time and frequency domain, Gabor spectrogram is adopted to obtain the joint time-frequency pattern of the jet noise under different jet conditions from nozzles with different structures. The jet noise from three nozzle pairs worked under two types of working conditions is treated by Gabor spectrogram. One condition is both nozzles in the nozzle pair keep their structure at a fixed chamber pressure, while another condition is one of these two nozzles' throat size decreases during the jet procedure under a fixed chamber pressure. Gabor spectrograms with different orders for the jet noise under the second condition are obtained and compared. Then a rational order is selected in analyzing the jet noise. Results are presented in this paper. The Gabor spectrogram patterns of these two conditions are with marked difference. The noise keeps its frequency peak during the whole jet procedure in the first condition. But there is a frequency peak shift in the second condition at a certain size of throat. The distribution of frequency peak along with the decrease of throat presents two states. This would be helpful for nozzle structure recognition.

  14. Gabor's hologram in a modern perspective

    NASA Astrophysics Data System (ADS)

    Repetto, L.; Pellistri, F.; Piano, E.; Pontiggia, C.

    2004-07-01

    We review Dennis Gabor's early results in light of more than fifty years of technological achievements, including the advent of CCD cameras and fast computers. By applying digital reading to one of the first holograms, we demonstrate the continuity between the classical technique and the digital implementation. This experiment can be used as a demonstration without needing the instrumentation of an optics laboratory.

  15. Automatic localization of the left ventricle in cardiac MRI images using deep learning.

    PubMed

    Emad, Omar; Yassine, Inas A; Fahmy, Ahmed S

    2015-08-01

    Automatic localization of the left ventricle (LV) in cardiac MRI images is an essential step for automatic segmentation, functional analysis, and content based retrieval of cardiac images. In this paper, we introduce a new approach based on deep Convolutional Neural Network (CNN) to localize the LV in cardiac MRI in short axis views. A six-layer CNN with different kernel sizes was employed for feature extraction, followed by Softmax fully connected layer for classification. The pyramids of scales analysis was introduced in order to take account of the different sizes of the heart. A publically-available database of 33 patients was used for learning and testing. The proposed method was able it localize the LV with 98.66%, 83.91% and 99.07% for accuracy, sensitivity and specificity respectively. PMID:26736354

  16. An improved Gabor enhancement method for low-quality fingerprint images

    NASA Astrophysics Data System (ADS)

    Geng, Hao; Li, Jicheng; Zhou, Jinwei; Chen, Dong

    2015-10-01

    The criminal's fingerprints often refer to those fingerprints that are extracted from crime scene and have played an important role in police' investigation and cracking the cases, but these fingerprints have features such as blur, incompleteness and low-contrast of ridges. Traditional fingerprint enhancement and identification methods have some limitations and the current automated fingerprint identification system (AFIS) hasn't not been applied extensively in police' investigation. Since the Gabor filter has drawbacks such as poor efficiency, low preciseness of the extracted ridge's orientation parameters, the enhancements of low-contrast fingerprint images can't achieve the desired effects. Therefore, an improved Gabor enhancement for low-quality fingerprint is proposed in this paper. Firstly, orientation image templates with different scales were used to distinguish the orientation images in the fingerprint area, and then orientation parameters of ridge were calculated. Secondly, mean frequencies of ridge were extracted based on local window of ridge's orientation and mean frequency parameters of ridges were calculated. Thirdly, the size and orientation of Gabor filter were self-adjusted according to local ridge's orientation and mean frequency. Finally, the poor-quality fingerprint images were enhanced. In the experiment, the improved Gabor filter has better performance for low-quality fingerprint images when compared with the traditional filtering methods.

  17. Automatic optimization of localized heat treatment for Al-Si-Mg alloys

    NASA Astrophysics Data System (ADS)

    Ludwig, A.; Holzmann, T.

    2016-03-01

    Material properties of aluminium alloys can usually be achieved by a heat treatment and quenching procedure. In case that only local strengthening is needed, a local heat treatment and quenching strategy could be an option to the energy intensive, time consuming and costly treatment of the whole part. One of the essential problem using a local strengthening procedure is the lack of knowledge about suitable process parameters. Therefore, a multiple criteria optimization approach with local strengthening as target function was set up, whereby the material constitution was calculated based on the precipitation evolution during local heat treatment and cooling. By automatically varying the exposure time and laser power, a series of process simulations was performed to find adequate process parameters for the sufficient local strengthening of the alloy.

  18. Automatically designed machine vision system for the localization of CCA transverse section in ultrasound images.

    PubMed

    Benes, Radek; Karasek, Jan; Burget, Radim; Riha, Kamil

    2013-01-01

    The common carotid artery (CCA) is a source of important information that doctors can use to evaluate the patients' health. The most often measured parameters are arterial stiffness, lumen diameter, wall thickness, and other parameters where variation with time is usually measured. Unfortunately, the manual measurement of dynamic parameters of the CCA is time consuming, and therefore, for practical reasons, the only alternative is automatic approach. The initial localization of artery is important and must precede the main measurement. This article describes a novel method for the localization of CCA in the transverse section of a B-mode ultrasound image. The novel method was designed automatically by using the grammar-guided genetic programming (GGGP). The GGGP searches for the best possible combination of simple image processing tasks (independent building blocks). The best possible solution is represented with the highest detection precision. The method is tested on a validation database of CCA images that was specially created for this purpose and released for use by other scientists. The resulting success of the proposed solution was 82.7%, which exceeded the current state of the art by 4% while the computation time requirements were acceptable. The paper also describes an automatic method that was used in designing the proposed solution. This automatic method provides a universal approach to designing complex solutions with the support of evolutionary algorithms. PMID:23031488

  19. Gabor lens focusing of a negative ion beam

    SciTech Connect

    Palkovic, J.A.; Mills, F.E.; Schmidt, C.; Young, D.E.

    1989-05-01

    Gabor or plasma lenses have previously been used to focus intense beams of positive ions at energies from 10 keV to 5 MeV. It is the large electrostatic field of the non-neutral plasma in the Gabor lens which is responsible for the focusing. Focusing an ion beam with a given sign of charge in a Gabor lens requires a non-neutral plasma with the opposite sign of charge as the beam. A Gabor lens constructed at Fermilab has been used to focus a 30 keV proton beam with good optical quality. We discuss studies of the action of a Gabor lens on a beam of negative ions. A Gabor lens has been considered for matching an H/sup /minus// beam into an RFQ in the redesign of the low energy section of the Fermilab linac. 9 refs., 3 figs., 1 tab.

  20. Comparison of manual and automatic onset Time picking for local earthquake in North Eastern Italy.

    NASA Astrophysics Data System (ADS)

    Spallarossa, D.; Tiberi, L.; Costa, G.

    2012-04-01

    Automatic estimates of earthquake parameters continues to be of considerable interest to the seismological community. The automatic processing of seismic data, whether for real-time seismic warning system or to reprocessing large amount of seismic recordings, is increasingly being demanded by seismologists. In this study is presented a new method used for automatic phase picking (P and S) which include envelope function calculation, STA/LTA detectors and AR picking algorithms based on the Akaike information criterion (AIC) The main characteristics of the proposed picking algorithm are: a) Pre-filtering and envelope calculation to prearrange the onset; b) Preliminary detection of P onset using both the AIC based picker and the STA/LTA picker; c) S/N analysis, P validation, filtering and re-picking; d) Preliminary earthquake location; e) Detection of S onset adopting the AIC based picker; f) S/N analysis, S validation; g) Earthquake location. The algorithm is applied to a reference data composed by 200 events set with very heterogeneous qualities of P and S onsets acquired by South Eastern Alps Transfontier network from 01/01/2008 to 03/31/2008 in North Eastern Italy and surrounding regions. These data are collected through the use of the software Antelope, an integrated collection of programs for data management and seismic data analysis. The reliability and robustness of the proposed algorithm is tested by comparing manually derived P and S readings (determined by an experienced seismic analyst), serving as reference picks, with the corresponding automatically estimated P and S arrival times. An additional analysis is comparing these automatic picks with the ones produced by Antelope, which used only STA/LTA detectors and finally studying the effect of these different set of arrival times in the resultant localizations for each database event. Preliminary results indicate that seismic detectors which integrate different techniques could improve the stability of the

  1. Gabor wavelet associative memory for face recognition.

    PubMed

    Zhang, Haihong; Zhang, Bailing; Huang, Weimin; Tian, Qi

    2005-01-01

    This letter describes a high-performance face recognition system by combining two recently proposed neural network models, namely Gabor wavelet network (GWN) and kernel associative memory (KAM), into a unified structure called Gabor wavelet associative memory (GWAM). GWAM has superior representation capability inherited from GWN and consequently demonstrates a much better recognition performance than KAM. Extensive experiments have been conducted to evaluate a GWAM-based recognition scheme using three popular face databases, i.e., FERET database, Olivetti-Oracle Research Lab (ORL) database and AR face database. The experimental results consistently show our scheme's superiority and demonstrate its very high-performance comparing favorably to some recent face recognition methods, achieving 99.3% and 100% accuracy, respectively, on the former two databases, exhibiting very robust performance on the last database against varying illumination conditions. PMID:15732406

  2. Analyzing subcellular structure with optical Fourier filtering based on Gabor filters

    NASA Astrophysics Data System (ADS)

    Boustany, Nada N.; Sierra, Heidy

    2013-02-01

    Label-free measurement of subcellular morphology can be used to track dynamically cellular function under various conditions and has important applications in cellular monitoring and in vitro cell assays. We show that optical filtering of scattered light by two-dimensional Gabor filters allows for direct and highly sensitive measurement of sample structure. The Gabor filters, which are defined by their spatial frequency, orientation and Gaussian envelope, can be used to track locally and in situ the characteristic size and orientation of structures within the sample. Our method consists of sequentially implementing a set of Gabor filters via a spatial light modulator placed in a conjugate Fourier plane during optical imaging and identifying the filters that yield maximum signal. Using this setup, we show that Gabor filtering of light forward-scattered by spheres yields an optical response which varies linearly with diameter between 100nm and 2000nm. The optical filtering sensitivity to changes in diameter is on the order of 20nm and can be achieved at low image resolution. We use numerical simulations to demonstrate that this linear response can be predicted from scatter theory and does not vary significantly with changes in refractive index ratio. By applying this Fourier filtering method in samples consisting of diatoms and cells, we generate false-color images of the object that encode at each pixel the size of the local structures within the object. The resolution of these encoded size maps in on the order of 0.36μm. The pixel histograms of these encoded images directly provide 20nm resolved "size spectra", depicting the size distribution of structures within the analyzed object. We use these size spectra to differentiate the morphology of apoptosis-competent and bax/bak null apoptosis-resistant cells during cell death. We also utilize the sensitivity of the Gabor filters to object orientation to track changes in organelle morphology, and detect mitochondrial

  3. Automatic block-matching registration to improve lung tumor localization during image-guided radiotherapy

    NASA Astrophysics Data System (ADS)

    Robertson, Scott Patrick

    To improve relatively poor outcomes for locally-advanced lung cancer patients, many current efforts are dedicated to minimizing uncertainties in radiotherapy. This enables the isotoxic delivery of escalated tumor doses, leading to better local tumor control. The current dissertation specifically addresses inter-fractional uncertainties resulting from patient setup variability. An automatic block-matching registration (BMR) algorithm is implemented and evaluated for the purpose of directly localizing advanced-stage lung tumors during image-guided radiation therapy. In this algorithm, small image sub-volumes, termed "blocks", are automatically identified on the tumor surface in an initial planning computed tomography (CT) image. Each block is independently and automatically registered to daily images acquired immediately prior to each treatment fraction. To improve the accuracy and robustness of BMR, this algorithm incorporates multi-resolution pyramid registration, regularization with a median filter, and a new multiple-candidate-registrations technique. The result of block-matching is a sparse displacement vector field that models local tissue deformations near the tumor surface. The distribution of displacement vectors is aggregated to obtain the final tumor registration, corresponding to the treatment couch shift for patient setup correction. Compared to existing rigid and deformable registration algorithms, the final BMR algorithm significantly improves the overlap between target volumes from the planning CT and registered daily images. Furthermore, BMR results in the smallest treatment margins for the given study population. However, despite these improvements, large residual target localization errors were noted, indicating that purely rigid couch shifts cannot correct for all sources of inter-fractional variability. Further reductions in treatment uncertainties may require the combination of high-quality target localization and adaptive radiotherapy.

  4. Gabor frames for quasicrystals and K-theory

    NASA Astrophysics Data System (ADS)

    Kreisel, Michael

    We study the connection between Gabor frames for quasicrystals, the topology of the hull of a quasicrystal, and the K-theory of an associated twisted groupoid algebra. In particular, we construct a finitely generated projective module over this algebra, and multiwindow Gabor frames can be used to construct an idempotent representing the module in K-theory. For lattice subsets in dimension two, this allows us to prove a twisted version of Bellissard's gap labeling theorem. By viewing Gabor frames in this operator algebraic framework, we are also able to show that for certain quasicrystals it is not possible to construct a tight multiwindow Gabor frame.

  5. Deep learning for automatic localization, identification, and segmentation of vertebral bodies in volumetric MR images

    NASA Astrophysics Data System (ADS)

    Suzani, Amin; Rasoulian, Abtin; Seitel, Alexander; Fels, Sidney; Rohling, Robert N.; Abolmaesumi, Purang

    2015-03-01

    This paper proposes an automatic method for vertebra localization, labeling, and segmentation in multi-slice Magnetic Resonance (MR) images. Prior work in this area on MR images mostly requires user interaction while our method is fully automatic. Cubic intensity-based features are extracted from image voxels. A deep learning approach is used for simultaneous localization and identification of vertebrae. The localized points are refined by local thresholding in the region of the detected vertebral column. Thereafter, a statistical multi-vertebrae model is initialized on the localized vertebrae. An iterative Expectation Maximization technique is used to register the vertebral body of the model to the image edges and obtain a segmentation of the lumbar vertebral bodies. The method is evaluated by applying to nine volumetric MR images of the spine. The results demonstrate 100% vertebra identification and a mean surface error of below 2.8 mm for 3D segmentation. Computation time is less than three minutes per high-resolution volumetric image.

  6. Texture classification of normal tissues in computed tomography using Gabor filters

    NASA Astrophysics Data System (ADS)

    Dettori, Lucia; Bashir, Alia; Hasemann, Julie

    2007-03-01

    The research presented in this article is aimed at developing an automated imaging system for classification of normal tissues in medical images obtained from Computed Tomography (CT) scans. Texture features based on a bank of Gabor filters are used to classify the following tissues of interests: liver, spleen, kidney, aorta, trabecular bone, lung, muscle, IP fat, and SQ fat. The approach consists of three steps: convolution of the regions of interest with a bank of 32 Gabor filters (4 frequencies and 8 orientations), extraction of two Gabor texture features per filter (mean and standard deviation), and creation of a Classification and Regression Tree-based classifier that automatically identifies the various tissues. The data set used consists of approximately 1000 DIACOM images from normal chest and abdominal CT scans of five patients. The regions of interest were labeled by expert radiologists. Optimal trees were generated using two techniques: 10-fold cross-validation and splitting of the data set into a training and a testing set. In both cases, perfect classification rules were obtained provided enough images were available for training (~65%). All performance measures (sensitivity, specificity, precision, and accuracy) for all regions of interest were at 100%. This significantly improves previous results that used Wavelet, Ridgelet, and Curvelet texture features, yielding accuracy values in the 85%-98% range The Gabor filters' ability to isolate features at different frequencies and orientations allows for a multi-resolution analysis of texture essential when dealing with, at times, very subtle differences in the texture of tissues in CT scans.

  7. Reconfigurable Gabor Filter For Fingerprint Recognition Using FPGA Verilog

    NASA Astrophysics Data System (ADS)

    Rosshidi, H. T.; Hadi, A. R.

    2009-06-01

    This paper present the implementations of Gabor filter for fingerprint recognition using Verilog HDL. This work demonstrates the application of Gabor Filter technique to enhance the fingerprint image. The incoming signal in form of image pixel will be filter out or convolute by the Gabor filter to define the ridge and valley regions of fingerprint. This is done with the application of a real time convolve based on Field Programmable Gate Array (FPGA) to perform the convolution operation. The main characteristic of the proposed approach are the usage of memory to store the incoming image pixel and the coefficient of the Gabor filter before the convolution matrix take place. The result was the signal convoluted with the Gabor coefficient.

  8. A Novel Modulation Classification Approach Using Gabor Filter Network

    PubMed Central

    Ghauri, Sajjad Ahmed; Qureshi, Ijaz Mansoor; Cheema, Tanveer Ahmed; Malik, Aqdas Naveed

    2014-01-01

    A Gabor filter network based approach is used for feature extraction and classification of digital modulated signals by adaptively tuning the parameters of Gabor filter network. Modulation classification of digitally modulated signals is done under the influence of additive white Gaussian noise (AWGN). The modulations considered for the classification purpose are PSK 2 to 64, FSK 2 to 64, and QAM 4 to 64. The Gabor filter network uses the network structure of two layers; the first layer which is input layer constitutes the adaptive feature extraction part and the second layer constitutes the signal classification part. The Gabor atom parameters are tuned using Delta rule and updating of weights of Gabor filter using least mean square (LMS) algorithm. The simulation results show that proposed novel modulation classification algorithm has high classification accuracy at low signal to noise ratio (SNR) on AWGN channel. PMID:25126603

  9. Real-time automatic small infrared target detection using local spectral filtering in the frequency

    NASA Astrophysics Data System (ADS)

    Chen, Hao; Zhang, Hong; Li, Jiafeng; Yuan, Ding; Sun, Mingui

    2014-11-01

    Accurate and fast detection of small infrared target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. Based on human visual attention mechanism, an automatic detection algorithm for small infrared target is presented. In this paper, instead of searching for infrared targets, we model regular patches that do not attract much attention by our visual system. This is inspired by the property that the regular patches in spatial domain turn out to correspond to the spikes in the amplitude spectrum. Unlike recent approaches using global spectral filtering, we define the concept of local maxima suppression using local spectral filtering to smooth the spikes in the amplitude spectrum, thereby producing the pop-out of the infrared targets. In the proposed method, we firstly compute the amplitude spectrum of an input infrared image. Second, we find the local maxima of the amplitude spectrum using cubic facet model. Third, we suppress the local maxima using the convolution of the local spectrum with a low-pass Gaussian kernel of an appropriate scale. At last, the detection result in spatial domain is obtained by reconstructing the 2D signal using the original phase and the log amplitude spectrum by suppressing local maxima. The experiments are performed for some real-life IR images, and the results prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, it has high detection efficiency and can be further used for real-time detection and tracking.

  10. Automatic localization of landmark sets in head CT images with regression forests for image registration initialization

    NASA Astrophysics Data System (ADS)

    Zhang, Dongqing; Liu, Yuan; Noble, Jack H.; Dawant, Benoit M.

    2016-03-01

    Cochlear Implants (CIs) are electrode arrays that are surgically inserted into the cochlea. Individual contacts stimulate frequency-mapped nerve endings thus replacing the natural electro-mechanical transduction mechanism. CIs are programmed post-operatively by audiologists but this is currently done using behavioral tests without imaging information that permits relating electrode position to inner ear anatomy. We have recently developed a series of image processing steps that permit the segmentation of the inner ear anatomy and the localization of individual contacts. We have proposed a new programming strategy that uses this information and we have shown in a study with 68 participants that 78% of long term recipients preferred the programming parameters determined with this new strategy. A limiting factor to the large scale evaluation and deployment of our technique is the amount of user interaction still required in some of the steps used in our sequence of image processing algorithms. One such step is the rough registration of an atlas to target volumes prior to the use of automated intensity-based algorithms when the target volumes have very different fields of view and orientations. In this paper we propose a solution to this problem. It relies on a random forest-based approach to automatically localize a series of landmarks. Our results obtained from 83 images with 132 registration tasks show that automatic initialization of an intensity-based algorithm proves to be a reliable technique to replace the manual step.

  11. Automatic programming via iterated local search for dynamic job shop scheduling.

    PubMed

    Nguyen, Su; Zhang, Mengjie; Johnston, Mark; Tan, Kay Chen

    2015-01-01

    Dispatching rules have been commonly used in practice for making sequencing and scheduling decisions. Due to specific characteristics of each manufacturing system, there is no universal dispatching rule that can dominate in all situations. Therefore, it is important to design specialized dispatching rules to enhance the scheduling performance for each manufacturing environment. Evolutionary computation approaches such as tree-based genetic programming (TGP) and gene expression programming (GEP) have been proposed to facilitate the design task through automatic design of dispatching rules. However, these methods are still limited by their high computational cost and low exploitation ability. To overcome this problem, we develop a new approach to automatic programming via iterated local search (APRILS) for dynamic job shop scheduling. The key idea of APRILS is to perform multiple local searches started with programs modified from the best obtained programs so far. The experiments show that APRILS outperforms TGP and GEP in most simulation scenarios in terms of effectiveness and efficiency. The analysis also shows that programs generated by APRILS are more compact than those obtained by genetic programming. An investigation of the behavior of APRILS suggests that the good performance of APRILS comes from the balance between exploration and exploitation in its search mechanism. PMID:24802623

  12. AutoGate: fast and automatic Doppler gate localization in B-mode echocardiogram.

    PubMed

    Park, JinHyeong; Zhou, S Kevin; Simopoulos, Costas; Comaniciu, Dorin

    2008-01-01

    In this paper, we propose an algorithm for fast and automatic Doppler gate localization in spectral Doppler echocardiography using the B-mode image information. The algorithm has two components: 1) cardiac standard view classification and 2) gate location inference. For cardiac view classification, we incorporate the probabilistic boosting network (PBN) principle to local-structure-dependent object classification, which speeds up the processing time as it breaks down the computational dependency on the number of classes. The gate location is computed using a data-driven shape inference approach. Clinical evaluation was performed by implementing the algorithm on an ultrasound system. Experiment results show that the performance of the proposed algorithm is comparable to the Doppler gate placement by an expert user. To the best of our knowledge, this is the first algorithm that provides a real time solution to the automated Doppler gate placement in the clinical environment. PMID:18982610

  13. SIMULATING LOCAL DENSE AREAS USING PMMA TO ASSESS AUTOMATIC EXPOSURE CONTROL IN DIGITAL MAMMOGRAPHY.

    PubMed

    Bouwman, R W; Binst, J; Dance, D R; Young, K C; Broeders, M J M; den Heeten, G J; Veldkamp, W J H; Bosmans, H; van Engen, R E

    2016-06-01

    Current digital mammography (DM) X-ray systems are equipped with advanced automatic exposure control (AEC) systems, which determine the exposure factors depending on breast composition. In the supplement of the European guidelines for quality assurance in breast cancer screening and diagnosis, a phantom-based test is included to evaluate the AEC response to local dense areas in terms of signal-to-noise ratio (SNR). This study evaluates the proposed test in terms of SNR and dose for four DM systems. The glandular fraction represented by the local dense area was assessed by analytic calculations. It was found that the proposed test simulates adipose to fully glandular breast compositions in attenuation. The doses associated with the phantoms were found to match well with the patient dose distribution. In conclusion, after some small adaptations, the test is valuable for the assessment of the AEC performance in terms of both SNR and dose. PMID:26977073

  14. Improved Gabor Deconvolution and Its Extended Applications

    NASA Astrophysics Data System (ADS)

    Sun, Xuekai; Sun, Sam Zandong

    2016-02-01

    In log time-frequency spectra, the nonstationary convolution model is a linear equation and thus we improved the Gabor deconvolution by employing a log hyperbolic smoothing scheme which can be implemented as an iteration process. Numerical tests and practical applications demonstrate that improved Gabor deconvolution can further broaden frequency bandwidth with less computational expenses than the ordinary method. Moreover, we attempt to enlarge this method's application value by addressing nonstationary and evaluating Q values. In fact, energy relationship of each hyperbolic bin (i.e., attenuation curve) can be taken as a quantitative indicator in balancing nonstationarity and conditioning seismic traces to the assumption of unchanging wavelet, which resultantly reveals more useful information for constrained reflectivity inversion. Meanwhile, a statistical method on Q-value estimation is also proposed by utilizing this linear model's gradient. In practice, not only estimations well agree with geologic settings, but also applications on Q-compensation migration are favorable in characterizing deep geologic structures, such as the pinch-out boundary and water channel.

  15. Spectral fusing Gabor domain optical coherence microscopy.

    PubMed

    Meemon, Panomsak; Widjaja, Joewono; Rolland, Jannick P

    2016-02-01

    Gabor domain optical coherence microscopy (GD-OCM) is one of many variations of optical coherence tomography (OCT) techniques that aims for invariant high resolution across a 3D field of view by utilizing the ability to dynamically refocus the imaging optics in the sample arm. GD-OCM acquires multiple cross-sectional images at different focus positions of the objective lens, and then fuses them to obtain an invariant high-resolution 3D image of the sample, which comes with the intrinsic drawback of a longer processing time as compared to conventional Fourier domain OCT. Here, we report on an alternative Gabor fusing algorithm, the spectral-fusion technique, which directly processes each acquired spectrum and combines them prior to the Fourier transformation to obtain a depth profile. The implementation of the spectral-fusion algorithm is presented and its performance is compared to that of the prior GD-OCM spatial-fusion approach. The spectral-fusion approach shows twice the speed of the spatial-fusion approach for a spectrum size of less than 2000 point sampling, which is a commonly used spectrum size in OCT imaging, including GD-OCM. PMID:26907410

  16. Peak detection in mass spectrometry by Gabor filters and envelope analysis.

    PubMed

    Nguyen, Nha; Huang, Heng; Oraintara, Soontorn; Vo, An

    2009-06-01

    Mass Spectrometry (MS) is increasingly being used to discover diseases-related proteomic patterns. The peak detection step is one of the most important steps in the typical analysis of MS data. Recently, many new algorithms have been proposed to increase true position rate with low false discovery rate in peak detection. Most of them follow two approaches: one is the denoising approach and the other is the decomposing approach. In the previous studies, the decomposition of MS data method shows more potential than the first one. In this paper, we propose two novel methods, named GaborLocal and GaborEnvelop, both of which can detect more true peaks with a lower false discovery rate than previous methods. We employ the method of Gaussian local maxima to detect peaks, because it is robust to noise in signals. A new approach, peak rank, is defined for the first time to identify peaks instead of using the signal-to-noise ratio. Meanwhile, the Gabor filter is used to amplify important information and compress noise in the raw MS signal. Moreover, we also propose the envelope analysis to improve the quantification of peaks and remove more false peaks. The proposed methods have been performed on the real SELDI-TOF spectrum with known polypeptide positions. The experimental results demonstrate that our methods outperform other commonly used methods in the Receiver Operating Characteristic (ROC) curve. PMID:19507289

  17. Automatic localization of IASLC-defined mediastinal lymph node stations on CT images using fuzzy models

    NASA Astrophysics Data System (ADS)

    Matsumoto, Monica M. S.; Beig, Niha G.; Udupa, Jayaram K.; Archer, Steven; Torigian, Drew A.

    2014-03-01

    Lung cancer is associated with the highest cancer mortality rates among men and women in the United States. The accurate and precise identification of the lymph node stations on computed tomography (CT) images is important for staging disease and potentially for prognosticating outcome in patients with lung cancer, as well as for pretreatment planning and response assessment purposes. To facilitate a standard means of referring to lymph nodes, the International Association for the Study of Lung Cancer (IASLC) has recently proposed a definition of the different lymph node stations and zones in the thorax. However, nodal station identification is typically performed manually by visual assessment in clinical radiology. This approach leaves room for error due to the subjective and potentially ambiguous nature of visual interpretation, and is labor intensive. We present a method of automatically recognizing the mediastinal IASLC-defined lymph node stations by modifying a hierarchical fuzzy modeling approach previously developed for body-wide automatic anatomy recognition (AAR) in medical imagery. Our AAR-lymph node (AAR-LN) system follows the AAR methodology and consists of two steps. In the first step, the various lymph node stations are manually delineated on a set of CT images following the IASLC definitions. These delineations are then used to build a fuzzy hierarchical model of the nodal stations which are considered as 3D objects. In the second step, the stations are automatically located on any given CT image of the thorax by using the hierarchical fuzzy model and object recognition algorithms. Based on 23 data sets used for model building, 22 independent data sets for testing, and 10 lymph node stations, a mean localization accuracy of within 1-6 voxels has been achieved by the AAR-LN system.

  18. A fast seed detection using local geometrical feature for automatic tracking of coronary arteries in CTA.

    PubMed

    Han, Dongjin; Doan, Nam-Thai; Shim, Hackjoon; Jeon, Byunghwan; Lee, Hyunna; Hong, Youngtaek; Chang, Hyuk-Jae

    2014-11-01

    We propose a fast seed detection for automatic tracking of coronary arteries in coronary computed tomographic angiography (CCTA). To detect vessel regions, Hessian-based filtering is combined with a new local geometric feature that is based on the similarity of the consecutive cross-sections perpendicular to the vessel direction. It is in turn founded on the prior knowledge that a vessel segment is shaped like a cylinder in axial slices. To improve computational efficiency, an axial slice, which contains part of three main coronary arteries, is selected and regions of interest (ROIs) are extracted in the slice. Only for the voxels belonging to the ROIs, the proposed geometric feature is calculated. With the seed points, which are the centroids of the detected vessel regions, and their vessel directions, vessel tracking method can be used for artery extraction. Here a particle filtering-based tracking algorithm is tested. Using 19 clinical CCTA datasets, it is demonstrated that the proposed method detects seed points and can be used for full automatic coronary artery extraction. ROC (receiver operating characteristic) curve analysis shows the advantages of the proposed method. PMID:25106730

  19. Semi-automatic stereotactic coordinate identification algorithm for routine localization of Deep Brain Stimulation electrodes.

    PubMed

    Hebb, Adam O; Miller, Kai J

    2010-03-15

    Deep Brain Stimulation (DBS) is a routine therapy for movement disorders, and has several emerging indications. We present a novel protocol to define the stereotactic coordinates of metallic DBS implants that may be routinely employed for validating therapeutic anatomical targets. Patients were referred for troubleshooting or new DBS implantation. A volumetric MRI of the brain obtained prior to or during this protocol was formatted to the Anterior Commissure-Posterior Commissure (AC-PC) coordinate system. Patients underwent a CT scan of the brain in an extended Hounsfield unit (EHU) mode. A semi-automatic detection algorithm based on a Normalized Mutual Information (NMI) co-registration method was implemented to measure the AC-PC coordinates of each DBS contact. This algorithm was validated using manual DBS contact identification. Fifty MRI-CT image pairs were available in 39 patients with a total of 336 DBS electrodes. The median and mean Euclidean distance errors for automatic identification of electrode locations were 0.20mm and 0.22 mm, respectively. This method is an accurate method of localization of active DBS contacts within the sub-cortical region. As the investigational indications of DBS expand, this method may be used for verification of final implant coordinates, critical for understanding clinical benefit and comparing efficacy between subjects. PMID:20036691

  20. Development of automatic image analysis algorithms for protein localization studies in budding yeast

    NASA Astrophysics Data System (ADS)

    Logg, Katarina; Kvarnström, Mats; Diez, Alfredo; Bodvard, Kristofer; Käll, Mikael

    2007-02-01

    Microscopy of fluorescently labeled proteins has become a standard technique for live cell imaging. However, it is still a challenge to systematically extract quantitative data from large sets of images in an unbiased fashion, which is particularly important in high-throughput or time-lapse studies. Here we describe the development of a software package aimed at automatic quantification of abundance and spatio-temporal dynamics of fluorescently tagged proteins in vivo in the budding yeast Saccharomyces cerevisiae, one of the most important model organisms in proteomics. The image analysis methodology is based on first identifying cell contours from bright field images, and then use this information to measure and statistically analyse protein abundance in specific cellular domains from the corresponding fluorescence images. The applicability of the procedure is exemplified for two nuclear localized GFP-tagged proteins, Mcm4p and Nrm1p.

  1. Unsupervised novelty detection using Gabor filters for defect segmentation in textures.

    PubMed

    Ralló, Miquel; Millán, María S; Escofet, Jaume

    2009-09-01

    Gabor wavelets are applied to develop an unsupervised novelty method for defect detection and segmentation that is fully automatic and free of any adjustable parameter. The algorithm combines the Gabor analysis of the sample image with a statistical analysis of the wavelet coefficients corresponding to each detail. The statistical distribution of the coefficients corresponding to the defect-free background texture is calculated from the coefficient's distribution of the sample under inspection. Once the background texture features are estimated, a threshold is automatically fixed and applied to all the details, whose information is merged into a single binary output image in which the defect appears segmented from the background. The method is applicable to random, nonperiodic, and periodic textures. Since all the information to inspect a sample is obtained from the sample itself, the method is proof against heterogeneities between different samples of the material, in-plane positioning errors, scale variations, and lack of homogeneous illumination. Experimental results are presented. Some results are compared with other unsupervised methods designed for defect segmentation in periodic textures. PMID:19721681

  2. Extracting tissue deformation using Gabor filter banks

    NASA Astrophysics Data System (ADS)

    Montillo, Albert; Metaxas, Dimitris; Axel, Leon

    2004-04-01

    This paper presents a new approach for accurate extraction of tissue deformation imaged with tagged MR. Our method, based on banks of Gabor filters, adjusts (1) the aspect and (2) orientation of the filter"s envelope and adjusts (3) the radial frequency and (4) angle of the filter"s sinusoidal grating to extract information about the deformation of tissue. The method accurately extracts tag line spacing, orientation, displacement and effective contrast. Existing, non-adaptive methods often fail to recover useful displacement information in the proximity of tissue boundaries while our method works in the proximity of the boundaries. We also present an interpolation method to recover all tag information at a finer resolution than the filter bank parameters. Results are shown on simulated images of translating and contracting tissue.

  3. New approaches for automatic threedimensional source localization of acoustic emissions--Applications to concrete specimens.

    PubMed

    Kurz, Jochen H

    2015-12-01

    The task of locating a source in space by measuring travel time differences of elastic or electromagnetic waves from the source to several sensors is evident in varying fields. The new concepts of automatic acoustic emission localization presented in this article are based on developments from geodesy and seismology. A detailed description of source location determination in space is given with the focus on acoustic emission data from concrete specimens. Direct and iterative solvers are compared. A concept based on direct solvers from geodesy extended by a statistical approach is described which allows a stable source location determination even for partly erroneous onset times. The developed approach is validated with acoustic emission data from a large specimen leading to travel paths up to 1m and therefore to noisy data with errors in the determined onsets. The adaption of the algorithms from geodesy to the localization procedure of sources of elastic waves offers new possibilities concerning stability, automation and performance of localization results. Fracture processes can be assessed more accurately. PMID:26233938

  4. Using locality-constrained linear coding in automatic target detection of HRS images

    NASA Astrophysics Data System (ADS)

    Rezaee, M.; Mirikharaji, Z.; Zhang, Y.

    2016-04-01

    Automatic target detection with complicated shapes in high spatial resolution images is an ongoing challenge in remote sensing image processing. This is because most methods use spectral or texture information, which are not sufficient for detecting complex shapes. In this paper, a new detection framework, based on Spatial Pyramid Matching (SPM) and Locality- constraint Linear Coding (LLC), is proposed to solve this problem, and exemplified using airplane shapes. The process starts with partitioning the image into sub-regions and generating a unique histogram for local features of each sub-region. Then, linear Support Vector Machines (SVMs) are used to detect objects based on a pyramid-matching kernel, which analyses the descriptors inside patches in different resolution. In order to generate the histogram, first a point feature detector (e.g. SIFT) is applied on the patches, and then a quantization process is used to select local features. In this step, the k-mean method is used in conjunction with the locality-constrained linear coding method. The LLC forces the coefficient matrix in the quantization process to be local and sparse as well. As a result, the speed of the method improves around 24 times in comparison to using sparse coding for quantization. Quantitative analysis also shows improvement in comparison to just using k-mean, but the accuracy in comparison to using sparse coding is similar. Rotation and shift of the desired object has no effect on the obtained results. The speed and accuracy of this algorithm for high spatial resolution images make it capable for use in real-world applications.

  5. Gabor-type matric algebra and fast computations of dual and tight Gaborwavelets

    NASA Astrophysics Data System (ADS)

    Qiu, Sigang

    1997-01-01

    We investigate a class of Gabor-type matrices and develop simplified Gabor-type matrix operations. The usual matrix- multiplication in the class is proved to be easily performed with O(ab log b) Gabor frame operators and the square roots of the Gabor frame operators as well as the dual Gabor and tight Gabor wavelets. A necessary and sufficient condition is derived for a Gabor triple (g, a, b) to generate a Gabor frame. It is very easy to predetermine the quality of a given (g, a, b) and the stability of Gabor synthesis.

  6. High-resolution seismic processing by Gabor deconvolution

    NASA Astrophysics Data System (ADS)

    Chen, Zengbao; Wang, Yanghua; Chen, Xiaohong; Li, Jingye

    2013-12-01

    Since viscoelastic attenuation effects are ubiquitous in subsurface media, the seismic source wavelet rapidly evolves as the wave travels through the subsurface. Eliminating the source wavelet and compensating the attenuation effect together may improve seismic resolution. Gabor deconvolution can achieve these two processes simultaneously, by removing the propagating wavelet which is the combination of the source wavelet and the attenuation effect. The Gabor deconvolution operator is determined based on the Gabor spectrum of a nonstationary seismic trace. By assuming white reflectivity, the Gabor amplitude spectrum can be smoothed to produce the required amplitude spectrum of the propagating wavelet. In this paper, smoothing is set as a least-squares inverse problem, and is referred to as regularized smoothing. By assuming that the source wavelet and the attenuation process are both minimum phased, the phase spectrum of the propagating wavelet can be defined by the Hilbert transform of the natural logarithm of the smoothed amplitude spectrum. The inverse of the complex spectrum of the propagating wavelet is the Gabor deconvolution operator. Applying it to the original time-frequency spectrum of the nonstationary trace produces an estimated time-frequency spectrum of reflectivity series. The final time-domain high-resolution trace, obtained by an inverse Gabor transform, is close to a band-pass filtered version of the reflectivity series.

  7. Automatic Segmentation of Myocardium from Black-Blood MR Images Using Entropy and Local Neighborhood Information

    PubMed Central

    Zheng, Qian; Lu, Zhentai; Zhang, Minghui; Xu, Lin; Ma, Huan; Song, Shengli; Feng, Qianjin; Feng, Yanqiu; Chen, Wufan; He, Taigang

    2015-01-01

    By using entropy and local neighborhood information, we present in this study a robust adaptive Gaussian regularizing Chan–Vese (CV) model to segment the myocardium from magnetic resonance images with intensity inhomogeneity. By utilizing the circular Hough transformation (CHT) our model is able to detect epicardial and endocardial contours of the left ventricle (LV) as circles automatically, and the circles are used as the initialization. In the cost functional of our model, the interior and exterior energies are weighted by the entropy to improve the robustness of the evolving curve. Local neighborhood information is used to evolve the level set function to reduce the impact of the heterogeneity inside the regions and to improve the segmentation accuracy. An adaptive window is utilized to reduce the sensitivity to initialization. The Gaussian kernel is used to regularize the level set function, which can not only ensure the smoothness and stability of the level set function, but also eliminate the traditional Euclidean length term and re-initialization. Extensive validation of the proposed method on patient data demonstrates its superior performance over other state-of-the-art methods. PMID:25811976

  8. Electroacoustical imaging technique for encoding incoherent radiance fields as Gabor elementary signals

    NASA Technical Reports Server (NTRS)

    Fales, C. L.; Huck, F. O.

    1985-01-01

    A technique is presented for directly encoding incoherent radiance fields as Gabor elementary signals. This technique uses an electro-acoustic sensor to modulate the electronic charges induced by the incident radiance field with the electric fields generated by Gaussian modulated sinusoidal acoustic waves. The resultant signal carries the amplitude and phase information required for localizing spatial frequencies of the radiance field. These localized spatial frequency representations provide a link between the either geometric or Fourier transform representations currently used in computer vision and pattern recognition.

  9. Automatic registration of optical imagery with 3d lidar data using local combined mutual information

    NASA Astrophysics Data System (ADS)

    Parmehr, E. G.; Fraser, C. S.; Zhang, C.; Leach, J.

    2013-10-01

    Automatic registration of multi-sensor data is a basic step in data fusion for photogrammetric and remote sensing applications. The effectiveness of intensity-based methods such as Mutual Information (MI) for automated registration of multi-sensor image has been previously reported for medical and remote sensing applications. In this paper, a new multivariable MI approach that exploits complementary information of inherently registered LiDAR DSM and intensity data to improve the robustness of registering optical imagery and LiDAR point cloud, is presented. LiDAR DSM and intensity information has been utilised in measuring the similarity of LiDAR and optical imagery via the Combined MI. An effective histogramming technique is adopted to facilitate estimation of a 3D probability density function (pdf). In addition, a local similarity measure is introduced to decrease the complexity of optimisation at higher dimensions and computation cost. Therefore, the reliability of registration is improved due to the use of redundant observations of similarity. The performance of the proposed method for registration of satellite and aerial images with LiDAR data in urban and rural areas is experimentally evaluated and the results obtained are discussed.

  10. An automatic locally-adaptive method to estimate heavily-tailed breakthrough curves from particle distributions

    NASA Astrophysics Data System (ADS)

    Pedretti, Daniele; Fernàndez-Garcia, Daniel

    2013-09-01

    Particle tracking methods to simulate solute transport deal with the issue of having to reconstruct smooth concentrations from a limited number of particles. This is an error-prone process that typically leads to large fluctuations in the determined late-time behavior of breakthrough curves (BTCs). Kernel density estimators (KDE) can be used to automatically reconstruct smooth BTCs from a small number of particles. The kernel approach incorporates the uncertainty associated with subsampling a large population by equipping each particle with a probability density function. Two broad classes of KDE methods can be distinguished depending on the parametrization of this function: global and adaptive methods. This paper shows that each method is likely to estimate a specific portion of the BTCs. Although global methods offer a valid approach to estimate early-time behavior and peak of BTCs, they exhibit important fluctuations at the tails where fewer particles exist. In contrast, locally adaptive methods improve tail estimation while oversmoothing both early-time and peak concentrations. Therefore a new method is proposed combining the strength of both KDE approaches. The proposed approach is universal and only needs one parameter (α) which slightly depends on the shape of the BTCs. Results show that, for the tested cases, heavily-tailed BTCs are properly reconstructed with α ≈ 0.5 .

  11. Automatic alignment of multi-temporal images of planetary nebulae using local optimization

    NASA Astrophysics Data System (ADS)

    Kazemzadeh, Farnoud; Hajian, Arsen R.

    2010-08-01

    Automatic alignment of time-separated astronomical images have historically proven to be difficult. The main reason for this difficulty is the amount of sporadic and unpredictable noise associated with astronomical images. A few examples of these effects are: image distortion due to optics, cosmic ray hits, transient background sources (super novae) and various artifact sources associated with the CCD imager itself. In this paper a new automated image registration method is introduced for aligning two time-separated images while minimizing the inherent errors and unpredictabilities. Using local optimization, the two images are aligned when the root mean square of the difference between the two images is minimized. The dataset consists of images of galactic planetary nebulae acquired by the Hubble Space Telescope. The aligned centroids inferred by the suggested method agree with the results from previously aligned images by inspection with high confidence. It is also demonstrated that this method is robust, sufficient, does not require extensive user input and it is highly sensitive to minor adjustments.

  12. Editorial: Special issue dedicated to Gabor Somorjai's 80th birthday

    NASA Astrophysics Data System (ADS)

    2016-06-01

    This special issue of Surface Science has been prepared to honor Professor Gabor A. Somorjai on the occasion of his 80th birthday. Professor Somorjai was born on May 4, 1935 in Budapest, Hungary. In 1953 he enrolled as a chemical engineering student at the Technical University of Budapest. Gabor was an active participant in the Hungarian Revolution of 1956. When the Soviet military crushed the revolution, he had to leave the country by walking across the border with his sister and his future wife. After immigrating to the USA in 1957, he applied to begin graduate studies and was accepted at the University of California, Berkeley. Gabor received a PhD in Chemistry in 1960, only three years later. Following a short sojourn at IBM, he returned to Berkeley in 1964 to take up a faculty position in the Department of Chemistry and the Lawrence Berkeley National Laboratory, which he still holds today. For the interested reader, more can be learned about Gabor's fascinating life in his autobiography, "An American Scientist: The Autobiography of Gabor A. Somorjai.

  13. Robust automatic photometry of local galaxies from SDSS. Dissecting the color magnitude relation with color profiles

    NASA Astrophysics Data System (ADS)

    Consolandi, Guido; Gavazzi, Giuseppe; Fumagalli, Michele; Dotti, Massimo; Fossati, Matteo

    2016-06-01

    We present an automatic procedure to perform reliable photometry of galaxies on SDSS images. We selected a sample of 5853 galaxies in the Coma and Virgo superclusters. For each galaxy, we derive Petrosian g and i magnitudes, surface brightness and color profiles. Unlike the SDSS pipeline, our procedure is not affected by the well known shredding problem and efficiently extracts Petrosian magnitudes for all galaxies. Hence we derived magnitudes even from the population of galaxies missed by the SDSS which represents ~25% of all local supercluster galaxies and ~95% of galaxies with g < 11 mag. After correcting the g and i magnitudes for Galactic and internal extinction, the blue and red sequences in the color magnitude diagram are well separated, with similar slopes. In addition, we study (i) the color-magnitude diagrams in different galaxy regions, the inner (r ≤ 1 kpc), intermediate (0.2RPet ≤ r ≤ 0.3RPet) and outer, disk-dominated (r ≥ 0.35RPet)) zone; and (ii), we compute template color profiles, discussing the dependences of the templates on the galaxy masses and on their morphological type. The two analyses consistently lead to a picture where elliptical galaxies show no color gradients, irrespective of their masses. Spirals, instead, display a steeper gradient in their color profiles with increasing mass, which is consistent with the growing relevance of a bulge and/or a bar component above 1010 M⊙. Full Table A.1 is only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/591/A38

  14. Pornographic image detection with Gabor filters

    NASA Astrophysics Data System (ADS)

    Durrell, Kevan; Murray, Daniel J. C.

    2002-04-01

    As Internet-enabled computers become ubiquitous in homes, schools, and other publicly accessible locations, there are more people 'surfing the net' who would prefer not to be exposed to offensive material. There is a lot of material freely available on the Internet that we, as a responsible and caring society, would like to keep our children from viewing. Pornographic image content is one category of material over which we would like some control. We have been conducting experiments to determine the effectiveness of using characteristic feature vectors and neural networks to identify semantic image content. This paper will describe our approach to identifying pornographic images using Gabor filters, Principal Component Analysis (PCA), Correllograms, and Neural Networks. In brief, we used a set of 5,000 typical images available from the Internet, 20% of which were judged to be pornographic, to train a neural network. We then apply the trained neural network to feature vectors from images that had not been used in training. We measure our performance as Recall, how many of the verification images labeled pornographic were correctly identified, and Precision, how many images deemed pornographic by the neural network are in fact pornographic. The set of images that were used in the experiment described in this paper for its training and validation sets are freely available on the Internet. Freely available is an important qualifier, since high-resolution, studio-quality pornographic images are often protected by portals that charge members a fee to gain access to their material. Although this is not a hard and fast rule, many of the pornographic images that are available easily and without charge on the Internet are of low image quality. Some of these images are collages or contain textual elements or have had their resolution intentionally lowered to reduce their file size. These are the offensive images that a user, without a credit card, might inadvertently come

  15. Analysis of frequency shifting in seismic signals using Gabor-Wigner transform

    NASA Astrophysics Data System (ADS)

    Kumar, Roshan; Sumathi, P.; Kumar, Ashok

    2015-12-01

    A hybrid time-frequency method known as Gabor-Wigner transform (GWT) is introduced in this paper for examining the time-frequency patterns of earthquake damaged buildings. GWT is developed by combining the Gabor transform (GT) and Wigner-Ville distribution (WVD). GT and WVD have been used separately on synthetic and recorded earthquake data to identify frequency shifting due to earthquake damages, but GT is prone to windowing effect and WVD involves ambiguity function. Hence to obtain better clarity and to remove the cross terms (frequency interference), GT and WVD are judiciously combined and the resultant GWT used to identify frequency shifting. Synthetic seismic response of an instrumented building and real-time earthquake data recorded on the building were investigated using GWT. It is found that GWT offers good accuracy for even slow variations in frequency, good time-frequency resolution, and localized response. Presented results confirm the efficacy of GWT when compared with GT and WVD used separately. Simulation results were quantified by the Renyi entropy measures and GWT shown to be an adequate technique in identifying localized response for structural damage detection.

  16. Matrix algebra approach to Gabor-type image representation

    NASA Astrophysics Data System (ADS)

    Zibulski, Meir; Zeevi, Yehoshua Y.

    1993-10-01

    Properties of basis functions which constitute a finite scheme of discrete Gabor representation are investigated. The approach is based on the concept of frames and utilizes the Piecewise Finite Zak Transform (PFZT). The frame operator associated with the Gabor-type frame is examined by representing it as a matrix-values function in the PFZT domain. The frame property of the Gabor representation functions are examined in relation to the properties of the matrix-valued function. The frame bounds are calculated by means of the eignevalues of the matrix-valued function, and the dual frame, which is used in calculation of the expansion coefficients, is expressed by means of the inverse matrix. DFT-based algorithms for computation of the expansion coefficients, and for the reconstruction of signals from these coefficients are generalized for the case of oversampling of the Gabor space. It is illustrated by an example that a better reconstruction is obtained in from the same number of coefficients in the case of oversampling.

  17. Finger-Vein Image Enhancement Using a Fuzzy-Based Fusion Method with Gabor and Retinex Filtering

    PubMed Central

    Shin, Kwang Yong; Park, Young Ho; Nguyen, Dat Tien; Park, Kang Ryoung

    2014-01-01

    Because of the advantages of finger-vein recognition systems such as live detection and usage as bio-cryptography systems, they can be used to authenticate individual people. However, images of finger-vein patterns are typically unclear because of light scattering by the skin, optical blurring, and motion blurring, which can degrade the performance of finger-vein recognition systems. In response to these issues, a new enhancement method for finger-vein images is proposed. Our method is novel compared with previous approaches in four respects. First, the local and global features of the vein lines of an input image are amplified using Gabor filters in four directions and Retinex filtering, respectively. Second, the means and standard deviations in the local windows of the images produced after Gabor and Retinex filtering are used as inputs for the fuzzy rule and fuzzy membership function, respectively. Third, the optimal weights required to combine the two Gabor and Retinex filtered images are determined using a defuzzification method. Fourth, the use of a fuzzy-based method means that image enhancement does not require additional training data to determine the optimal weights. Experimental results using two finger-vein databases showed that the proposed method enhanced the accuracy of finger-vein recognition compared with previous methods. PMID:24549251

  18. 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.

  19. High-resolution BOLD fMRI measurements of local orientation-dependent contextual modulation show a mismatch between predicted V1 output and local BOLD response

    PubMed Central

    Schumacher, Jennifer F.; Olman, Cheryl A.

    2010-01-01

    The blood oxygenation level-dependent (BOLD) functional MRI response to suppressive neural activity has not been tested on a fine spatial scale. Using Gabor patches placed in the near periphery, we precisely localized individual regions of interest in primary visual cortex and measured the response at a range of contrasts in two different contexts: with parallel and with orthogonal flanking Gabor patches. Psychophysical measurements confirmed strong suppression of the target Gabor response when flanked by parallel Gabors. However, the BOLD response to the target with parallel flankers decreased as the target contrast increased, which contradicts psychophysical estimates of local neural activity. PMID:20382175

  20. Automatic localization of target vertebrae in spine surgery using fast CT-to-fluoroscopy (3D-2D) image registration

    NASA Astrophysics Data System (ADS)

    Otake, Y.; Schafer, S.; Stayman, J. W.; Zbijewski, W.; Kleinszig, G.; Graumann, R.; Khanna, A. J.; Siewerdsen, J. H.

    2012-02-01

    Localization of target vertebrae is an essential step in minimally invasive spine surgery, with conventional methods relying on "level counting" - i.e., manual counting of vertebrae under fluoroscopy starting from readily identifiable anatomy (e.g., the sacrum). The approach requires an undesirable level of radiation, time, and is prone to counting errors due to the similar appearance of vertebrae in projection images; wrong-level surgery occurs in 1 of every ~3000 cases. This paper proposes a method to automatically localize target vertebrae in x-ray projections using 3D-2D registration between preoperative CT (in which vertebrae are preoperatively labeled) and intraoperative fluoroscopy. The registration uses an intensity-based approach with a gradient-based similarity metric and the CMA-ES algorithm for optimization. Digitally reconstructed radiographs (DRRs) and a robust similarity metric are computed on GPU to accelerate the process. Evaluation in clinical CT data included 5,000 PA and LAT projections randomly perturbed to simulate human variability in setup of mobile intraoperative C-arm. The method demonstrated 100% success for PA view (projection error: 0.42mm) and 99.8% success for LAT view (projection error: 0.37mm). Initial implementation on GPU provided automatic target localization within about 3 sec, with further improvement underway via multi-GPU. The ability to automatically label vertebrae in fluoroscopy promises to streamline surgical workflow, improve patient safety, and reduce wrong-site surgeries, especially in large patients for whom manual methods are time consuming and error prone.

  1. 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.

  2. Automatic P- and S-Phase Picker for High-Resolution Local Source Tomography: Application to the Alpine Region

    NASA Astrophysics Data System (ADS)

    Diehl, T.; Kissling, E.; Husen, S.; Deichmann, N.; Aldersons, F.

    2008-12-01

    Resolution and reliability of tomographic velocity models strongly depend on quality and consistency of available travel-time data. Arrival times routinely picked by network analysts on a day-to-day basis often yield a high level of noise due to mispicks and other inconsistencies, particularly in error assessment. Furthermore, tomographic studies at regional scales require merging of phase picks of several networks. Since a common quality assessment is usually not available for phase data provided by different networks, additional inconsistencies are introduced by the merging process. Considerable improvement in the quality of phase data can only be achieved by massive re-picking of seismograms. Considering the amount of data necessary for regional high-resolution tomography, algorithms combining accurate picking with an automated error assessment represent the best tool to derive large suitable data sets. In this work, we present algorithms for automatic P- and S-phase picking at local to regional distances including consistent picking error assessment. These algorithms are tested and applied to a waveform data set of the greater Alpine region. The MPX software is used to derive high-quality P-phase arrival times and the quality-attributed automatic picks are inverted for regional 1-D and 3-D P-wave models of the greater Alpine region. The comparison with a tomographic model based on standard routine phase data extracted from the ISC Bulletin illustrates effects on tomographic results due to consistency and reliability of our high- quality data set. In our proposed S-wave picking approach, we combine three commonly used phase detection and picking methods to a robust automated picking procedure. Information from the different techniques provides an 'in- situ' estimate of timing uncertainty and phase identification of the automatic S-phase pick. The average accuracy of automatic picks and their classification is comparable with manually picked reference picks, even

  3. Automatic estimation of midline shift in patients with cerebral glioma based on enhanced voigt model and local symmetry.

    PubMed

    Chen, Mingyang; Elazab, Ahmed; Jia, Fucang; Wu, Jianhuang; Li, Guanglin; Li, Xiaodong; Hu, Qingmao

    2015-12-01

    Cerebral glioma is one of the most aggressive space-occupying diseases, which will exhibit midline shift (MLS) due to mass effect. MLS has been used as an important feature for evaluating the pathological severity and patients' survival possibility. Automatic quantification of MLS is challenging due to deformation, complex shape and complex grayscale distribution. An automatic method is proposed and validated to estimate MLS in patients with gliomas diagnosed using magnetic resonance imaging (MRI). The deformed midline is approximated by combining mechanical model and local symmetry. An enhanced Voigt model which takes into account the size and spatial information of lesion is devised to predict the deformed midline. A composite local symmetry combining local intensity symmetry and local intensity gradient symmetry is proposed to refine the predicted midline within a local window whose size is determined according to the pinhole camera model. To enhance the MLS accuracy, the axial slice with maximum MSL from each volumetric data has been interpolated from a spatial resolution of 1 mm to 0.33 mm. The proposed method has been validated on 30 publicly available clinical head MRI scans presenting with MLS. It delineates the deformed midline with maximum MLS and yields a mean difference of 0.61 ± 0.27 mm, and average maximum difference of 1.89 ± 1.18 mm from the ground truth. Experiments show that the proposed method will yield better accuracy with the geometric center of pathology being the geometric center of tumor and the pathological region being the whole lesion. It has also been shown that the proposed composite local symmetry achieves significantly higher accuracy than the traditional local intensity symmetry and the local intensity gradient symmetry. To the best of our knowledge, for delineation of deformed midline, this is the first report on both quantification of gliomas and from MRI, which hopefully will provide valuable information for diagnosis

  4. Automatic localization of the prostate for on-line or off-line image-guided radiotherapy

    SciTech Connect

    Smitsmans, Monique H.P.; Wolthaus, Jochem W.H.; Artignan, Xavier; Bois, Josien de; Jaffray, David A.; Lebesque, Joos V.; Herk, Marcel van . E-mail: portal@nki.nl

    2004-10-01

    Purpose: With higher radiation dose, higher cure rates have been reported in prostate cancer patients. The extra margin needed to account for prostate motion, however, limits the level of dose escalation, because of the presence of surrounding organs at risk. Knowledge of the precise position of the prostate would allow significant reduction of the treatment field. Better localization of the prostate at the time of treatment is therefore needed, e.g. using a cone-beam computed tomography (CT) system integrated with the linear accelerator. Localization of the prostate relies upon manual delineation of contours in successive axial CT slices or interactive alignment and is fairly time-consuming. A faster method is required for on-line or off-line image-guided radiotherapy, because of prostate motion, for patient throughput and efficiency. Therefore, we developed an automatic method to localize the prostate, based on 3D gray value registration. Methods and materials: A study was performed on conventional repeat CT scans of 19 prostate cancer patients to develop the methodology to localize the prostate. For each patient, 8-13 repeat CT scans were made during the course of treatment. First, the planning CT scan and the repeat CT scan were registered onto the rigid bony structures. Then, the delineated prostate in the planning CT scan was enlarged by an optimum margin of 5 mm to define a region of interest in the planning CT scan that contained enough gray value information for registration. Subsequently, this region was automatically registered to a repeat CT scan using 3D gray value registration to localize the prostate. The performance of automatic prostate localization was compared to prostate localization using contours. Therefore, a reference set was generated by registering the delineated contours of the prostates in all scans of all patients. Gray value registrations that showed large differences with respect to contour registrations were detected with a {chi

  5. Automatic Phase Picker for Local and Teleseismic Events Using Wavelet Transform and Simulated Annealing

    NASA Astrophysics Data System (ADS)

    Gaillot, P.; Bardaine, T.; Lyon-Caen, H.

    2004-12-01

    Since recent years, various automatic phase pickers based on the wavelet transform have been developed. The main motivation for using wavelet transform is that they are excellent at finding the characteristics of transient signals, they have good time resolution at all periods, and they are easy to program for fast execution. Thus, the time-scale properties and flexibility of the wavelets allow detection of P and S phases in a broad frequency range making their utilization possible in various context. However, the direct application of an automatic picking program in a different context/network than the one for which it has been initially developed is quickly tedious. In fact, independently of the strategy involved in automatic picking algorithms (window average, autoregressive, beamforming, optimization filtering, neuronal network), all developed algorithms use different parameters that depend on the objective of the seismological study, the region and the seismological network. Classically, these parameters are manually defined by trial-error or calibrated learning stage. In order to facilitate this laborious process, we have developed an automated method that provide optimal parameters for the picking programs. The set of parameters can be explored using simulated annealing which is a generic name for a family of optimization algorithms based on the principle of stochastic relaxation. The optimization process amounts to systematically modifying an initial realization so as to decrease the value of the objective function, getting the realization acceptably close to the target statistics. Different formulations of the optimization problem (objective function) are discussed using (1) world seismicity data recorded by the French national seismic monitoring network (ReNass), (2) regional seismicity data recorded in the framework of the Corinth Rift Laboratory (CRL) experiment, (3) induced seismicity data from the gas field of Lacq (Western Pyrenees), and (4) micro

  6. Automatic localization of backscattering events due to particulate in urban areas

    NASA Astrophysics Data System (ADS)

    Gaudio, P.; Gelfusa, M.; Malizia, Andrea; Parracino, Stefano; Richetta, M.; Murari, A.; Vega, J.

    2014-10-01

    Particulate matter (PM), emitted by vehicles in urban traffic, can greatly affect environment air quality and have direct implications on both human health and infrastructure integrity. The consequences for society are relevant and can impact also on national health. Limits and thresholds of pollutants emitted by vehicles are typically regulated by government agencies. In the last few years, the interest in PM emissions has grown substantially due to both air quality issues and global warming. Lidar-Dial techniques are widely recognized as a costeffective alternative to monitor large regions of the atmosphere. To maximize the effectiveness of the measurements and to guarantee reliable, automatic monitoring of large areas, new data analysis techniques are required. In this paper, an original tool, the Universal Multi-Event Locator (UMEL), is applied to the problem of automatically indentifying the time location of peaks in Lidar measurements for the detection of particulate matter emitted by anthropogenic sources like vehicles. The method developed is based on Support Vector Regression and presents various advantages with respect to more traditional techniques. In particular, UMEL is based on the morphological properties of the signals and therefore the method is insensitive to the details of the noise present in the detection system. The approach is also fully general, purely software and can therefore be applied to a large variety of problems without any additional cost. The potential of the proposed technique is exemplified with the help of data acquired during an experimental campaign in the field in Rome.

  7. Stereo correspondence in one-dimensional Gabor stimuli.

    PubMed

    Prince, S J; Eagle, R A

    2000-01-01

    Previous data [Prince, S.J.D., & Eagle, R.A., (1999). Size-disparity correlation in human binocular depth perception. Proceedings of the Royal Society of London B, 266, 1361-1365] have demonstrated that the upper disparity limit for stereopsis (DMax) is considerably smaller in filtered noise stereograms than in isolated Gabor patches of the same spatial frequency. This discrepancy is not currently understood. Here, the solution of the correspondence problem for bandpass stereograms was further examined. On each trial observers were presented with two one-dimensional Gabor stimuli containing disparities of equal magnitude but opposite sign. Subjects were required to indicate which interval contained the crossed disparity stimulus. It was found that matching behaviour changed as a function of Gabor envelope size. As a function of disparity magnitude, performance cycled between mostly correct and mostly incorrect at large envelope sizes but was always correct at small envelope sizes. At intermediate envelope sizes performance was cyclical at small disparities but always correct at large disparities. The critical envelope size at which performance changed from mostly correct to mostly incorrect at 270 degrees phase disparity was used as a measure of the matching performance as other parameters of the Gabor were varied. Both absolute and relative contrast were shown to influence the perceived sign of matches. Critical envelope size was also found to decrease as a function of spatial frequency, but more slowly than a phase-based limit would predict. These data cannot be predicted by current models of stereopsis, and can be used to constrain future models. PMID:10720662

  8. Selecting the projection functions used in an iterative Gabor expansion

    NASA Astrophysics Data System (ADS)

    Braithwaite, R. N.; Beddoes, Michael P.

    1993-11-01

    This paper discusses the selection of projection functions used in an iterative implementation of the Gabor expansion. We show that the optimal support-limited projection function corresponds to a truncated version of Bastiaans' biorthonormal projection function for the case of a harmonic lattice. For various support widths, the lower bound of the optimal convergence factor is calculated. It is shown that Gabor's original projection function, which corresponds to the central lobe of Bastiaans' biorthonormal projection function, is truncated too severely, producing a significant overlap with elementary functions from high frequency channels. As a result, the lower bound for the optimal convergence factor and the rate of convergence will approach zero as the signal bandwidth (and the highest frequency Gabor channel) is increased. This work also determines the lower bound of the optimal convergence factor for projection functions implemented using log-polar lattices. For both the harmonic and log-polar lattices, we investigate the trade-off between spread of convergence and the size of the projection function.

  9. Analysis of breast thermograms using Gabor wavelet anisotropy index.

    PubMed

    Suganthi, S S; Ramakrishnan, S

    2014-09-01

    In this study, an attempt is made to distinguish the normal and abnormal tissues in breast thermal images using Gabor wavelet transform. Thermograms having normal, benign and malignant tissues are considered in this study and are obtained from public online database. Segmentation of breast tissues is performed by multiplying raw image and ground truth mask. Left and right breast regions are separated after removing the non-breast regions from the segmented image. Based on the pathological conditions, the separated breast regions are grouped as normal and abnormal tissues. Gabor features such as energy and amplitude in different scales and orientations are extracted. Anisotropy and orientation measures are calculated from the extracted features and analyzed. A distinctive variation is observed among different orientations of the extracted features. It is found that the anisotropy measure is capable of differentiating the structural changes due to varied metabolic conditions. Further, the Gabor features also showed relative variations among different pathological conditions. It appears that these features can be used efficiently to identify normal and abnormal tissues and hence, improve the relevance of breast thermography in early detection of breast cancer and content based image retrieval. PMID:25064085

  10. Automatic loop closure detection using multiple cameras for 3D indoor localization

    NASA Astrophysics Data System (ADS)

    Kua, John; Corso, Nicholas; Zakhor, Avideh

    2012-03-01

    Automated 3D modeling of building interiors is useful in applications such as virtual reality and environment mapping. We have developed a human operated backpack data acquisition system equipped with a variety of sensors such as cameras, laser scanners, and orientation measurement sensors to generate 3D models of building interiors, including uneven surfaces and stairwells. An important intermediate step in any 3D modeling system, including ours, is accurate 6 degrees of freedom localization over time. In this paper, we propose two approaches to improve localization accuracy over our previously proposed methods. First, we develop an adaptive localization algorithm which takes advantage of the environment's floor planarity whenever possible. Secondly, we show that by including all the loop closures resulting from two cameras facing away from each other, it is possible to reduce localization error in scenarios where parts of the acquisition path is retraced. We experimentally characterize the performance gains due to both schemes.

  11. Measurement of subcellular texture by optical Gabor-like filtering with a digital micromirror device

    PubMed Central

    Pasternack, Robert M.; Qian, Zhen; Zheng, Jing-Yi; Metaxas, Dimitris N.; White, Eileen; Boustany, Nada N.

    2010-01-01

    We demonstrate an optical Fourier processing method to quantify object texture arising from subcellular feature orientation within unstained living cells. Using a digital micromirror device as a Fourier spatial filter, we measured cellular responses to two-dimensional optical Gabor-like filters optimized to sense orientation of nonspherical particles, such as mitochondria, with a width around 0.45 μm. Our method showed significantly rounder structures within apoptosis-defective cells lacking the proapoptotic mitochondrial effectors Bax and Bak, when compared with Bax/Bak expressing cells functional for apoptosis, consistent with reported differences in mitochondrial shape in these cells. By decoupling spatial frequency resolution from image resolution, this method enables rapid analysis of nonspherical submicrometer scatterers in an under-sampled large field of view and yields spatially localized morphometric parameters that improve the quantitative assessment of biological function. PMID:18830354

  12. Two-step fringe pattern analysis with a Gabor filter bank

    NASA Astrophysics Data System (ADS)

    Rivera, Mariano; Dalmau, Oscar; Gonzalez, Adonai; Hernandez-Lopez, Francisco

    2016-10-01

    We propose a two-shot fringe analysis method for Fringe Patterns (FPs) with random phase-shift and changes in illumination components. These conditions reduce the acquisition time and simplify the experimental setup. Our method builds upon a Gabor Filter (GF) bank that eliminates noise and estimates the phase from the FPs. The GF bank allows us to obtain two phase maps with a sign ambiguity between them. Due to the fact that the random sign map is common to both computed phases, we can correct the sign ambiguity. We estimate a local phase-shift from the absolute wrapped residual between the estimated phases. Next, we robustly compute the global phase-shift. In order to unwrap the phase, we propose a robust procedure that interpolates unreliable phase regions obtained after applying the GF bank. We present numerical experiments that demonstrate the performance of our method.

  13. Automatic detection of regions of interest in breast ultrasound images based on local phase information.

    PubMed

    Wang, Xin; Guo, Yi; Wang, Yuanyuan

    2015-01-01

    Due to the inherent speckling and low contrast of ultrasonic images, the accurate and efficient location of regions of interest (ROIs) is still a challenging task for breast ultrasound (BUS) computer-aided diagnosis (CAD) systems. In this paper, a fully automatic and efficient ROI generation approach is proposed. First, a BUS image is preprocessed to improve image quality. Second, a phase of max-energy orientation (PMO) image of the preprocessed image is calculated. Otsu's threshold selection method is then used to binarize the preprocessed image, the phase image and the composed image obtained by adding and normalizing the set of two images. Finally, a region selection algorithm is developed to select the true tumor region from these three binary images before generating a final ROI. The method was validated on a BUS database with 168 cases (81 benign and 87 malignant); the accuracy, average precision rate and average recall rate are calculated and compared with conventional method. The results indicate that the proposed method is more accurate and efficient in locating ROIs. PMID:26405886

  14. Semi-automatic medical image segmentation with adaptive local statistics in Conditional Random Fields framework.

    PubMed

    Hu, Yu-Chi J; Grossberg, Michael D; Mageras, Gikas S

    2008-01-01

    Planning radiotherapy and surgical procedures usually require onerous manual segmentation of anatomical structures from medical images. In this paper we present a semi-automatic and accurate segmentation method to dramatically reduce the time and effort required of expert users. This is accomplished by giving a user an intuitive graphical interface to indicate samples of target and non-target tissue by loosely drawing a few brush strokes on the image. We use these brush strokes to provide the statistical input for a Conditional Random Field (CRF) based segmentation. Since we extract purely statistical information from the user input, we eliminate the need of assumptions on boundary contrast previously used by many other methods, A new feature of our method is that the statistics on one image can be reused on related images without registration. To demonstrate this, we show that boundary statistics provided on a few 2D slices of volumetric medical data, can be propagated through the entire 3D stack of images without using the geometric correspondence between images. In addition, the image segmentation from the CRF can be formulated as a minimum s-t graph cut problem which has a solution that is both globally optimal and fast. The combination of a fast segmentation and minimal user input that is reusable, make this a powerful technique for the segmentation of medical images. PMID:19163362

  15. Automatic processing in moiré deflectometry by local fringe direction calculation.

    PubMed

    Canabal, H; Quiroga, J A; Bernabeu, E

    1998-09-01

    An algorithm for accurately extracting the local fringe direction is presented. The algorithm estimates, in the neighborhood of n x n points, the direction of the gradient that points normal to the local fringe direction. The performance of four different derivative kernels is also compared. Since this method is sensitive to noise and variations in background and amplitude, a preprocessing step is used to limit these error sources. The method has been applied to the moiré deflectogram of a spherical and a progressive addition ophthalmic lens, resulting in a map of the refractive power of these lenses. The results are compared with the data obtained with a commercial focimeter. This technique is useful for analyzing the fringe patterns where the fringe direction is variable and must be obtained locally. PMID:18286083

  16. System for analysis of LANDSAT agricultural data: Automatic computer-assisted proportion estimation of local areas

    NASA Technical Reports Server (NTRS)

    Nalepka, R. F. (Principal Investigator); Kauth, R. J.; Thomas, G. S.

    1976-01-01

    The author has identified the following significant results. A conceptual man machine system framework was created for a large scale agricultural remote sensing system. The system is based on and can grow out of the local recognition mode of LACIE, through a gradual transition wherein computer support functions supplement and replace AI functions. Local proportion estimation functions are broken into two broad classes: (1) organization of the data within the sample segment; and (2) identification of the fields or groups of fields in the sample segment.

  17. Osteoarthritis Classification Using Self Organizing Map Based on Gabor Kernel and Contrast-Limited Adaptive Histogram Equalization

    PubMed Central

    Anifah, Lilik; Purnama, I Ketut Eddy; Hariadi, Mochamad; Purnomo, Mauridhi Hery

    2013-01-01

    Localization is the first step in osteoarthritis (OA) classification. Manual classification, however, is time-consuming, tedious, and expensive. The proposed system is designed as decision support system for medical doctors to classify the severity of knee OA. A method has been proposed here to localize a joint space area for OA and then classify it in 4 steps to classify OA into KL-Grade 0, KL-Grade 1, KL-Grade 2, KL-Grade 3 and KL-Grade 4, which are preprocessing, segmentation, feature extraction, and classification. In this proposed system, right and left knee detection was performed by employing the Contrast-Limited Adaptive Histogram Equalization (CLAHE) and the template matching. The Gabor kernel, row sum graph and moment methods were used to localize the junction space area of knee. CLAHE is used for preprocessing step, i.e.to normalize the varied intensities. The segmentation process was conducted using the Gabor kernel, template matching, row sum graph and gray level center of mass method. Here GLCM (contrast, correlation, energy, and homogeinity) features were employed as training data. Overall, 50 data were evaluated for training and 258 data for testing. Experimental results showed the best performance by using gabor kernel with parameters α=8, θ=0, Ψ=[0 π/2], γ=0,8, N=4 and with number of iterations being 5000, momentum value 0.5 and α0=0.6 for the classification process. The run gave classification accuracy rate of 93.8% for KL-Grade 0, 70% for KL-Grade 1, 4% for KL-Grade 2, 10% for KL-Grade 3 and 88.9% for KL-Grade 4. PMID:23525188

  18. Osteoarthritis classification using self organizing map based on gabor kernel and contrast-limited adaptive histogram equalization.

    PubMed

    Anifah, Lilik; Purnama, I Ketut Eddy; Hariadi, Mochamad; Purnomo, Mauridhi Hery

    2013-01-01

    Localization is the first step in osteoarthritis (OA) classification. Manual classification, however, is time-consuming, tedious, and expensive. The proposed system is designed as decision support system for medical doctors to classify the severity of knee OA. A method has been proposed here to localize a joint space area for OA and then classify it in 4 steps to classify OA into KL-Grade 0, KL-Grade 1, KL-Grade 2, KL-Grade 3 and KL-Grade 4, which are preprocessing, segmentation, feature extraction, and classification. In this proposed system, right and left knee detection was performed by employing the Contrast-Limited Adaptive Histogram Equalization (CLAHE) and the template matching. The Gabor kernel, row sum graph and moment methods were used to localize the junction space area of knee. CLAHE is used for preprocessing step, i.e.to normalize the varied intensities. The segmentation process was conducted using the Gabor kernel, template matching, row sum graph and gray level center of mass method. Here GLCM (contrast, correlation, energy, and homogeinity) features were employed as training data. Overall, 50 data were evaluated for training and 258 data for testing. Experimental results showed the best performance by using gabor kernel with parameters α=8, θ=0, Ψ=[0 π/2], γ=0,8, N=4 and with number of iterations being 5000, momentum value 0.5 and α0=0.6 for the classification process. The run gave classification accuracy rate of 93.8% for KL-Grade 0, 70% for KL-Grade 1, 4% for KL-Grade 2, 10% for KL-Grade 3 and 88.9% for KL-Grade 4. PMID:23525188

  19. INFLUENCE OF LOCALIZER AND SCAN DIRECTION ON THE DOSE-REDUCING EFFECT OF AUTOMATIC TUBE CURRENT MODULATION IN COMPUTED TOMOGRAPHY.

    PubMed

    Franck, C; Bacher, K

    2016-06-01

    The purpose of this study was to investigate the influence of the localizer and scan direction on the dose-reducing efficacy of the automatic tube current modulation (ATCM) in computed tomography (CT). Craniocaudal and caudocranial chest CT scans, based on anterior-posterior (AP), posterior-anterior (PA), lateral (LAT) or dual AP/LAT localizers, of an anthropomorphic phantom containing thermoluminescent dosimeters (TLDs), were made on three Siemens systems. TLD readings were converted to lung and thyroid doses. A second dose estimation was performed based on Monte Carlo simulations. In addition, the ATCM behaviour of GE and Toshiba was evaluated based on AP, PA and LAT localizers. Compared with AP, tube currents of PA and AP/LAT scans were on average 20 % higher and 40 % lower, respectively, for the Siemens systems. Consequently, thyroid and lung doses increased with 60 % with a PA instead of an AP/LAT scan, with significant differences in image noise. Moreover, the thyroid dose halves by taking the scan in caudocranial direction. Noise values were not significantly different when changing scan direction. PMID:27056145

  20. Robotic camera for automatic localization of steam generator tubes in nuclear power stations

    NASA Astrophysics Data System (ADS)

    Cers, Philippe; Garnero, Marie-Agnes

    1994-11-01

    Maintenance of steam generators occupies a substantial proportion of scheduled shutdowns at nuclear power stations. Maintenance operations are broken down into a number of distinct phases; these are performed separately to ensure accountability for the work carried out at each stage, thereby guaranteeing the quality of the maintenance process as a whole. One of these phases, known as `marking,' consists in locating certain tubes in the steam generator tube plate and marking them using a suitable system. The list of tubes for marking may be determined on the basis of prior tests. Marked tubes will undergo subsequent operations as required, such as plugging for example. Clearly, the quality of the marking process will have a significant impact on all subsequent maintenance operations on tubes in the secondary bundle. Present-day marking tools make little use of automation, and over-reliance on human judgement means that the marking phase is liable to error. Moreover, depending on the number of tubes to mark, this phase can be long and fastidious. With these considerations in mind, the EDF Research Division has developed a display system for locating steam generator tubes, with the main purpose of facilitating marking operations. Following an initialization phase, this system (named LUCANER) provides the operator with a simple, reliable and fully automatic method for locating tubes in the tube plate. Besides reducing the risk of error, the system also reduces the time required for the marking phase. The system can also be used for complementary phases involving checks on markings, checks on plugging, etc. In a wider context, it provides visual inspection capabilities over a large part of the bowl.

  1. Gabor feature-based apple quality inspection using kernel principal component analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Automated inspection of apple quality involves computer recognition of good apples and blemished apples based on geometric or statistical features derived from apple images. This paper introduces a Gabor feature-based kernel, principal component analysis (PCA) method; by combining Gabor wavelet rep...

  2. Stability of Gabor Frames Under Small Time Hamiltonian Evolutions

    NASA Astrophysics Data System (ADS)

    de Gosson, Maurice A.; Gröchenig, Karlheinz; Romero, José Luis

    2016-06-01

    We consider Hamiltonian deformations of Gabor systems, where the window evolves according to the action of a Schrödinger propagator and the phase-space nodes evolve according to the corresponding Hamiltonian flow. We prove the stability of the frame property for small times and Hamiltonians consisting of a quadratic polynomial plus a potential in the Sjöstrand class with bounded second-order derivatives. This answers a question raised in de Gosson (Appl Comput Harmonic Anal 38(2):196-221, 2015)

  3. Stability of Gabor Frames Under Small Time Hamiltonian Evolutions

    NASA Astrophysics Data System (ADS)

    de Gosson, Maurice A.; Gröchenig, Karlheinz; Romero, José Luis

    2016-05-01

    We consider Hamiltonian deformations of Gabor systems, where the window evolves according to the action of a Schrödinger propagator and the phase-space nodes evolve according to the corresponding Hamiltonian flow. We prove the stability of the frame property for small times and Hamiltonians consisting of a quadratic polynomial plus a potential in the Sjöstrand class with bounded second-order derivatives. This answers a question raised in de Gosson (Appl Comput Harmonic Anal 38(2):196-221, 2015)

  4. Gabor Wave Packet Method to Solve Plasma Wave Equations

    SciTech Connect

    A. Pletzer; C.K. Phillips; D.N. Smithe

    2003-06-18

    A numerical method for solving plasma wave equations arising in the context of mode conversion between the fast magnetosonic and the slow (e.g ion Bernstein) wave is presented. The numerical algorithm relies on the expansion of the solution in Gaussian wave packets known as Gabor functions, which have good resolution properties in both real and Fourier space. The wave packets are ideally suited to capture both the large and small wavelength features that characterize mode conversion problems. The accuracy of the scheme is compared with a standard finite element approach.

  5. A novel local-phase method of automatic atlas construction in fetal ultrasound

    NASA Astrophysics Data System (ADS)

    Fathima, Sana; Rueda, Sylvia; Papageorghiou, Aris; Noble, J. Alison

    2011-03-01

    In recent years, fetal diagnostics have relied heavily on clinical assessment and biometric analysis of manually acquired ultrasound images. There is a profound need for automated and standardized evaluation tools to characterize fetal growth and development. This work addresses this need through the novel use of feature-based techniques to develop evaluators of fetal brain gestation. The methodology is comprised of an automated database-driven 2D/3D image atlas construction method, which includes several iterative processes. A unique database was designed to store fetal image data acquired as part of the Intergrowth-21st study. This database drives the proposed automated atlas construction methodology using local phase information to perform affine registration with normalized mutual information as the similarity parameter, followed by wavelet-based image fusion and averaging. The unique feature-based application of local phase and wavelet fusion towards creating the atlas reduces the intensity dependence and difficulties in registering ultrasound images. The method is evaluated on fetal transthalamic head ultrasound images of 20 weeks gestation. The results show that the proposed method is more robust to intensity variations than standard intensity-based methods. Results also suggest that the feature-based approach improves the registration accuracy needed in creating a clinically valid ultrasound image atlas.

  6. SU-D-BRF-03: Improvement of TomoTherapy Megavoltage Topogram Image Quality for Automatic Registration During Patient Localization

    SciTech Connect

    Scholey, J; White, B; Qi, S; Low, D

    2014-06-01

    Purpose: To improve the quality of mega-voltage orthogonal scout images (MV topograms) for a fast and low-dose alternative technique for patient localization on the TomoTherapy HiART system. Methods: Digitally reconstructed radiographs (DRR) of anthropomorphic head and pelvis phantoms were synthesized from kVCT under TomoTherapy geometry (kV-DRR). Lateral (LAT) and anterior-posterior (AP) aligned topograms were acquired with couch speeds of 1cm/s, 2cm/s, and 3cm/s. The phantoms were rigidly translated in all spatial directions with known offsets in increments of 5mm, 10mm, and 15mm to simulate daily positioning errors. The contrast of the MV topograms was automatically adjusted based on the image intensity characteristics. A low-pass fast Fourier transform filter removed high-frequency noise and a Weiner filter reduced stochastic noise caused by scattered radiation to the detector array. An intensity-based image registration algorithm was used to register the MV topograms to a corresponding kV-DRR by minimizing the mean square error between corresponding pixel intensities. The registration accuracy was assessed by comparing the normalized cross correlation coefficients (NCC) between the registered topograms and the kV-DRR. The applied phantom offsets were determined by registering the MV topograms with the kV-DRR and recovering the spatial translation of the MV topograms. Results: The automatic registration technique provided millimeter accuracy and was robust for the deformed MV topograms for three tested couch speeds. The lowest average NCC for all AP and LAT MV topograms was 0.96 for the head phantom and 0.93 for the pelvis phantom. The offsets were recovered to within 1.6mm and 6.5mm for the processed and the original MV topograms respectively. Conclusion: Automatic registration of the processed MV topograms to a corresponding kV-DRR recovered simulated daily positioning errors that were accurate to the order of a millimeter. These results suggest the clinical

  7. Automatic variance reduction for Monte Carlo simulations via the local importance function transform

    SciTech Connect

    Turner, S.A.

    1996-02-01

    The author derives a transformed transport problem that can be solved theoretically by analog Monte Carlo with zero variance. However, the Monte Carlo simulation of this transformed problem cannot be implemented in practice, so he develops a method for approximating it. The approximation to the zero variance method consists of replacing the continuous adjoint transport solution in the transformed transport problem by a piecewise continuous approximation containing local biasing parameters obtained from a deterministic calculation. He uses the transport and collision processes of the transformed problem to bias distance-to-collision and selection of post-collision energy groups and trajectories in a traditional Monte Carlo simulation of ``real`` particles. He refers to the resulting variance reduction method as the Local Importance Function Transform (LIFI) method. He demonstrates the efficiency of the LIFT method for several 3-D, linearly anisotropic scattering, one-group, and multigroup problems. In these problems the LIFT method is shown to be more efficient than the AVATAR scheme, which is one of the best variance reduction techniques currently available in a state-of-the-art Monte Carlo code. For most of the problems considered, the LIFT method produces higher figures of merit than AVATAR, even when the LIFT method is used as a ``black box``. There are some problems that cause trouble for most variance reduction techniques, and the LIFT method is no exception. For example, the author demonstrates that problems with voids, or low density regions, can cause a reduction in the efficiency of the LIFT method. However, the LIFT method still performs better than survival biasing and AVATAR in these difficult cases.

  8. Using pattern recognition to automatically localize reflection hyperbolas in data from ground penetrating radar

    NASA Astrophysics Data System (ADS)

    Maas, Christian; Schmalzl, Jörg

    2013-08-01

    Ground Penetrating Radar (GPR) is used for the localization of supply lines, land mines, pipes and many other buried objects. These objects can be recognized in the recorded data as reflection hyperbolas with a typical shape depending on depth and material of the object and the surrounding material. To obtain the parameters, the shape of the hyperbola has to be fitted. In the last years several methods were developed to automate this task during post-processing. In this paper we show another approach for the automated localization of reflection hyperbolas in GPR data by solving a pattern recognition problem in grayscale images. In contrast to other methods our detection program is also able to immediately mark potential objects in real-time. For this task we use a version of the Viola-Jones learning algorithm, which is part of the open source library "OpenCV". This algorithm was initially developed for face recognition, but can be adapted to any other simple shape. In our program it is used to narrow down the location of reflection hyperbolas to certain areas in the GPR data. In order to extract the exact location and the velocity of the hyperbolas we apply a simple Hough Transform for hyperbolas. Because the Viola-Jones Algorithm reduces the input for the computational expensive Hough Transform dramatically the detection system can also be implemented on normal field computers, so on-site application is possible. The developed detection system shows promising results and detection rates in unprocessed radargrams. In order to improve the detection results and apply the program to noisy radar images more data of different GPR systems as input for the learning algorithm is necessary.

  9. Cardiac phase extraction in IVUS sequences using 1-D Gabor filters.

    PubMed

    Barajas, Joel; Caballero, Karla L; Rodriguez, Oriol; Radeva, Petia

    2007-01-01

    A main issue in the automatic analysis of Intravascular Ultrasound (IVUS) images is the presence of periodic changes provoked by heart motion during the cardiac cycle. Although the Electrocardiogram (ECG) signal can be used to gate the sequence, few IVUS systems incorporate the ECG-gating option, and the synchronization between them implies several issues. In this paper, we present a fast and robust method to assign a phase in the cardiac cycle to each image in the sequence directly from in vivo clinical IVUS sequences. It is based on the assumption that the vessel wall is significantly brighter than the blood in each IVUS beam. To guarantee stability in this assumption, we use normalized reconstructed images. Then, the wall boundary is extracted for all the radial beams in the sequence and a matrix with these positions is formed. This matrix is filtered using a bank of 1-D Gabor filters centered at the predominant frequency of a given number of windows in the sequence. After filtering, we combine the responses to obtain a unique phase within the cardiac cycle for each image. For this study, we gate the sequence to make the sequence comparable with other ones of the same patient. The method is tested with 12 pullbacks of real patients and 15 synthetic tests. PMID:18001960

  10. Automatic classification of prostate stromal tissue in histological images using Haralick descriptors and Local Binary Patterns

    NASA Astrophysics Data System (ADS)

    Oliveira, D. L. L.; Nascimento, M. Z.; Neves, L. A.; Batista, V. R.; Godoy, M. F.; Jacomini, R. S.; Duarte, Y. A. S.; Arruda, P. F. F.; Neto, D. S.

    2014-03-01

    In this paper we presente a classification system that uses a combination of texture features from stromal regions: Haralick features and Local Binary Patterns (LBP) in wavelet domain. The system has five steps for classification of the tissues. First, the stromal regions were detected and extracted using segmentation techniques based on thresholding and RGB colour space. Second, the Wavelet decomposition was applied in the extracted regions to obtain the Wavelet coefficients. Third, the Haralick and LBP features were extracted from the coefficients. Fourth, relevant features were selected using the ANOVA statistical method. The classication (fifth step) was performed with Radial Basis Function (RBF) networks. The system was tested in 105 prostate images, which were divided into three groups of 35 images: normal, hyperplastic and cancerous. The system performance was evaluated using the area under the ROC curve and resulted in 0.98 for normal versus cancer, 0.95 for hyperplasia versus cancer and 0.96 for normal versus hyperplasia. Our results suggest that texture features can be used as discriminators for stromal tissues prostate images. Furthermore, the system was effective to classify prostate images, specially the hyperplastic class which is the most difficult type in diagnosis and prognosis.

  11. Multiwindow Gabor-type transform for signal representation and analysis

    NASA Astrophysics Data System (ADS)

    Zibulski, Meir; Zeevi, Yehoshua Y.

    1995-09-01

    The Gabor scheme is generalized to incorporate several window functions as well as kernels other than the exponential. The properties of the sequence of representation functions are characterized by an approach based on the concept of frames. the frame operator associated with the multi-window Gabor-type frame, is examined for a rational oversampling rate by representing the frame operator as a finite order matrix-valued function in the Zak Transform domain. Completeness and frame properties of the sequence of representation functions are examined in relation to the properties of the matrix-valued function. Calculation of the frame bounds and the dual frame, as well as the issue of tight frames are considered. It is shown that the properties of the sequence of representation functions are essentially not changed by replacing the widely-used exponential kernel with other kernels. The issue of a different sampling rate for each window is also considered. The so-called Balian-Low theorem is generalized to consideration of a scheme of multi-windows, which makes it possible to overcome the constraint imposed by the original theorem in the case of a single window.

  12. Automatic Localization of the Anterior Commissure, Posterior Commissure, and Midsagittal Plane in MRI Scans using Regression Forests

    PubMed Central

    Liu, Yuan; Dawant, Benoit M.

    2015-01-01

    Localizing the anterior and posterior commissures (AC/PC) and the midsagittal plane (MSP) is crucial in stereotactic and functional neurosurgery, human brain mapping, and medical image processing. We present a learning-based method for automatic and efficient localization of these landmarks and the plane using regression forests. Given a point in an image, we first extract a set of multi-scale long-range contextual features. We then build random forests models to learn a nonlinear relationship between these features and the probability of the point being a landmark or in the plane. Three-stage coarse-to-fine models are trained for the AC, PC, and MSP separately using down-sampled by 4, down-sampled by 2, and the original images. Localization is performed hierarchically, starting with a rough estimation that is progressively refined. We evaluate our method using a leave-one-out approach with 100 clinical T1-weighted images and compare it to state-of-the-art methods including an atlas-based approach with six nonrigid registration algorithms and a model-based approach for the AC and PC, and a global symmetry-based approach for the MSP. Our method results in an overall error of 0.55±0.30mm for AC, 0.56±0.28mm for PC, 1.08°±0.66° in the plane’s normal direction and 1.22±0.73 voxels in average distance for MSP; it performs significantly better than four registration algorithms and the model-based method for AC and PC, and the global symmetry-based method for MSP. We also evaluate the sensitivity of our method to image quality and parameter values. We show that it is robust to asymmetry, noise, and rotation. Computation time is 25 seconds. PMID:25955855

  13. Automatic Localization of Target Vertebrae in Spine Surgery: Clinical Evaluation of the LevelCheck Registration Algorithm

    PubMed Central

    Lo, Sheng-fu L.; Otake, Yoshito; Puvanesarajah, Varun; Wang, Adam S.; Uneri, Ali; De Silva, Tharindu; Vogt, Sebastian; Kleinszig, Gerhard; Elder, Benjamin D; Goodwin, C. Rory; Kosztowski, Thomas A.; Liauw, Jason A.; Groves, Mari; Bydon, Ali; Sciubba, Daniel M.; Witham, Timothy F.; Wolinsky, Jean-Paul; Aygun, Nafi; Gokaslan, Ziya L.; Siewerdsen, Jeffrey H.

    2015-01-01

    Study Design A 3D-2D image registration algorithm, “LevelCheck,” was used to automatically label vertebrae in intraoperative mobile radiographs obtained during spine surgery. Accuracy, computation time, and potential failure modes were evaluated in a retrospective study of 20 patients. Objective To measurethe performance of the LevelCheck algorithm using clinical images acquired during spine surgery. Summary of Background Data In spine surgery, the potential for wrong level surgery is significant due to the difficulty of localizing target vertebrae based solely on visual impression, palpation, and fluoroscopy. To remedy this difficulty and reduce the risk of wrong-level surgery, our team introduced a program (dubbed LevelCheck) to automatically localize target vertebrae in mobile radiographs using robust 3D-2D image registration to preoperative CT. Methods Twenty consecutive patients undergoing thoracolumbar spine surgery, for whom both a preoperative CT scan and an intraoperative mobile radiograph were available, were retrospectively analyzed. A board-certified neuroradiologist determined the “true” vertebra levels in each radiograph. Registration of the preoperative CT to the intraoperative radiographwere calculated via LevelCheck, and projection distance errors were analyzed. Five hundred random initializations were performed for eachpatient, andalgorithm settings (viz., the number of robust multi-starts, ranging 50 to 200) were varied to evaluate the tradeoff between registration error and computation time. Failure mode analysis was performed by individually analyzing unsuccessful registrations (>5 mm distance error) observed with 50 multi-starts. Results At 200 robust multi-starts (computation time of ∼26 seconds), the registration accuracy was 100% across all 10,000 trials. As the number of multi-starts (and computation time) decreased, the registration remained fairly robust, down to 99.3% registration accuracy at 50 multi-starts (computation time

  14. Robust ear recognition via nonnegative sparse representation of Gabor orientation information.

    PubMed

    Zhang, Baoqing; Mu, Zhichun; Zeng, Hui; Luo, Shuang

    2014-01-01

    Orientation information is critical to the accuracy of ear recognition systems. In this paper, a new feature extraction approach is investigated for ear recognition by using orientation information of Gabor wavelets. The proposed Gabor orientation feature can not only avoid too much redundancy in conventional Gabor feature but also tend to extract more precise orientation information of the ear shape contours. Then, Gabor orientation feature based nonnegative sparse representation classification (Gabor orientation + NSRC) is proposed for ear recognition. Compared with SRC in which the sparse coding coefficients can be negative, the nonnegativity of NSRC conforms to the intuitive notion of combining parts to form a whole and therefore is more consistent with the biological modeling of visual data. Additionally, the use of Gabor orientation features increases the discriminative power of NSRC. Extensive experimental results show that the proposed Gabor orientation feature based nonnegative sparse representation classification paradigm achieves much better recognition performance and is found to be more robust to challenging problems such as pose changes, illumination variations, and ear partial occlusion in real-world applications. PMID:24723792

  15. Implementation of an Automatic S-Wave Picker for Local Earthquake Tomography in South-Central Tibet

    NASA Astrophysics Data System (ADS)

    Riddle, E.; Nabelek, J.; Braunmiller, J.

    2012-12-01

    The HiCLIMB broadband seismic experiment (2002-2005) operated 233 stations along an 800 km long north-south line from the Himalayan foreland into the central Tibetan Plateau and in a 350x350 km sub-array within southern Tibet and central and eastern Nepal. From June 2004 to August 2005, over 22,500 local and regional seismic events were recorded throughout the south-central Tibetan Plateau based on automated arrival time picks. This dataset provides an opportunity to jointly invert for crust and upper mantle velocity structure along with earthquake locations using both P and S waves. The automated picks, however, were determined from vertical component data resulting in relatively few S picks of generally low quality. To increase the number of accurate S arrivals, we implemented an automatic S-wave picker, which uses signal attributes from three-component seismic data. The signal attributes used are rectilinearity, directivity relative to incoming P wave, ratio of transverse to overall energy and transverse amplitude. An S pick is declared when the combination of signal attributes reaches a noise dependent threshold. We used manual picks from events throughout south-central Tibet to adjust picking parameters and thresholds to optimize automatic S picks. For shallow events we found Sg can be picked reliably to the Sg/Sn crossover distance of approximately 3° while Sn arrivals are absent. Deep events beneath the southern Tibetan Plateau and the High Himalayas produce clear S arrivals that can be picked to about 5°-6° distance. Applying the S-picker to 584 larger (ML≥2.7), well-recorded events led to about 20,000 S picks; doubling the number of picks and significantly improving their accuracy. Compared to manual picks, the new automatic S picks show average differences of approximately 0.1 s from 0 to 100 km, 0.25 s from 100 to 200 km and 0.5 s from 200 to 250 km distance. This is significantly better than our previous S picks, which, from 100 to 250 km distance

  16. Starlet transform applied to digital Gabor holographic microscopy.

    PubMed

    Aguilar, Juan C; Misawa, Masaki; Matsuda, Kiyofumi; Rehman, Shakil; Yasumoto, Masato; Suzuki, Yoshio; Takeuchi, Akihisa; Berriel-Valdos, L R

    2016-08-20

    In this paper, we show how the starlet transform can be used to process holograms from a digital Gabor holographic microscope. The starlet transform is an undecimated wavelet transform with the property that when performing reconstruction, we only need to add all scales without the use of a synthesis filter bank. When the starlet transform is applied to a hologram, we divide the hologram into a certain number of scales, process them separately, and propagate each one using a numerical diffraction method. After diffraction propagation, we perform processing on complex amplitudes that correspond to individual scales. With the aforementioned procedure, it is possible to reduce the background and effects of parasitic fringes caused by high coherence of a laser, enhance the contrast, and reduce the effects of the twin image. Experimental results confirming the method are presented. PMID:27556979

  17. Matrix approach to frame analysis of Gabor-type image representation

    NASA Astrophysics Data System (ADS)

    Zibulski, Meir; Zeevi, Yehoshua Y.

    1993-11-01

    An approach for characterizing the properties of basis functions which constitute a finite scheme of discrete Gabor representation is presented in the context of oversampling. The approach is based on the concept of frames and utilizes the Piecewise Finite Zak Transform (PFZT). The frame operator associated with the Gabor-type frame is examined by representing the frame operator as a matrix-valued function in the PFZT domain. The frame property of the Gabor representation functions are examined in relation to the properties of the matrix-valued function. The frame bounds are calculated by means of the eigenvalues of the matrix-valued function, and the dual frame, which is used in calculation of the expansion coefficients, is expressed by means of the inverse matrix. DFT-based algorithms for computation of the expansion coefficients, and for the reconstruction of signals from these coefficients are generalized for the case of oversampling of the Gabor space.

  18. On the use of log-gabor features for subsurface object detection using ground penetrating radar

    NASA Astrophysics Data System (ADS)

    Harris, Samuel; Ho, K. C.; Zare, Alina

    2016-05-01

    regions with significant amount of metal debris. The challenge for the handheld GPR is to reduce the false alarm rate and limit the undesirable human operator effect. This paper proposes the use of log-Gabor features to improve the detection performance. In particular, we apply 36 log-Gabor filters to the B-scan of the GPR data in the time domain for the purpose to extract the edge behaviors of a prescreener alarm. The 36 log-Gabor filters cover the entire frequency plane with different bandwidths and orientations. The energy of each filter output forms an element of the feature vector and an SVM is trained to perform target vs non-target classification. Experimental results using the experimental hand held demonstrator data collected at a government site supports the increase in detection performance by using the log-Gabor features.

  19. Automatic identification of biological microorganisms using three-dimensional complex morphology.

    PubMed

    Yeom, Seokwon; Javidi, Bahram

    2006-01-01

    We propose automated identification of microorganisms using three-dimensional (3-D) complex morphology. This 3-D complex morphology pattern includes the complex amplitude (magnitude and phase) of computationally reconstructed holographic images at arbitrary depths. Microscope-based single-exposure on-line (SEOL) digital holography records and reconstructs holographic images of the biological microorganisms. The 3-D automatic recognition is processed by segmentation, feature extraction by Gabor-based wavelets, automatic feature vector selection by graph matching, training rules, and a decision process. Graph matching combined with Gabor feature vectors measures the similarity of complex geometrical shapes between a reference microorganism and unknown biological samples. Automatic selection of the training data is proposed to achieve a fully automatic recognition system. Preliminary experimental results are presented for 3-D image recognition of Sphacelaria alga and Tribonema aequale alga. PMID:16674207

  20. Automatic localization of endoscope in intraoperative CT image: A simple approach to augmented reality guidance in laparoscopic surgery.

    PubMed

    Bernhardt, Sylvain; Nicolau, Stéphane A; Agnus, Vincent; Soler, Luc; Doignon, Christophe; Marescaux, Jacques

    2016-05-01

    The use of augmented reality in minimally invasive surgery has been the subject of much research for more than a decade. The endoscopic view of the surgical scene is typically augmented with a 3D model extracted from a preoperative acquisition. However, the organs of interest often present major changes in shape and location because of the pneumoperitoneum and patient displacement. There have been numerous attempts to compensate for this distortion between the pre- and intraoperative states. Some have attempted to recover the visible surface of the organ through image analysis and register it to the preoperative data, but this has proven insufficiently robust and may be problematic with large organs. A second approach is to introduce an intraoperative 3D imaging system as a transition. Hybrid operating rooms are becoming more and more popular, so this seems to be a viable solution, but current techniques require yet another external and constraining piece of apparatus such as an optical tracking system to determine the relationship between the intraoperative images and the endoscopic view. In this article, we propose a new approach to automatically register the reconstruction from an intraoperative CT acquisition with the static endoscopic view, by locating the endoscope tip in the volume data. We first describe our method to localize the endoscope orientation in the intraoperative image using standard image processing algorithms. Secondly, we highlight that the axis of the endoscope needs a specific calibration process to ensure proper registration accuracy. In the last section, we present quantitative and qualitative results proving the feasibility and the clinical potential of our approach. PMID:26925804

  1. Extended Gabor approach applied to classification of emphysematous patterns in computed tomography

    PubMed Central

    Escalante-Ramírez, Boris; Cristóbal, Gabriel; Estépar, Raúl San José

    2014-01-01

    Chronic obstructive pulmonary disease (COPD) is a progressive and irreversible lung condition typically related to emphysema. It hinders air from passing through airpaths and causes that alveolar sacs lose their elastic quality. Findings of COPD may be manifested in a variety of computed tomography (CT) studies. Nevertheless, visual assessment of CT images is time-consuming and depends on trained observers. Hence, a reliable computer-aided diagnosis system would be useful to reduce time and inter-evaluator variability. In this paper, we propose a new emphysema classification framework based on complex Gabor filters and local binary patterns. This approach simultaneously encodes global characteristics and local information to describe emphysema morphology in CT images. Kernel Fisher analysis was used to reduce dimensionality and to find the most discriminant nonlinear boundaries among classes. Finally, classification was performed using the k-nearest neighbor classifier. The results have shown the effectiveness of our approach for quantifying lesions due to emphysema and that the combination of descriptors yields to a better classification performance. PMID:24496558

  2. Extended Gabor approach applied to classification of emphysematous patterns in computed tomography.

    PubMed

    Nava, Rodrigo; Escalante-Ramírez, Boris; Cristóbal, Gabriel; Estépar, Raúl San José

    2014-04-01

    Chronic obstructive pulmonary disease (COPD) is a progressive and irreversible lung condition typically related to emphysema. It hinders air from passing through airpaths and causes that alveolar sacs lose their elastic quality. Findings of COPD may be manifested in a variety of computed tomography (CT) studies. Nevertheless, visual assessment of CT images is time-consuming and depends on trained observers. Hence, a reliable computer-aided diagnosis system would be useful to reduce time and inter-evaluator variability. In this paper, we propose a new emphysema classification framework based on complex Gabor filters and local binary patterns. This approach simultaneously encodes global characteristics and local information to describe emphysema morphology in CT images. Kernel Fisher analysis was used to reduce dimensionality and to find the most discriminant nonlinear boundaries among classes. Finally, classification was performed using the k-nearest neighbor classifier. The results have shown the effectiveness of our approach for quantifying lesions due to emphysema and that the combination of descriptors yields to a better classification performance. PMID:24496558

  3. Robust classification for occluded ear via Gabor scale feature-based non-negative sparse representation

    NASA Astrophysics Data System (ADS)

    Zhang, Baoqing; Mu, Zhichun; Li, Chen; Zeng, Hui

    2014-06-01

    The Gabor wavelets have been experimentally verified to be a good approximation to the response of cortical neurons. A new feature extraction approach is investigated for ear recognition by using scale information of Gabor wavelets. The proposed Gabor scale feature conforms to human visual perception of objects from far to near. It can not only avoid too much redundancy in Gabor features but also tends to extract more precise structural information that is robust to image variations. Then, Gabor scale feature-based non-negative sparse representation classification (G-NSRC) is proposed for ear recognition under occlusion. Compared with SRC in which the sparse coding coefficients can be negative, the non-negativity of G-NSRC conforms to the intuitive notion of combing parts to form a whole and therefore is more consistent with the biological modeling of visual data. Additionally, the use of Gabor scale features increases the discriminative power of G-NSRC. Finally, the proposed classification paradigm is applied to occluded ear recognition. Experimental results demonstrate the effectiveness of our proposed algorithm. Especially when the ear is occluded, the proposed algorithm exhibits great robustness and achieves state-of-the-art recognition performance.

  4. Automatically designing an image processing pipeline for a five-band camera prototype using the local, linear, learned (L3) method

    NASA Astrophysics Data System (ADS)

    Tian, Qiyuan; Blasinski, Henryk; Lansel, Steven; Jiang, Haomiao; Fukunishi, Munenori; Farrell, Joyce E.; Wandell, Brian A.

    2015-02-01

    The development of an image processing pipeline for each new camera design can be time-consuming. To speed camera development, we developed a method named L3 (Local, Linear, Learned) that automatically creates an image processing pipeline for any design. In this paper, we describe how we used the L3 method to design and implement an image processing pipeline for a prototype camera with five color channels. The process includes calibrating and simulating the prototype, learning local linear transforms and accelerating the pipeline using graphics processing units (GPUs).

  5. A comparison of feature extraction methods for Sentinel-1 images: Gabor and Weber transforms

    NASA Astrophysics Data System (ADS)

    Stan, Mihaela; Popescu, Anca; Stoichescu, Dan Alexandru

    2015-10-01

    The purpose of this paper is to compare the performance of two feature extraction methods when applied on high resolution Synthetic Aperture Radar (SAR) images acquired with the new ESA mission SENTINEL-1 (S-1). The feature extraction methods were previously tested on high and very high resolution SAR data (imaged by TerraSAR-X) and had a good performance in discriminating between a relevant numbers of land cover classes (tens of classes). Based on the available spatial resolution (10x10m) of S-1 Interferometric Wide (IW) Ground Range Detected (GRD) images the number of detectable classes is much lower. Moreover, the overall heterogeneity of the images is much lower as compared to the high resolution data, the number of observable details is smaller, and this favors the choice of a smaller window size for the analysis: between 10 and 50 pixels in range and azimuth. The size of the analysis window ensures the consistency with the previous results reported in the literature in very high resolution data (as the size on the ground is comparable and thus the number of contributing objects in the window is similar). The performance of Gabor filters and the Weber Local Descriptor (WLD) was investigated in a twofold approach: first the descriptors were computed directly over the IW GRD images and secondly on the sub-sampled version of the same data (in order to determine the effect of the speckle correlation on the overall class detection probability).

  6. Band-Reweighed Gabor Kernel Embedding for Face Image Representation and Recognition.

    PubMed

    Ren, Chuan-Xian; Dai, Dao-Qing; Li, Xiao-Xin; Lai, Zhao-Rong

    2014-02-01

    Face recognition with illumination or pose variation is a challenging problem in image processing and pattern recognition. A novel algorithm using band-reweighed Gabor kernel embedding to deal with the problem is proposed in this paper. For a given image, it is first transformed by a group of Gabor filters, which output Gabor features using different orientation and scale parameters. Fisher scoring function is used to measure the importance of features in each band, and then, the features with the largest scores are preserved for saving memory requirements. The reduced bands are combined by a vector, which is determined by a weighted kernel discriminant criterion and solved by a constrained quadratic programming method, and then, the weighted sum of these nonlinear bands is defined as the similarity between two images. Compared with existing concatenation-based Gabor feature representation and the uniformly weighted similarity calculation approaches, our method provides a new way to use Gabor features for face recognition and presents a reasonable interpretation for highlighting discriminant orientations and scales. The minimum Mahalanobis distance considering the spatial correlations within the data is exploited for feature matching, and the graphical lasso is used therein for directly estimating the sparse inverse covariance matrix. Experiments using benchmark databases show that our new algorithm improves the recognition results and obtains competitive performance. PMID:26270914

  7. Automatic anatomy partitioning of the torso region on CT images by using multiple organ localizations with a group-wise calibration technique

    NASA Astrophysics Data System (ADS)

    Zhou, Xiangrong; Morita, Syoichi; Zhou, Xinxin; Chen, Huayue; Hara, Takeshi; Yokoyama, Ryujiro; Kanematsu, Masayuki; Hoshi, Hiroaki; Fujita, Hiroshi

    2015-03-01

    This paper describes an automatic approach for anatomy partitioning on three-dimensional (3D) computedtomography (CT) images that divide the human torso into several volume-of-interesting (VOI) images based on anatomical definition. The proposed approach combines several individual detections of organ-location with a groupwise organ-location calibration and correction to achieve an automatic and robust multiple-organ localization task. The essence of the proposed method is to jointly detect the 3D minimum bounding box for each type of organ shown on CT images based on intra-organ-image-textures and inter-organ-spatial-relationship in the anatomy. Machine-learning-based template matching and generalized Hough transform-based point-distribution estimation are used in the detection and calibration processes. We apply this approach to the automatic partitioning of a torso region on CT images, which are divided into 35 VOIs presenting major organ regions and tissues required by routine diagnosis in clinical medicine. A database containing 4,300 patient cases of high-resolution 3D torso CT images is used for training and performance evaluations. We confirmed that the proposed method was successful in target organ localization on more than 95% of CT cases. Only two organs (gallbladder and pancreas) showed a lower success rate: 71 and 78% respectively. In addition, we applied this approach to another database that included 287 patient cases of whole-body CT images scanned for positron emission tomography (PET) studies and used for additional performance evaluation. The experimental results showed that no significant difference between the anatomy partitioning results from those two databases except regarding the spleen. All experimental results showed that the proposed approach was efficient and useful in accomplishing localization tasks for major organs and tissues on CT images scanned using different protocols.

  8. A universal approach for automatic organ segmentations on 3D CT images based on organ localization and 3D GrabCut

    NASA Astrophysics Data System (ADS)

    Zhou, Xiangrong; Ito, Takaaki; Zhou, Xinxin; Chen, Huayue; Hara, Takeshi; Yokoyama, Ryujiro; Kanematsu, Masayuki; Hoshi, Hiroaki; Fujita, Hiroshi

    2014-03-01

    This paper describes a universal approach to automatic segmentation of different internal organ and tissue regions in three-dimensional (3D) computerized tomography (CT) scans. The proposed approach combines object localization, a probabilistic atlas, and 3D GrabCut techniques to achieve automatic and quick segmentation. The proposed method first detects a tight 3D bounding box that contains the target organ region in CT images and then estimates the prior of each pixel inside the bounding box belonging to the organ region or background based on a dynamically generated probabilistic atlas. Finally, the target organ region is separated from the background by using an improved 3D GrabCut algorithm. A machine-learning method is used to train a detector to localize the 3D bounding box of the target organ using template matching on a selected feature space. A content-based image retrieval method is used for online generation of a patient-specific probabilistic atlas for the target organ based on a database. A 3D GrabCut algorithm is used for final organ segmentation by iteratively estimating the CT number distributions of the target organ and backgrounds using a graph-cuts algorithm. We applied this approach to localize and segment twelve major organ and tissue regions independently based on a database that includes 1300 torso CT scans. In our experiments, we randomly selected numerous CT scans and manually input nine principal types of inner organ regions for performance evaluation. Preliminary results showed the feasibility and efficiency of the proposed approach for addressing automatic organ segmentation issues on CT images.

  9. Automatic localization of the left ventricle from cardiac cine magnetic resonance imaging: a new spectrum-based computer-aided tool.

    PubMed

    Zhong, Liang; Zhang, Jun-Mei; Zhao, Xiaodan; Tan, Ru San; Wan, Min

    2014-01-01

    Traditionally, cardiac image analysis is done manually. Automatic image processing can help with the repetitive tasks, and also deal with huge amounts of data, a task which would be humanly tedious. This study aims to develop a spectrum-based computer-aided tool to locate the left ventricle using images obtained via cardiac magnetic resonance imaging. Discrete Fourier Transform was conducted pixelwise on the image sequence. Harmonic images of all frequencies were analyzed visually and quantitatively to determine different patterns of the left and right ventricles on spectrum. The first and fifth harmonic images were selected to perform an anisotropic weighted circle Hough detection. This tool was then tested in ten volunteers. Our tool was able to locate the left ventricle in all cases and had a significantly higher cropping ratio of 0.165 than did earlier studies. In conclusion, a new spectrum-based computer aided tool has been proposed and developed for automatic left ventricle localization. The development of this technique, which will enable the automatic location and further segmentation of the left ventricle, will have a significant impact in research and in diagnostic settings. We envisage that this automated method could be used by radiographers and cardiologists to diagnose and assess ventricular function in patients with diverse heart diseases. PMID:24722328

  10. A Kernel Gabor-Based Weighted Region Covariance Matrix for Face Recognition

    PubMed Central

    Qin, Huafeng; Qin, Lan; Xue, Lian; Li, Yantao

    2012-01-01

    This paper proposes a novel image region descriptor for face recognition, named kernel Gabor-based weighted region covariance matrix (KGWRCM). As different parts are different effectual in characterizing and recognizing faces, we construct a weighting matrix by computing the similarity of each pixel within a face sample to emphasize features. We then incorporate the weighting matrices into a region covariance matrix, named weighted region covariance matrix (WRCM), to obtain the discriminative features of faces for recognition. Finally, to further preserve discriminative features in higher dimensional space, we develop the kernel Gabor-based weighted region covariance matrix (KGWRCM). Experimental results show that the KGWRCM outperforms other algorithms including the kernel Gabor-based region covariance matrix (KGCRM). PMID:22969351

  11. Gabor transforms on the sphere with applications to CMB power spectrum estimation

    NASA Astrophysics Data System (ADS)

    Hansen, Frode K.; Górski, Krzysztof M.; Hivon, Eric

    2002-11-01

    The Fourier transform of a data set apodized with a window function is known as the Gabor transform. In this paper we extend the Gabor transform formalism to the sphere with the intention of applying it to cosmic microwave background (CMB) data analysis. The Gabor coefficients on the sphere known as the pseudo power spectrum is studied for windows of different size. By assuming that the pseudo power spectrum coefficients are Gaussian distributed, we formulate a likelihood ansatz using these as input parameters to estimate the full-sky power spectrum from a patch on the sky. As this likelihood can be calculated quickly without having to invert huge matrices, this allows for fast power spectrum estimation. By using the pseudo power spectrum from several patches on the sky together, the full-sky power spectrum can be estimated from full-sky or nearly full-sky observations.

  12. A kernel Gabor-based weighted region covariance matrix for face recognition.

    PubMed

    Qin, Huafeng; Qin, Lan; Xue, Lian; Li, Yantao

    2012-01-01

    This paper proposes a novel image region descriptor for face recognition, named kernel Gabor-based weighted region covariance matrix (KGWRCM). As different parts are different effectual in characterizing and recognizing faces, we construct a weighting matrix by computing the similarity of each pixel within a face sample to emphasize features. We then incorporate the weighting matrices into a region covariance matrix, named weighted region covariance matrix (WRCM), to obtain the discriminative features of faces for recognition. Finally, to further preserve discriminative features in higher dimensional space, we develop the kernel Gabor-based weighted region covariance matrix (KGWRCM). Experimental results show that the KGWRCM outperforms other algorithms including the kernel Gabor-based region covariance matrix (KGCRM). PMID:22969351

  13. Fast residential area extraction from remote sensing image based on Log-Gabor filter

    NASA Astrophysics Data System (ADS)

    Xiao, Jie; Cai, Chao

    2011-11-01

    Monitoring urbanization may help government agencies and urban region planners in updating land maps and forming long-term plans accordingly. In this paper, a novel method for fast extracting residential area from remote sensing images based on log-Gabor filter was proposed. The method is divided in three steps. Firstly, we detect the edge-oriented urban characteristics in a remote sensing image using log-Gabor filter. Secondly, with the filtering orientations perpendicular to each other, we choose two log-Gabor filter response images to suppress the noise and acquire a smooth spatial region. Thirdly, a set of smooth regions served as residential areas can be extracted using Otsu's method. We tested it on diverse aerial and satellite images and encouraging results were acquired. The comparison of our method with the classical texture analyzing method of co-occurrence matrix demonstrated its superiority.

  14. Phase-space analysis for ionization processes in the laser-atom interaction using Gabor transformation

    NASA Astrophysics Data System (ADS)

    Shu, X. F.; Liu, S. B.; Song, H. Y.

    2016-04-01

    In this paper, the ionization processes during laser-atom interaction are investigated in phase-space using Gabor transformation. Based on the time-dependent Schrödinger equation (TDSE), the depletion of the whole system caused by the mask function is taken into consideration in calculating the plasma density. We obtain the momentum distribution via the Gabor transformation of the escaping portions of the time-dependent wave packet at the detector-like points on the interior boundaries from which the kinetic energies carried by the escaping portions are calculated.

  15. Accurate and Fully Automatic Hippocampus Segmentation Using Subject-Specific 3D Optimal Local Maps Into a Hybrid Active Contour Model.

    PubMed

    Zarpalas, Dimitrios; Gkontra, Polyxeni; Daras, Petros; Maglaveras, Nicos

    2014-01-01

    Assessing the structural integrity of the hippocampus (HC) is an essential step toward prevention, diagnosis, and follow-up of various brain disorders due to the implication of the structural changes of the HC in those disorders. In this respect, the development of automatic segmentation methods that can accurately, reliably, and reproducibly segment the HC has attracted considerable attention over the past decades. This paper presents an innovative 3-D fully automatic method to be used on top of the multiatlas concept for the HC segmentation. The method is based on a subject-specific set of 3-D optimal local maps (OLMs) that locally control the influence of each energy term of a hybrid active contour model (ACM). The complete set of the OLMs for a set of training images is defined simultaneously via an optimization scheme. At the same time, the optimal ACM parameters are also calculated. Therefore, heuristic parameter fine-tuning is not required. Training OLMs are subsequently combined, by applying an extended multiatlas concept, to produce the OLMs that are anatomically more suitable to the test image. The proposed algorithm was tested on three different and publicly available data sets. Its accuracy was compared with that of state-of-the-art methods demonstrating the efficacy and robustness of the proposed method. PMID:27170866

  16. Accurate and Fully Automatic Hippocampus Segmentation Using Subject-Specific 3D Optimal Local Maps Into a Hybrid Active Contour Model

    PubMed Central

    Gkontra, Polyxeni; Daras, Petros; Maglaveras, Nicos

    2014-01-01

    Assessing the structural integrity of the hippocampus (HC) is an essential step toward prevention, diagnosis, and follow-up of various brain disorders due to the implication of the structural changes of the HC in those disorders. In this respect, the development of automatic segmentation methods that can accurately, reliably, and reproducibly segment the HC has attracted considerable attention over the past decades. This paper presents an innovative 3-D fully automatic method to be used on top of the multiatlas concept for the HC segmentation. The method is based on a subject-specific set of 3-D optimal local maps (OLMs) that locally control the influence of each energy term of a hybrid active contour model (ACM). The complete set of the OLMs for a set of training images is defined simultaneously via an optimization scheme. At the same time, the optimal ACM parameters are also calculated. Therefore, heuristic parameter fine-tuning is not required. Training OLMs are subsequently combined, by applying an extended multiatlas concept, to produce the OLMs that are anatomically more suitable to the test image. The proposed algorithm was tested on three different and publicly available data sets. Its accuracy was compared with that of state-of-the-art methods demonstrating the efficacy and robustness of the proposed method. PMID:27170866

  17. Automated Protein Localization of Blood Brain Barrier Vasculature in Brightfield IHC Images.

    PubMed

    Soans, Rajath E; Lim, Diane C; Keenan, Brendan T; Pack, Allan I; Shackleford, James A

    2016-01-01

    In this paper, we present an objective method for localization of proteins in blood brain barrier (BBB) vasculature using standard immunohistochemistry (IHC) techniques and bright-field microscopy. Images from the hippocampal region at the BBB are acquired using bright-field microscopy and subjected to our segmentation pipeline which is designed to automatically identify and segment microvessels containing the protein glucose transporter 1 (GLUT1). Gabor filtering and k-means clustering are employed to isolate potential vascular structures within cryosectioned slabs of the hippocampus, which are subsequently subjected to feature extraction followed by classification via decision forest. The false positive rate (FPR) of microvessel classification is characterized using synthetic and non-synthetic IHC image data for image entropies ranging between 3 and 8 bits. The average FPR for synthetic and non-synthetic IHC image data was found to be 5.48% and 5.04%, respectively. PMID:26828723

  18. Automated Protein Localization of Blood Brain Barrier Vasculature in Brightfield IHC Images

    PubMed Central

    Keenan, Brendan T.; Pack, Allan I.; Shackleford, James A.

    2016-01-01

    In this paper, we present an objective method for localization of proteins in blood brain barrier (BBB) vasculature using standard immunohistochemistry (IHC) techniques and bright-field microscopy. Images from the hippocampal region at the BBB are acquired using bright-field microscopy and subjected to our segmentation pipeline which is designed to automatically identify and segment microvessels containing the protein glucose transporter 1 (GLUT1). Gabor filtering and k-means clustering are employed to isolate potential vascular structures within cryosectioned slabs of the hippocampus, which are subsequently subjected to feature extraction followed by classification via decision forest. The false positive rate (FPR) of microvessel classification is characterized using synthetic and non-synthetic IHC image data for image entropies ranging between 3 and 8 bits. The average FPR for synthetic and non-synthetic IHC image data was found to be 5.48% and 5.04%, respectively. PMID:26828723

  19. Improving the resolution in phase-shifting Gabor holography by CCD shift

    NASA Astrophysics Data System (ADS)

    Granero, L.; Micó, V.; Zalevsky, Z.; García, J.; Javidi, B.

    2015-05-01

    Holography dates back to the year when Dennis Gabor reported on a method to avoid spherical aberration and to improve image quality in electron microscopy. Gabor's two-step holographic method was pioneer but suffered from three major drawbacks: the reconstructed image is affected by coherent noise, the twin image problem of holography that also affects the final image quality, and a restricted sample range (weak diffraction assumption) for preserving the holographic behavior of the method. Nowadays, most of those drawbacks have been overcome and new capabilities have been added due to the replacement of the classical recording media (photographic plate) by digital sensors (CCD and CMOS cameras). But in the Gabor' regime, holography is restricted to weak diffraction assumptions because otherwise, diffraction prevents an accurate recovery of the object's complex wavefront. In this contribution, we present an experimental approach to overcome such limitation and improve final image resolution. We use the phase-shifting Gabor configuration while the CCD camera is shifted to different off-axis positions in order to capture a bigger portion of the diffracted wavefront. Thus, once the whole image set is recorded and digitally processed for each camera's position, we merge the resulting band-pass images into one image by assembling a synthetic aperture. Finally, a superresolved image is recovered by Fourier transformation of the information contained in the generated synthetic aperture. Experimental results are provided using a USAF resolution test target and validating our concepts for a gain in resolution of close to 2.

  20. A texture classification method for diffused liver diseases using Gabor wavelets.

    PubMed

    Ahmadian, A; Mostafa, A; Abolhassani, M; Salimpour, Y

    2005-01-01

    We proposed an efficient method for classification of diffused liver diseases based on Gabor wavelet. It is well known that Gabor wavelets attain maximum joint space-frequency resolution which is highly significant in the process of texture extraction and presentation. This property has been explored here as the proposed method outperforms the classification rate obtained by using dyadic wavelets and methods based on statistical properties of textures. The feature vector is relatively small compared to other methods. This has a significant impact on the speed of retrieval process. In addition, the proposed algorithm is not sensitive to shift of the image contents. Since shifting the contents of an image will cause a circular shift of the Gabor filter coefficients in each sub-band. The proposed algorithm applied to discriminate ultrasonic liver images into three disease states that are normal liver, liver hepatitis and cirrhosis. In our experiment 45 liver sample images from each three disease states which already proven by needle biopsy were used. We achieved the sensitivity 85% in the distinction between normal and hepatitis liver images and 86% in the distinction between normal and cirrhosis liver images. Based on our experiments, the Gabor wavelet is more appropriate than dyadic wavelets and statistical based methods for texture classification as it leads to higher classification accuracy. PMID:17282503

  1. Gait recognition based on Gabor wavelets and modified gait energy image for human identification

    NASA Astrophysics Data System (ADS)

    Huang, Deng-Yuan; Lin, Ta-Wei; Hu, Wu-Chih; Cheng, Chih-Hsiang

    2013-10-01

    This paper proposes a method for recognizing human identity using gait features based on Gabor wavelets and modified gait energy images (GEIs). Identity recognition by gait generally involves gait representation, extraction, and classification. In this work, a modified GEI convolved with an ensemble of Gabor wavelets is proposed as a gait feature. Principal component analysis is then used to project the Gabor-wavelet-based gait features into a lower-dimension feature space for subsequent classification. Finally, support vector machine classifiers based on a radial basis function kernel are trained and utilized to recognize human identity. The major contributions of this paper are as follows: (1) the consideration of the shadow effect to yield a more complete segmentation of gait silhouettes; (2) the utilization of motion estimation to track people when walkers overlap; and (3) the derivation of modified GEIs to extract more useful gait information. Extensive performance evaluation shows a great improvement of recognition accuracy due to the use of shadow removal, motion estimation, and gait representation using the modified GEIs and Gabor wavelets.

  2. Detection of vertebral plateaus in lateral lumbar spinal X-ray images with Gabor filters.

    PubMed

    Alvarez Ribeiro, Eduardo; Nogueira-Barbosa, Marcello Henrique; Rangayyan, Rangaraj M; Azevedo-Marques, Paulo M

    2010-01-01

    A few recent studies have proposed computed-aided methods for the detection and analysis of vertebral bodies in radiographic images. This paper presents a method based on Gabor filters. Forty-one lateral lumbar spinal X-ray images from different patients were included in the study. For each image, a radiologist manually delineated the vertebral plateaus of L1, L2, L3, and L4 using a software tool for image display and mark-up. Each original image was filtered with a bank of 180 Gabor filters. The angle of the Gabor filter with the highest response at each pixel was used to derive a measure of the strength of orientation or alignment. In order to limit the spatial extent of the image data and the derived features in further analysis, a semi-automated procedure was applied to the original image. A neural network utilizing the logistic sigmoid function was trained with pixel intensity from the original image, the result of manual delineation of the plateaus, the Gabor magnitude response, and the alignment image. The average overlap between the results of detection by image processing and manual delineation of the plateaus of L1-L4 in the 41 images tested was 0.917. The results are expected to be useful in the analysis of vertebral deformities and fractures. PMID:21097095

  3. Automatic 3D segmentation of ultrasound images using atlas registration and statistical texture prior

    NASA Astrophysics Data System (ADS)

    Yang, Xiaofeng; Schuster, David; Master, Viraj; Nieh, Peter; Fenster, Aaron; Fei, Baowei

    2011-03-01

    We are developing a molecular image-directed, 3D ultrasound-guided, targeted biopsy system for improved detection of prostate cancer. In this paper, we propose an automatic 3D segmentation method for transrectal ultrasound (TRUS) images, which is based on multi-atlas registration and statistical texture prior. The atlas database includes registered TRUS images from previous patients and their segmented prostate surfaces. Three orthogonal Gabor filter banks are used to extract texture features from each image in the database. Patient-specific Gabor features from the atlas database are used to train kernel support vector machines (KSVMs) and then to segment the prostate image from a new patient. The segmentation method was tested in TRUS data from 5 patients. The average surface distance between our method and manual segmentation is 1.61 +/- 0.35 mm, indicating that the atlas-based automatic segmentation method works well and could be used for 3D ultrasound-guided prostate biopsy.

  4. Automatic localization of vertebral levels in x-ray fluoroscopy using 3D-2D registration: a tool to reduce wrong-site surgery

    NASA Astrophysics Data System (ADS)

    Otake, Y.; Schafer, S.; Stayman, J. W.; Zbijewski, W.; Kleinszig, G.; Graumann, R.; Khanna, A. J.; Siewerdsen, J. H.

    2012-09-01

    Surgical targeting of the incorrect vertebral level (wrong-level surgery) is among the more common wrong-site surgical errors, attributed primarily to the lack of uniquely identifiable radiographic landmarks in the mid-thoracic spine. The conventional localization method involves manual counting of vertebral bodies under fluoroscopy, is prone to human error and carries additional time and dose. We propose an image registration and visualization system (referred to as LevelCheck), for decision support in spine surgery by automatically labeling vertebral levels in fluoroscopy using a GPU-accelerated, intensity-based 3D-2D (namely CT-to-fluoroscopy) registration. A gradient information (GI) similarity metric and a CMA-ES optimizer were chosen due to their robustness and inherent suitability for parallelization. Simulation studies involved ten patient CT datasets from which 50 000 simulated fluoroscopic images were generated from C-arm poses selected to approximate the C-arm operator and positioning variability. Physical experiments used an anthropomorphic chest phantom imaged under real fluoroscopy. The registration accuracy was evaluated as the mean projection distance (mPD) between the estimated and true center of vertebral levels. Trials were defined as successful if the estimated position was within the projection of the vertebral body (namely mPD <5 mm). Simulation studies showed a success rate of 99.998% (1 failure in 50 000 trials) and computation time of 4.7 s on a midrange GPU. Analysis of failure modes identified cases of false local optima in the search space arising from longitudinal periodicity in vertebral structures. Physical experiments demonstrated the robustness of the algorithm against quantum noise and x-ray scatter. The ability to automatically localize target anatomy in fluoroscopy in near-real-time could be valuable in reducing the occurrence of wrong-site surgery while helping to reduce radiation exposure. The method is applicable beyond

  5. Human gait recognition using patch distribution feature and locality-constrained group sparse representation.

    PubMed

    Xu, Dong; Huang, Yi; Zeng, Zinan; Xu, Xinxing

    2012-01-01

    In this paper, we propose a new patch distribution feature (PDF) (i.e., referred to as Gabor-PDF) for human gait recognition. We represent each gait energy image (GEI) as a set of local augmented Gabor features, which concatenate the Gabor features extracted from different scales and different orientations together with the X-Y coordinates. We learn a global Gaussian mixture model (GMM) (i.e., referred to as the universal background model) with the local augmented Gabor features from all the gallery GEIs; then, each gallery or probe GEI is further expressed as the normalized parameters of an image-specific GMM adapted from the global GMM. Observing that one video is naturally represented as a group of GEIs, we also propose a new classification method called locality-constrained group sparse representation (LGSR) to classify each probe video by minimizing the weighted l(1, 2) mixed-norm-regularized reconstruction error with respect to the gallery videos. In contrast to the standard group sparse representation method that is a special case of LGSR, the group sparsity and local smooth sparsity constraints are both enforced in LGSR. Our comprehensive experiments on the benchmark USF HumanID database demonstrate the effectiveness of the newly proposed feature Gabor-PDF and the new classification method LGSR for human gait recognition. Moreover, LGSR using the new feature Gabor-PDF achieves the best average Rank-1 and Rank-5 recognition rates on this database among all gait recognition algorithms proposed to date. PMID:21724511

  6. Automatic Imitation

    ERIC Educational Resources Information Center

    Heyes, Cecilia

    2011-01-01

    "Automatic imitation" is a type of stimulus-response compatibility effect in which the topographical features of task-irrelevant action stimuli facilitate similar, and interfere with dissimilar, responses. This article reviews behavioral, neurophysiological, and neuroimaging research on automatic imitation, asking in what sense it is "automatic"…

  7. A comparison of texture models for automatic liver segmentation

    NASA Astrophysics Data System (ADS)

    Pham, Mailan; Susomboon, Ruchaneewan; Disney, Tim; Raicu, Daniela; Furst, Jacob

    2007-03-01

    Automatic liver segmentation from abdominal computed tomography (CT) images based on gray levels or shape alone is difficult because of the overlap in gray-level ranges and the variation in position and shape of the soft tissues. To address these issues, we propose an automatic liver segmentation method that utilizes low-level features based on texture information; this texture information is expected to be homogenous and consistent across multiple slices for the same organ. Our proposed approach consists of the following steps: first, we perform pixel-level texture extraction; second, we generate liver probability images using a binary classification approach; third, we apply a split-and-merge algorithm to detect the seed set with the highest probability area; and fourth, we apply to the seed set a region growing algorithm iteratively to refine the liver's boundary and get the final segmentation results. Furthermore, we compare the segmentation results from three different texture extraction methods (Co-occurrence Matrices, Gabor filters, and Markov Random Fields (MRF)) to find the texture method that generates the best liver segmentation. From our experimental results, we found that the co-occurrence model led to the best segmentation, while the Gabor model led to the worst liver segmentation. Moreover, co-occurrence texture features alone produced approximately the same segmentation results as those produced when all the texture features from the combined co-occurrence, Gabor, and MRF models were used. Therefore, in addition to providing an automatic model for liver segmentation, we also conclude that Haralick cooccurrence texture features are the most significant texture characteristics in distinguishing the liver tissue in CT scans.

  8. Automated 3D Motion Tracking using Gabor Filter Bank, Robust Point Matching, and Deformable Models

    PubMed Central

    Wang, Xiaoxu; Chung, Sohae; Metaxas, Dimitris; Axel, Leon

    2013-01-01

    Tagged Magnetic Resonance Imaging (tagged MRI or tMRI) provides a means of directly and noninvasively displaying the internal motion of the myocardium. Reconstruction of the motion field is needed to quantify important clinical information, e.g., the myocardial strain, and detect regional heart functional loss. In this paper, we present a three-step method for this task. First, we use a Gabor filter bank to detect and locate tag intersections in the image frames, based on local phase analysis. Next, we use an improved version of the Robust Point Matching (RPM) method to sparsely track the motion of the myocardium, by establishing a transformation function and a one-to-one correspondence between grid tag intersections in different image frames. In particular, the RPM helps to minimize the impact on the motion tracking result of: 1) through-plane motion, and 2) relatively large deformation and/or relatively small tag spacing. In the final step, a meshless deformable model is initialized using the transformation function computed by RPM. The model refines the motion tracking and generates a dense displacement map, by deforming under the influence of image information, and is constrained by the displacement magnitude to retain its geometric structure. The 2D displacement maps in short and long axis image planes can be combined to drive a 3D deformable model, using the Moving Least Square method, constrained by the minimization of the residual error at tag intersections. The method has been tested on a numerical phantom, as well as on in vivo heart data from normal volunteers and heart disease patients. The experimental results show that the new method has a good performance on both synthetic and real data. Furthermore, the method has been used in an initial clinical study to assess the differences in myocardial strain distributions between heart disease (left ventricular hypertrophy) patients and the normal control group. The final results show that the proposed method

  9. Discretization of the Gabor-type scheme by sampling of the Zak transform

    NASA Astrophysics Data System (ADS)

    Zibulski, Meir; Zeevi, Yehoshua Y.

    1994-09-01

    The matrix algebra approach was previously applied in the analysis of the continuous Gabor representation in the Zak transform domain. In this study we analyze the discrete and finite (periodic) scheme by the same approach. A direct relation that exists between the two schemes, based on the sampling of the Zak transform, is established. Specifically, we show that sampling of the Gabor expansion in the Zak transform domain yields a discrete scheme of representation. Such a derivation yields a simple relation between the schemes by means of the periodic extension of the signal. We show that in the discrete Zak domain the frame operator can be expressed by means of a matrix-valued function which is simply the sampled version of the matrix-valued function of the continuous scheme. This result establishes a direct relation between the frame properties of the two schemes.

  10. Face recognition via edge-based Gabor feature representation for plastic surgery-altered images

    NASA Astrophysics Data System (ADS)

    Chude-Olisah, Chollette C.; Sulong, Ghazali; Chude-Okonkwo, Uche A. K.; Hashim, Siti Z. M.

    2014-12-01

    Plastic surgery procedures on the face introduce skin texture variations between images of the same person (intra-subject), thereby making the task of face recognition more difficult than in normal scenario. Usually, in contemporary face recognition systems, the original gray-level face image is used as input to the Gabor descriptor, which translates to encoding some texture properties of the face image. The texture-encoding process significantly degrades the performance of such systems in the case of plastic surgery due to the presence of surgically induced intra-subject variations. Based on the proposition that the shape of significant facial components such as eyes, nose, eyebrow, and mouth remains unchanged after plastic surgery, this paper employs an edge-based Gabor feature representation approach for the recognition of surgically altered face images. We use the edge information, which is dependent on the shapes of the significant facial components, to address the plastic surgery-induced texture variation problems. To ensure that the significant facial components represent useful edge information with little or no false edges, a simple illumination normalization technique is proposed for preprocessing. Gabor wavelet is applied to the edge image to accentuate on the uniqueness of the significant facial components for discriminating among different subjects. The performance of the proposed method is evaluated on the Georgia Tech (GT) and the Labeled Faces in the Wild (LFW) databases with illumination and expression problems, and the plastic surgery database with texture changes. Results show that the proposed edge-based Gabor feature representation approach is robust against plastic surgery-induced face variations amidst expression and illumination problems and outperforms the existing plastic surgery face recognition methods reported in the literature.

  11. Dual side transparent OLED 3D display using Gabor super-lens

    NASA Astrophysics Data System (ADS)

    Chestak, Sergey; Kim, Dae-Sik; Cho, Sung-Woo

    2015-03-01

    We devised dual side transparent 3D display using transparent OLED panel and two lenticular arrays. The OLED panel is sandwiched between two parallel confocal lenticular arrays, forming Gabor super-lens. The display provides dual side stereoscopic 3D imaging and floating image of the object, placed behind it. The floating image can be superimposed with the displayed 3D image. The displayed autostereoscopic 3D images are composed of 4 views, each with resolution 64x90 pix.

  12. Automatic abdominal lymph node detection method based on local intensity structure analysis from 3D x-ray CT images

    NASA Astrophysics Data System (ADS)

    Nakamura, Yoshihiko; Nimura, Yukitaka; Kitasaka, Takayuki; Mizuno, Shinji; Furukawa, Kazuhiro; Goto, Hidemi; Fujiwara, Michitaka; Misawa, Kazunari; Ito, Masaaki; Nawano, Shigeru; Mori, Kensaku

    2013-03-01

    This paper presents an automated method of abdominal lymph node detection to aid the preoperative diagnosis of abdominal cancer surgery. In abdominal cancer surgery, surgeons must resect not only tumors and metastases but also lymph nodes that might have a metastasis. This procedure is called lymphadenectomy or lymph node dissection. Insufficient lymphadenectomy carries a high risk for relapse. However, excessive resection decreases a patient's quality of life. Therefore, it is important to identify the location and the structure of lymph nodes to make a suitable surgical plan. The proposed method consists of candidate lymph node detection and false positive reduction. Candidate lymph nodes are detected using a multi-scale blob-like enhancement filter based on local intensity structure analysis. To reduce false positives, the proposed method uses a classifier based on support vector machine with the texture and shape information. The experimental results reveal that it detects 70.5% of the lymph nodes with 13.0 false positives per case.

  13. Automatic Robust Neurite Detection and Morphological Analysis of Neuronal Cell Cultures in High-content Screening

    PubMed Central

    Wu, Chaohong; Schulte, Joost; Sepp, Katharine J.; Littleton, J. Troy

    2011-01-01

    Cell-based high content screening (HCS) is becoming an important and increasingly favored approach in therapeutic drug discovery and functional genomics. In HCS, changes in cellular morphology and biomarker distributions provide an information-rich profile of cellular responses to experimental treatments such as small molecules or gene knockdown probes. One obstacle that currently exists with such cell-based assays is the availability of image processing algorithms that are capable of reliably and automatically analyzing large HCS image sets. HCS images of primary neuronal cell cultures are particularly challenging to analyze due to complex cellular morphology. Here we present a robust method for quantifying and statistically analyzing the morphology of neuronal cells in HCS images. The major advantages of our method over existing software lie in its capability to correct non-uniform illumination using the contrast-limited adaptive histogram equalization method; segment neuromeres using Gabor-wavelet texture analysis; and detect faint neurites by a novel phase-based neurite extraction algorithm that is invariant to changes in illumination and contrast and can accurately localize neurites. Our method was successfully applied to analyze a large HCS image set generated in a morphology screen for polyglutamine-mediated neuronal toxicity using primary neuronal cell cultures derived from embryos of a Drosophila Huntington’s Disease (HD) model. PMID:20405243

  14. Robust automatic target recognition in FLIR imagery

    NASA Astrophysics Data System (ADS)

    Soyman, Yusuf

    2012-05-01

    In this paper, a robust automatic target recognition algorithm in FLIR imagery is proposed. Target is first segmented out from the background using wavelet transform. Segmentation process is accomplished by parametric Gabor wavelet transformation. Invariant features that belong to the target, which is segmented out from the background, are then extracted via moments. Higher-order moments, while providing better quality for identifying the image, are more sensitive to noise. A trade-off study is then performed on a few moments that provide effective performance. Bayes method is used for classification, using Mahalanobis distance as the Bayes' classifier. Results are assessed based on false alarm rates. The proposed method is shown to be robust against rotations, translations and scale effects. Moreover, it is shown to effectively perform under low-contrast objects in FLIR images. Performance comparisons are also performed on both GPU and CPU. Results indicate that GPU has superior performance over CPU.

  15. Time-Domain Techniques to Automatically Detect Local Earthquakes in the Wavetrain of Large Remote Teleseseismic Events Using Data within the Continental United States

    NASA Astrophysics Data System (ADS)

    Alfaro-Diaz, R. A.; Velasco, A. A.; Kilb, D.; Pankow, K.; Linville, L. M.

    2014-12-01

    Technology advances in combination with the onslaught of data availability now allow for large seismic data streams to automatically and systematically be processed. This processing allows for the detection of unique seismic events, including events triggered by the passage of seismic waves created by large, distant earthquakes. We develop an automated approach to identify small, locally recorded earthquakes on a single station within continuous seismic data. We apply a time domain short-term average (STA) to long-term-average (LTA) ratio algorithm to create a catalog of "detections" (a signal above the noise level, which may, or may not be an earthquake) at each station recorded on three components, and then remove any spurious detections by requiring that a detection is real only if recorded on a minimum of two channels. To calibrate the algorithm, we use a set of ~900 small earthquakes in the December 2008 Yellowstone Swarm. Of the four STA/LTA algorithms we tested (e.g., 1 s/10 s; 4 s/40 s; 8 s/80 s; 16 s/160s), the 4/40s method is the most effective at identifying the majority of events in the swarm. We apply this preferred method to data from 165 M≥7 earthquakes (±5-hours of data centered on the mainshock origin times) recorded at >400 seismic stations in EarthScope's USArray Transportable Array (TA) and regional seismic networks within the continental United States. Our algorithm nets, on average, hundreds of detections for each mainshock, and we find we can detect small events within the network. The 4/40s method is successful at identifying local earthquakes within the TA and regional networks. We find STA/LTA algorithms can successfully identify small local earthquakes within large datasets.

  16. Non-invasive health status detection system using Gabor filters based on facial block texture features.

    PubMed

    Shu, Ting; Zhang, Bob

    2015-04-01

    Blood tests allow doctors to check for certain diseases and conditions. However, using a syringe to extract the blood can be deemed invasive, slightly painful, and its analysis time consuming. In this paper, we propose a new non-invasive system to detect the health status (Healthy or Diseased) of an individual based on facial block texture features extracted using the Gabor filter. Our system first uses a non-invasive capture device to collect facial images. Next, four facial blocks are located on these images to represent them. Afterwards, each facial block is convolved with a Gabor filter bank to calculate its texture value. Classification is finally performed using K-Nearest Neighbor and Support Vector Machines via a Library for Support Vector Machines (with four kernel functions). The system was tested on a dataset consisting of 100 Healthy and 100 Diseased (with 13 forms of illnesses) samples. Experimental results show that the proposed system can detect the health status with an accuracy of 93 %, a sensitivity of 94 %, a specificity of 92 %, using a combination of the Gabor filters and facial blocks. PMID:25722202

  17. Fully automated muscle quality assessment by Gabor filtering of second harmonic generation images

    NASA Astrophysics Data System (ADS)

    Paesen, Rik; Smolders, Sophie; Vega, José Manolo de Hoyos; Eijnde, Bert O.; Hansen, Dominique; Ameloot, Marcel

    2016-02-01

    Although structural changes on the sarcomere level of skeletal muscle are known to occur due to various pathologies, rigorous studies of the reduced sarcomere quality remain scarce. This can possibly be explained by the lack of an objective tool for analyzing and comparing sarcomere images across biological conditions. Recent developments in second harmonic generation (SHG) microscopy and increasing insight into the interpretation of sarcomere SHG intensity profiles have made SHG microscopy a valuable tool to study microstructural properties of sarcomeres. Typically, sarcomere integrity is analyzed by fitting a set of manually selected, one-dimensional SHG intensity profiles with a supramolecular SHG model. To circumvent this tedious manual selection step, we developed a fully automated image analysis procedure to map the sarcomere disorder for the entire image at once. The algorithm relies on a single-frequency wavelet-based Gabor approach and includes a newly developed normalization procedure allowing for unambiguous data interpretation. The method was validated by showing the correlation between the sarcomere disorder, quantified by the M-band size obtained from manually selected profiles, and the normalized Gabor value ranging from 0 to 1 for decreasing disorder. Finally, to elucidate the applicability of our newly developed protocol, Gabor analysis was used to study the effect of experimental autoimmune encephalomyelitis on the sarcomere regularity. We believe that the technique developed in this work holds great promise for high-throughput, unbiased, and automated image analysis to study sarcomere integrity by SHG microscopy.

  18. A Gabor subband decomposition ICA and MRF hybrid algorithm for infrared image reconstruction from subpixel shifted sequences

    NASA Astrophysics Data System (ADS)

    Yi-nan, Chen; Wei-qi, Jin; Ling-Xue, Wang; Lei, Zhao; Hong-sheng, Yu

    2009-03-01

    An image blind reconstruction, as a blind source separation problem, has been solved recently by independent component analysis (ICA). Based on ICA theory, in this paper, a high resolution image is reconstructed from low resolution and subpixel shifted sequences captured by infrared microscan imaging system. The algorithm has the attractive feature that neither the prior knowledge of the blur kernel nor the value of subpixel misregistrations between the input channels is required. The statistical independence in the image domain is improved by the multiscale Gabor subband decompositions, which are designed for the best ability to cover the whole spatial frequency and to avoid overlapping between the subbands. The mutual information is employed to locate a subband with the least dependent components. In terms of MAP estimator, we combine the super-Gaussian with Markov random field to form a hybrid image distribution. This strategy helps to estimate the separating matrix reasonable to extract the sources with the image properties, that is, sharp enough as well as correlative in local area. The proposed algorithm is capable of performing high resolution image sources which are not strictly independent, and its viability is proved by the computer simulations and real experiments.

  19. Automatic detection of informative frames from wireless capsule endoscopy images.

    PubMed

    Bashar, M K; Kitasaka, T; Suenaga, Y; Mekada, Y; Mori, K

    2010-06-01

    Wireless capsule endoscopy (WCE) is a new clinical technology permitting visualization of the small bowel, the most difficult segment of the digestive tract. The major drawback of this technology is the excessive amount of time required for video diagnosis. We therefore propose a method for generating smaller videos by detecting informative frames from original WCE videos. This method isolates useless frames that are highly contaminated by turbid fluids, faecal materials and/or residual foods. These materials and fluids are presented in a wide range of colors, from brown to yellow, and/or have bubble-like texture patterns. The detection scheme therefore consists of two steps: isolating (Step-1) highly contaminated non-bubbled (HCN) frames and (Step-2) significantly bubbled (SB) frames. Two color representations, viz., local color moments in Ohta space and the HSV color histogram, are attempted to characterize HCN frames, which are isolated by a support vector machine (SVM) classifier in Step-1. The rest of the frames go to Step-2, where a Gauss Laguerre transform (GLT) based multiresolution texture feature is used to characterize the bubble structures in WCE frames. GLT uses Laguerre Gauss circular harmonic functions (LG-CHFs) to decompose WCE images into multiresolution components. An automatic method of segmentation was designed to extract bubbled regions from grayscale versions of the color images based on the local absolute energies of their CHF responses. The final informative frames were detected by using a threshold on the segmented regions. An automatic procedure for selecting features based on analyzing the consistency of the energy-contrast map is also proposed. Three experiments, two of which use 14,841 and 37,100 frames from three videos and the rest uses 66,582 frames from six videos, were conducted for justifying the proposed method. The two combinations of the proposed color and texture features showed excellent average detection accuracies (86

  20. Fully Automatic Localization and Segmentation of 3D Vertebral Bodies from CT/MR Images via a Learning-Based Method

    PubMed Central

    Chu, Chengwen; Belavý, Daniel L.; Armbrecht, Gabriele; Bansmann, Martin; Felsenberg, Dieter; Zheng, Guoyan

    2015-01-01

    In this paper, we address the problems of fully automatic localization and segmentation of 3D vertebral bodies from CT/MR images. We propose a learning-based, unified random forest regression and classification framework to tackle these two problems. More specifically, in the first stage, the localization of 3D vertebral bodies is solved with random forest regression where we aggregate the votes from a set of randomly sampled image patches to get a probability map of the center of a target vertebral body in a given image. The resultant probability map is then further regularized by Hidden Markov Model (HMM) to eliminate potential ambiguity caused by the neighboring vertebral bodies. The output from the first stage allows us to define a region of interest (ROI) for the segmentation step, where we use random forest classification to estimate the likelihood of a voxel in the ROI being foreground or background. The estimated likelihood is combined with the prior probability, which is learned from a set of training data, to get the posterior probability of the voxel. The segmentation of the target vertebral body is then done by a binary thresholding of the estimated probability. We evaluated the present approach on two openly available datasets: 1) 3D T2-weighted spine MR images from 23 patients and 2) 3D spine CT images from 10 patients. Taking manual segmentation as the ground truth (each MR image contains at least 7 vertebral bodies from T11 to L5 and each CT image contains 5 vertebral bodies from L1 to L5), we evaluated the present approach with leave-one-out experiments. Specifically, for the T2-weighted MR images, we achieved for localization a mean error of 1.6 mm, and for segmentation a mean Dice metric of 88.7% and a mean surface distance of 1.5 mm, respectively. For the CT images we achieved for localization a mean error of 1.9 mm, and for segmentation a mean Dice metric of 91.0% and a mean surface distance of 0.9 mm, respectively. PMID:26599505

  1. Fully Automatic Localization and Segmentation of 3D Vertebral Bodies from CT/MR Images via a Learning-Based Method.

    PubMed

    Chu, Chengwen; Belavý, Daniel L; Armbrecht, Gabriele; Bansmann, Martin; Felsenberg, Dieter; Zheng, Guoyan

    2015-01-01

    In this paper, we address the problems of fully automatic localization and segmentation of 3D vertebral bodies from CT/MR images. We propose a learning-based, unified random forest regression and classification framework to tackle these two problems. More specifically, in the first stage, the localization of 3D vertebral bodies is solved with random forest regression where we aggregate the votes from a set of randomly sampled image patches to get a probability map of the center of a target vertebral body in a given image. The resultant probability map is then further regularized by Hidden Markov Model (HMM) to eliminate potential ambiguity caused by the neighboring vertebral bodies. The output from the first stage allows us to define a region of interest (ROI) for the segmentation step, where we use random forest classification to estimate the likelihood of a voxel in the ROI being foreground or background. The estimated likelihood is combined with the prior probability, which is learned from a set of training data, to get the posterior probability of the voxel. The segmentation of the target vertebral body is then done by a binary thresholding of the estimated probability. We evaluated the present approach on two openly available datasets: 1) 3D T2-weighted spine MR images from 23 patients and 2) 3D spine CT images from 10 patients. Taking manual segmentation as the ground truth (each MR image contains at least 7 vertebral bodies from T11 to L5 and each CT image contains 5 vertebral bodies from L1 to L5), we evaluated the present approach with leave-one-out experiments. Specifically, for the T2-weighted MR images, we achieved for localization a mean error of 1.6 mm, and for segmentation a mean Dice metric of 88.7% and a mean surface distance of 1.5 mm, respectively. For the CT images we achieved for localization a mean error of 1.9 mm, and for segmentation a mean Dice metric of 91.0% and a mean surface distance of 0.9 mm, respectively. PMID:26599505

  2. 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

  3. Hyperspectral Region Classification Using Three-Dimensional Spectral/Spatial Gabor Filters

    NASA Astrophysics Data System (ADS)

    Bau, Tien Cheng

    A three-dimensional (3D) spectral/spatial DFT can be used to represent a hyperspectral image region using a dense sampling in the frequency domain. In many cases, a more compact frequency-domain representation that preserves the three-dimensional structure of the data can be exploited. For this purpose, we have developed a new model for spectral/spatial information based on 3D Gabor filters. These filters capture specific orientation, scale, and wavelength-dependent properties of hyperspectral image data and provide an efficient means of sampling a three-dimensional frequency-domain representation. Since 3D Gabor filters allow for a large number of spectral/spatial features to be used to represent an image region, the performance and efficiency of algorithms that use this representation can be further improved if methods are available to reduce the size of the model. Thus, we have derived methods for selecting features that emphasize the most significant spectral/spatial differences for a set of classes. In addition, the orientation and scale selective properties of the filters allow the development of new algorithms that are invariant to rotation and scale. The new approach can also adapt to changes in the environmental conditions. The analysis of 3D textures under changing environmental conditions is addressed using an invariant recognition algorithm. The new features are compared against pure spectral features and multiband generalizations of gray-level co-occurrence matrix (GLCM) features using both synthesized and real-world data. We have demonstrated that the 3D Gabor features can be used to improve the classification of hyperspectral regions over using only spectral features.

  4. Design of free-space optical interconnects using two Gabor superlenses

    NASA Astrophysics Data System (ADS)

    Garza-Rivera, Anel; Renero-Carrillo, Francisco-Javier; Trevino-Palacios, Carlos-G.

    2014-09-01

    We propose a novel design of micro-optical devices based on multi-aperture compound insect eyes, which transfer a point-to-point multichannel free space signal combined with a diffraction grating. The system is inspired in the refractive superposition compound eyes configuration known as Gabor superlens (GSL) using microlens arrays. A switching function and wave division multiplexing are achieved by introducing a diffraction grating placed in the global focus of the system. The source characteristics, either coherent or incoherent, influence the device performance.

  5. Gabor-wavelet decomposition and integrated PCA-FLD method for texture based defect classification

    NASA Astrophysics Data System (ADS)

    Cheng, Xuemei; Chen, Yud-Ren; Yang, Tao; Chen, Xin

    2005-11-01

    In many hyperspectral applications, it is desirable to extract the texture features for pattern classification. Texture refers to replications, symmetry of certain patterns. In a set of hyperspectral images, the differences of image textures often imply changes in the physical and chemical properties on or underneath the surface. In this paper, we utilize Gabor wavelet based texture analysis method for textural pattern extraction, and combined with integrated PCA-FLD method for hyperspectral band selection in the application of classifying chilling damaged cucumbers from normal ones. The classification performances are compared and analyzed.

  6. Holonomy, quantum mechanics and the signal-tuned Gabor approach to the striate cortex

    NASA Astrophysics Data System (ADS)

    Torreão, José R. A.

    2016-02-01

    It has been suggested that an appeal to holographic and quantum properties will be ultimately required for the understanding of higher brain functions. On the other hand, successful quantum-like approaches to cognitive and behavioral processes bear witness to the usefulness of quantum prescriptions as applied to the analysis of complex non-quantum systems. Here, we show that the signal-tuned Gabor approach for modeling cortical neurons, although not based on quantum assumptions, also admits a quantum-like interpretation. Recently, the equation of motion for the signal-tuned complex cell response has been derived and proven equivalent to the Schrödinger equation for a dissipative quantum system whose solutions come under two guises: as plane-wave and Airy-packet responses. By interpreting the squared magnitude of the plane-wave solution as a probability density, in accordance with the quantum mechanics prescription, we arrive at a Poisson spiking probability — a common model of neuronal response — while spike propagation can be described by the Airy-packet solution. The signal-tuned approach is also proven consistent with holonomic brain theories, as it is based on Gabor functions which provide a holographic representation of the cell’s input, in the sense that any restricted subset of these functions still allows stimulus reconstruction.

  7. Simple Cell Response Properties Imply Receptive Field Structure: Balanced Gabor and/or Bandlimited Field Functions

    PubMed Central

    Cope, Davis; Blakeslee, Barbara; McCourt, Mark E.

    2011-01-01

    The classical receptive fields of simple cells in mammalian primary visual cortex demonstrate three cardinal response properties: 1) they do not respond to stimuli which are spatially homogeneous; 2) they respond best to stimuli in a preferred orientation (direction); and 3) they do not respond to stimuli in other, non-preferred orientations (directions). We refer to these as the Balanced Field Property, the Maximum Response Direction Property, and the Zero Response Direction Property, respectively. These empirically-determined response properties are used to derive a complete characterization of elementary receptive field functions (of cosine- and mixed-type) defined as products of a circularly symmetric weight function and a simple periodic carrier. Two disjoint classes of elementary receptive field functions result: the balanced Gabor class, a generalization of the traditional Gabor filter, and a bandlimited class whose Fourier transforms have compact support (i.e., are zero-valued outside of a bounded range). The detailed specification of these two classes of receptive field functions from empirically-based postulates may prove useful to neurophysiologists seeking to test alternative theories of simple cell receptive field structure, and to computational neuroscientists seeking basis functions with which to model human vision. PMID:19721693

  8. Bridge recognition based on Gabor filter in forward-looking infrared images

    NASA Astrophysics Data System (ADS)

    Liu, Songlin; Sun, Gang; Niu, Zhaodong; Chen, Zengping

    2013-10-01

    Conventional methods often assume that water region is homogeneous and bridge is brighter than background. They usually recognize target by parallel lines detection. But grayscale of bridge has bipolar problem in FLIR images due to interference of complex background and constraints of imaging conditions, which means that it can be greater or lower than river. Furthermore, water is not a homogeneous area as a whole because of the interference of water clutter and shoals. This paper proposes a novel algorithm of bridge recognition based on Gabor filter. Firstly, we obtain target ROI by extracting the horizontal line. And then ROI sub-images are enhanced by Gabor filter and target polarity is determined by bridge body detection. Finally, bridge recognition can be achieved by pier detection according to the target polarity and location of bridge body. Experimental results of nearly 3000 frames show that the proposed algorithm can effectively overcome problems such as bipolar target and low image contrast. It offers a good practicability and accuracy in bridge recognition in FLIR images.

  9. Automated detection scheme of architectural distortion in mammograms using adaptive Gabor filter

    NASA Astrophysics Data System (ADS)

    Yoshikawa, Ruriha; Teramoto, Atsushi; Matsubara, Tomoko; Fujita, Hiroshi

    2013-03-01

    Breast cancer is a serious health concern for all women. Computer-aided detection for mammography has been used for detecting mass and micro-calcification. However, there are challenges regarding the automated detection of the architectural distortion about the sensitivity. In this study, we propose a novel automated method for detecting architectural distortion. Our method consists of the analysis of the mammary gland structure, detection of the distorted region, and reduction of false positive results. We developed the adaptive Gabor filter for analyzing the mammary gland structure that decides filter parameters depending on the thickness of the gland structure. As for post-processing, healthy mammary glands that run from the nipple to the chest wall are eliminated by angle analysis. Moreover, background mammary glands are removed based on the intensity output image obtained from adaptive Gabor filter. The distorted region of the mammary gland is then detected as an initial candidate using a concentration index followed by binarization and labeling. False positives in the initial candidate are eliminated using 23 types of characteristic features and a support vector machine. In the experiments, we compared the automated detection results with interpretations by a radiologist using 50 cases (200 images) from the Digital Database of Screening Mammography (DDSM). As a result, true positive rate was 82.72%, and the number of false positive per image was 1.39. There results indicate that the proposed method may be useful for detecting architectural distortion in mammograms.

  10. Estimation of the breast skin-line in mammograms using multidirectional Gabor filters.

    PubMed

    Casti, P; Mencattini, A; Salmeri, M; Ancona, A; Mangeri, F; Pepe, M L; Rangayyan, R M

    2013-11-01

    Segmentation of the breast region is a fundamental step in any system for computerized analysis of mammograms. In this work, we propose a novel procedure for the estimation of the breast skin-line based upon multidirectional Gabor filtering. The method includes an adaptive values-of-interest (VOI) transformation, extraction of the skin-air ribbon by Otsu's thresholding method and the Euclidean distance transform, Gabor filtering with 18 real kernels, and a step for suppression of false edge points using the magnitude and phase responses of the filters. On a test set of 361 images from different acquisition modalities (screen-film and full-field digital mammograms), the average Hausdorff and polyline distances obtained were 2.85 mm and 0.84 mm, respectively, with reference to the ground-truth boundaries provided by an expert radiologist. When compared with the results obtained by other state-of-the-art methods on the same set of images and with respect to the same ground-truth boundaries, our method mostly outperformed the other approaches. The results demonstrate the effectiveness and robustness of the proposed algorithm. PMID:24209932

  11. Automatic warranties.

    PubMed

    Decker, R

    1987-10-01

    In addition to express warranties (those specifically made by the supplier in the contract) and implied warranties (those resulting from circumstances of the sale), there is one other classification of warranties that needs to be understood by hospital materials managers. These are sometimes known as automatic warranties. In the following dialogue, Doctor Decker develops these legal concepts. PMID:10284977

  12. Automatic Stabilization

    NASA Technical Reports Server (NTRS)

    Haus, FR

    1936-01-01

    This report lays more stress on the principles underlying automatic piloting than on the means of applications. Mechanical details of servomotors and the mechanical release device necessary to assure instantaneous return of the controls to the pilot in case of malfunction are not included. Descriptions are provided of various commercial systems.

  13. Machine vision: an incremental learning system based on features derived using fast Gabor transforms for the identification of textural objects

    NASA Astrophysics Data System (ADS)

    Clark, Richard M.; Adjei, Osei; Johal, Harpal

    2001-11-01

    This paper proposes a fast, effective and also very adaptable incremental learning system for identifying textures based on features extracted from Gabor space. The Gabor transform is a useful technique for feature extraction since it exhibits properties that are similar to biologically visual sensory systems such as those found in the mammalian visual cortex. Although two-dimensional Gabor filters have been applied successfully to a variety of tasks such as text segmentation, object detection and fingerprint analysis, the work of this paper extends previous work by incorporating incremental learning to facilitate easier training. The proposed system transforms textural images into Gabor space and a non-linear threshold function is then applied to extract feature vectors that bear signatures of the textural images. The mean and variance of each training group is computed followed by a technique that uses the Kohonen network to cluster these features. The centers of these clusters form the basis of an incremental learning paradigm that allows new information to be integrated into the existing knowledge. A number of experiments are conducted for real-time identification or discrimination of textural images.

  14. Automatic carrier acquisition system

    NASA Technical Reports Server (NTRS)

    Bunce, R. C. (Inventor)

    1973-01-01

    An automatic carrier acquisition system for a phase locked loop (PLL) receiver is disclosed. It includes a local oscillator, which sweeps the receiver to tune across the carrier frequency uncertainty range until the carrier crosses the receiver IF reference. Such crossing is detected by an automatic acquisition detector. It receives the IF signal from the receiver as well as the IF reference. It includes a pair of multipliers which multiply the IF signal with the IF reference in phase and in quadrature. The outputs of the multipliers are filtered through bandpass filters and power detected. The output of the power detector has a signal dc component which is optimized with respect to the noise dc level by the selection of the time constants of the filters as a function of the sweep rate of the local oscillator.

  15. AUTOMATIC COUNTER

    DOEpatents

    Robinson, H.P.

    1960-06-01

    An automatic counter of alpha particle tracks recorded by a sensitive emulsion of a photographic plate is described. The counter includes a source of mcdulated dark-field illumination for developing light flashes from the recorded particle tracks as the photographic plate is automatically scanned in narrow strips. Photoelectric means convert the light flashes to proportional current pulses for application to an electronic counting circuit. Photoelectric means are further provided for developing a phase reference signal from the photographic plate in such a manner that signals arising from particle tracks not parallel to the edge of the plate are out of phase with the reference signal. The counting circuit includes provision for rejecting the out-of-phase signals resulting from unoriented tracks as well as signals resulting from spurious marks on the plate such as scratches, dust or grain clumpings, etc. The output of the circuit is hence indicative only of the tracks that would be counted by a human operator.

  16. A non-parametric method for automatic determination of P-wave and S-wave arrival times: application to local micro earthquakes

    NASA Astrophysics Data System (ADS)

    Rawles, Christopher; Thurber, Clifford

    2015-08-01

    We present a simple, fast, and robust method for automatic detection of P- and S-wave arrivals using a nearest neighbours-based approach. The nearest neighbour algorithm is one of the most popular time-series classification methods in the data mining community and has been applied to time-series problems in many different domains. Specifically, our method is based on the non-parametric time-series classification method developed by Nikolov. Instead of building a model by estimating parameters from the data, the method uses the data itself to define the model. Potential phase arrivals are identified based on their similarity to a set of reference data consisting of positive and negative sets, where the positive set contains examples of analyst identified P- or S-wave onsets and the negative set contains examples that do not contain P waves or S waves. Similarity is defined as the square of the Euclidean distance between vectors representing the scaled absolute values of the amplitudes of the observed signal and a given reference example in time windows of the same length. For both P waves and S waves, a single pass is done through the bandpassed data, producing a score function defined as the ratio of the sum of similarity to positive examples over the sum of similarity to negative examples for each window. A phase arrival is chosen as the centre position of the window that maximizes the score function. The method is tested on two local earthquake data sets, consisting of 98 known events from the Parkfield region in central California and 32 known events from the Alpine Fault region on the South Island of New Zealand. For P-wave picks, using a reference set containing two picks from the Parkfield data set, 98 per cent of Parkfield and 94 per cent of Alpine Fault picks are determined within 0.1 s of the analyst pick. For S-wave picks, 94 per cent and 91 per cent of picks are determined within 0.2 s of the analyst picks for the Parkfield and Alpine Fault data set

  17. Phase retrieval of microscope objects using the Wavelet-Gabor transform method from holographic filters

    NASA Astrophysics Data System (ADS)

    Hernández-Romo, Martín.; Padilla-Vivanco, Alfonso; Kim, Myung K.; Toxqui-Quitl, Carina

    2014-09-01

    An analysis of an optical-digital system based on the architecture of the Mach-Zehnder interferometer for recording holographic filters is presented. The holographic recording system makes use of one microscope objective in each interferometer arm. Moreover, the Gabor Wavelet Transform is implemented for the holographic reconstruction stage. The samples studied of this research are selected in order to test the retrieval algorithm and to characterize the resolution of the holographic recording system. In this last step, some sections of an USAF1951 resolution chart are used. These samples allow us to study the features of lighting in the recorded system. Additionally, some organic samples are used to proven the capabilities of the method because biological samples have much complex morphological composition than others. With this in mind, we can verify the frequencies recovered with each of the settings set in the retrieval method. Experimental results are presented.

  18. Reproducing pairs and the continuous nonstationary Gabor transform on LCA groups

    NASA Astrophysics Data System (ADS)

    Speckbacher, Michael; Balazs, Peter

    2015-10-01

    In this paper we introduce and investigate the concept of reproducing pairs as a generalization of continuous frames. Reproducing pairs yield a bounded analysis and synthesis process while the frame condition can be omitted at both stages. Moreover, we will investigate certain continuous frames (resp. reproducing pairs) on LCA groups, which can be described as a continuous version of nonstationary Gabor systems and state sufficient conditions for these systems to form a continuous frame (resp. reproducing pair). As a byproduct we identify the structure of the frame operator (resp. resolution operator). We will apply our results to systems generated by a unitary action of a subset of the affine Weyl-Heisenberg group in {L}2({{R}}). This setup will also serve as a nontrivial example of a system for which, whereas continuous frames exist, no dual system with the same structure exists even if we drop the frame property.

  19. Adaptation of Gabor filters for simulation of human preattentive mechanism for a mobile robot

    NASA Astrophysics Data System (ADS)

    Kulkarni, Naren; Naghdy, Golshah A.

    1993-08-01

    Vision guided mobile robot navigation is complex and requires analysis of tremendous amounts of information in real time. In order to simplify the task and reduce the amount of information, human preattentive mechanism can be adapted [Nag90]. During the preattentive search the scene is analyzed rapidly but in sufficient detail for the attention to be focused on the `area of interest.' The `area of interest' can further be scrutinized in more detail for recognition purposes. This `area of interest' can be a text message to facilitate navigation. Gabor filters and an automated turning mechanism are used to isolate the `area of interest.' These regions are subsequently processed with optimal spatial resolution for perception tasks. This method has clear advantages over the global operators in that, after an initial search, it scans each region of interest with optimum resolution. This reduces the volume of information for recognition stages and ensures that no region is over or under estimated.

  20. Segmenting and counting of wall-pasted cells based on gabor filter.

    PubMed

    Sun, Nongliang; Xu, Saicong; Cao, Maoyong; Li, Jing

    2005-01-01

    Correctly counting the live cells plays a great role in the ectogenetic anti-virus experiment. According to the irregular shape and arbitrary size of the wall pasted Hela cells overlapping each other, we propose a scheme to segment and count the cells using Gabor filter with different parameters and Morphological operation. Experiments reveal that filters with different parameters will lead to different results and a better segmentation will be achieved based on the characteristics of cells and optimal parameters. Large amount of experiment results show that this algorithm can successfully segment the cells and the accuracy arrives at 99.3%. This scheme based on image analysis and pattern recognition can overcome some disadvantages of traditional approaches, shortening anti-virus experimental period and reducing experimental cost. PMID:17282957

  1. A high precision feature based on LBP and Gabor theory for face recognition.

    PubMed

    Xia, Wei; Yin, Shouyi; Ouyang, Peng

    2013-01-01

    How to describe an image accurately with the most useful information but at the same time the least useless information is a basic problem in the recognition field. In this paper, a novel and high precision feature called BG2D2LRP is proposed, accompanied with a corresponding face recognition system. The feature contains both static texture differences and dynamic contour trends. It is based on Gabor and LBP theory, operated by various kinds of transformations such as block, second derivative, direct orientation, layer and finally fusion in a particular way. Seven well-known face databases such as FRGC, AR, FERET and so on are used to evaluate the veracity and robustness of the proposed feature. A maximum improvement of 29.41% is achieved comparing with other methods. Besides, the ROC curve provides a satisfactory figure. Those experimental results strongly demonstrate the feasibility and superiority of the new feature and method. PMID:23552103

  2. Retinal identification based on an Improved Circular Gabor Filter and Scale Invariant Feature Transform.

    PubMed

    Meng, Xianjing; Yin, Yilong; Yang, Gongping; Xi, Xiaoming

    2013-01-01

    Retinal identification based on retinal vasculatures in the retina provides the most secure and accurate means of authentication among biometrics and has primarily been used in combination with access control systems at high security facilities. Recently, there has been much interest in retina identification. As digital retina images always suffer from deformations, the Scale Invariant Feature Transform (SIFT), which is known for its distinctiveness and invariance for scale and rotation, has been introduced to retinal based identification. However, some shortcomings like the difficulty of feature extraction and mismatching exist in SIFT-based identification. To solve these problems, a novel preprocessing method based on the Improved Circular Gabor Transform (ICGF) is proposed. After further processing by the iterated spatial anisotropic smooth method, the number of uninformative SIFT keypoints is decreased dramatically. Tested on the VARIA and eight simulated retina databases combining rotation and scaling, the developed method presents promising results and shows robustness to rotations and scale changes. PMID:23873409

  3. Retinal Identification Based on an Improved Circular Gabor Filter and Scale Invariant Feature Transform

    PubMed Central

    Meng, Xianjing; Yin, Yilong; Yang, Gongping; Xi, Xiaoming

    2013-01-01

    Retinal identification based on retinal vasculatures in the retina provides the most secure and accurate means of authentication among biometrics and has primarily been used in combination with access control systems at high security facilities. Recently, there has been much interest in retina identification. As digital retina images always suffer from deformations, the Scale Invariant Feature Transform (SIFT), which is known for its distinctiveness and invariance for scale and rotation, has been introduced to retinal based identification. However, some shortcomings like the difficulty of feature extraction and mismatching exist in SIFT-based identification. To solve these problems, a novel preprocessing method based on the Improved Circular Gabor Transform (ICGF) is proposed. After further processing by the iterated spatial anisotropic smooth method, the number of uninformative SIFT keypoints is decreased dramatically. Tested on the VARIA and eight simulated retina databases combining rotation and scaling, the developed method presents promising results and shows robustness to rotations and scale changes. PMID:23873409

  4. Palm vein for efficient person recognition based on 2D Gabor filter

    NASA Astrophysics Data System (ADS)

    Wang, Jixing; He, Yuqing; Zhu, Jiadan; Gao, Xinru; Cui, Yongsheng

    2013-05-01

    Palm vein recognition is a relatively new method in biometrics. This paper presents an effective palm vein feature extraction approach for improving the efficiency of palm vein identification. In this paper, relevant preprocessing steps as rotation and extraction of the Region of Interest are presented. In feature extraction, multiple 2D Gabor filters with 4 orientations are employed to extract the phase information on a palm vein image, which is then merged into unique feature according to an encoding rule. Hamming distance is used for vein recognition. Experiments are carried on a selfmade palm vein database. Experimental results show that the method in this paper achieved a higher correct recognition rate and a faster speed.

  5. Fast cosmic microwave background power spectrum estimation of temperature and polarization with Gabor transforms

    NASA Astrophysics Data System (ADS)

    Hansen, Frode K.; Górski, Krzysztof M.

    2003-08-01

    We extend the analysis of Gabor transforms on a cosmic microwave background temperature map to polarization. We study the temperature and polarization power spectra on the cut sky, the so-called pseudo-power spectra. The transformation kernels relating the full-sky polarization power spectra and the polarization pseudo-power spectra are found to be similar to the kernel for the temperature power spectrum. This fact is used to construct a fast power spectrum estimation algorithm using the pseudo-power spectrum of temperature and polarization as data vectors in a maximum-likelihood approach. Using the pseudo-power spectra as input to the likelihood analysis solves the problem of having to invert huge matrices, which makes the standard likelihood approach infeasible.

  6. Automatic stabilization

    NASA Technical Reports Server (NTRS)

    Haus, FR

    1936-01-01

    This report concerns the study of automatic stabilizers and extends it to include the control of the three-control system of the airplane instead of just altitude control. Some of the topics discussed include lateral disturbed motion, static stability, the mathematical theory of lateral motion, and large angles of incidence. Various mechanisms and stabilizers are also discussed. The feeding of Diesel engines by injection pumps actuated by engine compression, achieves the required high speeds of injection readily and permits rigorous control of the combustible charge introduced into each cylinder and of the peak pressure in the resultant cycle.

  7. Swept source optical coherence tomography Gabor fusion splicing technique for microscopy of thick samples using a deformable mirror.

    PubMed

    Costa, Christopher; Bradu, Adrian; Rogers, John; Phelan, Pauline; Podoleanu, Adrian

    2015-01-01

    We present a swept source optical coherence tomography (OCT) system at 1060 nm equipped with a wavefront sensor at 830 nm and a deformable mirror in a closed-loop adaptive optics (AO) system. Due to the AO correction, the confocal profile of the interface optics becomes narrower than the OCT axial range, restricting the part of the B-scan (cross section) with good contrast. By actuating on the deformable mirror, the depth of the focus is changed and the system is used to demonstrate Gabor filtering in order to produce B-scan OCT images with enhanced sensitivity throughout the axial range from a Drosophila larvae. The focus adjustment is achieved by manipulating the curvature of the deformable mirror between two user-defined limits. Particularities of controlling the focus for Gabor filtering using the deformable mirror are presented. PMID:25588163

  8. Swept source optical coherence tomography Gabor fusion splicing technique for microscopy of thick samples using a deformable mirror

    NASA Astrophysics Data System (ADS)

    Costa, Christopher; Bradu, Adrian; Rogers, John; Phelan, Pauline; Podoleanu, Adrian

    2015-01-01

    We present a swept source optical coherence tomography (OCT) system at 1060 nm equipped with a wavefront sensor at 830 nm and a deformable mirror in a closed-loop adaptive optics (AO) system. Due to the AO correction, the confocal profile of the interface optics becomes narrower than the OCT axial range, restricting the part of the B-scan (cross section) with good contrast. By actuating on the deformable mirror, the depth of the focus is changed and the system is used to demonstrate Gabor filtering in order to produce B-scan OCT images with enhanced sensitivity throughout the axial range from a Drosophila larvae. The focus adjustment is achieved by manipulating the curvature of the deformable mirror between two user-defined limits. Particularities of controlling the focus for Gabor filtering using the deformable mirror are presented.

  9. 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.

  10. A Gabor-block-based kernel discriminative common vector approach using cosine kernels for human face recognition.

    PubMed

    Kar, Arindam; Bhattacharjee, Debotosh; Basu, Dipak Kumar; Nasipuri, Mita; Kundu, Mahantapas

    2012-01-01

    In this paper a nonlinear Gabor Wavelet Transform (GWT) discriminant feature extraction approach for enhanced face recognition is proposed. Firstly, the low-energized blocks from Gabor wavelet transformed images are extracted. Secondly, the nonlinear discriminating features are analyzed and extracted from the selected low-energized blocks by the generalized Kernel Discriminative Common Vector (KDCV) method. The KDCV method is extended to include cosine kernel function in the discriminating method. The KDCV with the cosine kernels is then applied on the extracted low-energized discriminating feature vectors to obtain the real component of a complex quantity for face recognition. In order to derive positive kernel discriminative vectors, we apply only those kernel discriminative eigenvectors that are associated with nonzero eigenvalues. The feasibility of the low-energized Gabor-block-based generalized KDCV method with cosine kernel function models has been successfully tested for classification using the L(1), L(2) distance measures; and the cosine similarity measure on both frontal and pose-angled face recognition. Experimental results on the FRAV2D and the FERET database demonstrate the effectiveness of this new approach. PMID:23365559

  11. The quantum state vector in phase space and Gabor's windowed Fourier transform

    NASA Astrophysics Data System (ADS)

    Bracken, A. J.; Watson, P.

    2010-10-01

    Representations of quantum state vectors by complex phase space amplitudes, complementing the description of the density operator by the Wigner function, have been defined by applying the Weyl-Wigner transform to dyadic operators, linear in the state vector and anti-linear in a fixed 'window state vector'. Here aspects of this construction are explored, and a connection is established with Gabor's 'windowed Fourier transform'. The amplitudes that arise for simple quantum states from various choices of windows are presented as illustrations. Generalized Bargmann representations of the state vector appear as special cases, associated with Gaussian windows. For every choice of window, amplitudes lie in a corresponding linear subspace of square-integrable functions on phase space. A generalized Born interpretation of amplitudes is described, with both the Wigner function and a generalized Husimi function appearing as quantities linear in an amplitude and anti-linear in its complex conjugate. Schrödinger's time-dependent and time-independent equations are represented on phase space amplitudes, and their solutions described in simple cases.

  12. Imperfect pitch: Gabor's uncertainty principle and the pitch of extremely brief sounds.

    PubMed

    Hsieh, I-Hui; Saberi, Kourosh

    2016-02-01

    How brief must a sound be before its pitch is no longer perceived? The uncertainty tradeoff between temporal and spectral resolution (Gabor's principle) limits the minimum duration required for accurate pitch identification or discrimination. Prior studies have reported that pitch can be extracted from sinusoidal pulses as brief as half a cycle. This finding has been used in a number of classic papers to develop models of pitch encoding. We have found that phase randomization, which eliminates timbre confounds, degrades this ability to chance, raising serious concerns over the foundation on which classic pitch models have been built. The current study investigated whether subthreshold pitch cues may still exist in partial-cycle pulses revealed through statistical integration in a time series containing multiple pulses. To this end, we measured frequency-discrimination thresholds in a two-interval forced-choice task for trains of partial-cycle random-phase tone pulses. We found that residual pitch cues exist in these pulses but discriminating them requires an order of magnitude (ten times) larger frequency difference than that reported previously, necessitating a re-evaluation of pitch models built on earlier findings. We also found that as pulse duration is decreased to less than two cycles its pitch becomes biased toward higher frequencies, consistent with predictions of an auto-correlation model of pitch extraction. PMID:26022837

  13. Real Time Gabor-Domain Optical Coherence Microscopy for 3D Imaging.

    PubMed

    Rolland, Jannick P; Canavesi, Cristina; Tankam, Patrice; Cogliati, Andrea; Lanis, Mara; Santhanam, Anand P

    2016-01-01

    Fast, robust, nondestructive 3D imaging is needed for the characterization of microscopic tissue structures across various clinical applications. A custom microelectromechanical system (MEMS)-based 2D scanner was developed to achieve, together with a multi-level GPU architecture, 55 kHz fast-axis A-scan acquisition in a Gabor-domain optical coherence microscopy (GD-OCM) custom instrument. GD-OCM yields high-definition micrometer-class volumetric images. A dynamic depth of focusing capability through a bio-inspired liquid lens-based microscope design, as in whales' eyes, was developed to enable the high definition instrument throughout a large field of view of 1 mm3 volume of imaging. Developing this technology is prime to enable integration within the workflow of clinical environments. Imaging at an invariant resolution of 2 μm has been achieved throughout a volume of 1 × 1 × 0.6 mm3, acquired in less than 2 minutes. Volumetric scans of human skin in vivo and an excised human cornea are presented. PMID:27046601

  14. Log-Gabor energy based multimodal medical image fusion in NSCT domain.

    PubMed

    Yang, Yong; Tong, Song; Huang, Shuying; Lin, Pan

    2014-01-01

    Multimodal medical image fusion is a powerful tool in clinical applications such as noninvasive diagnosis, image-guided radiotherapy, and treatment planning. In this paper, a novel nonsubsampled Contourlet transform (NSCT) based method for multimodal medical image fusion is presented, which is approximately shift invariant and can effectively suppress the pseudo-Gibbs phenomena. The source medical images are initially transformed by NSCT followed by fusing low- and high-frequency components. The phase congruency that can provide a contrast and brightness-invariant representation is applied to fuse low-frequency coefficients, whereas the Log-Gabor energy that can efficiently determine the frequency coefficients from the clear and detail parts is employed to fuse the high-frequency coefficients. The proposed fusion method has been compared with the discrete wavelet transform (DWT), the fast discrete curvelet transform (FDCT), and the dual tree complex wavelet transform (DTCWT) based image fusion methods and other NSCT-based methods. Visually and quantitatively experimental results indicate that the proposed fusion method can obtain more effective and accurate fusion results of multimodal medical images than other algorithms. Further, the applicability of the proposed method has been testified by carrying out a clinical example on a woman affected with recurrent tumor images. PMID:25214889

  15. Translation invariant directional framelet transform combined with Gabor filters for image denoising.

    PubMed

    Shi, Yan; Yang, Xiaoyuan; Guo, Yuhua

    2014-01-01

    This paper is devoted to the study of a directional lifting transform for wavelet frames. A nonsubsampled lifting structure is developed to maintain the translation invariance as it is an important property in image denoising. Then, the directionality of the lifting-based tight frame is explicitly discussed, followed by a specific translation invariant directional framelet transform (TIDFT). The TIDFT has two framelets ψ1, ψ2 with vanishing moments of order two and one respectively, which are able to detect singularities in a given direction set. It provides an efficient and sparse representation for images containing rich textures along with properties of fast implementation and perfect reconstruction. In addition, an adaptive block-wise orientation estimation method based on Gabor filters is presented instead of the conventional minimization of residuals. Furthermore, the TIDFT is utilized to exploit the capability of image denoising, incorporating the MAP estimator for multivariate exponential distribution. Consequently, the TIDFT is able to eliminate the noise effectively while preserving the textures simultaneously. Experimental results show that the TIDFT outperforms some other frame-based denoising methods, such as contourlet and shearlet, and is competitive to the state-of-the-art denoising approaches. PMID:24215934

  16. Subjective contrast sensitivity function assessment in stereoscopic viewing of Gabor patches

    NASA Astrophysics Data System (ADS)

    Rousson, Johanna; Haar, Jérémy; Platiša, Ljiljana; Piepers, Bastian; Kimpe, Tom R.; Philips, Wilfried

    2015-03-01

    While 3D displays are entering hospitals, no study to-date has explored the impact of binocular disparity and 3D inclination on contrast sensitivity function (CSF) of humans. However, knowledge of the CSF is crucial to properly calibrate medical, especially diagnostic, displays. This study examined the impact of two parameters on the CSF: (1) the depth plane position (0 mm or 171 mm behind the display plane, respectively DP:0 or DP:171), and (2) the 3D inclination (0° or 45° around the horizontal axis of the considered DP), each of these for seven spatial frequencies ranging from 0.4 to 10 cycles per degree (cpd). The stimuli were computer-generated stereoscopic images of a vertically oriented 2D Gabor patch with a given frequency. They were displayed on a 24" full HD stereoscopic display using a patterned retarder. Nine human observers assessed the CSF in a 3-down 1-up staircase experiment. Medians of the measured contrast sensitivities and results of Friedman tests suggest that the 2D CSF as modeled by Barten1 still holds when a 3D display is used as a 2D visualization system (DP:0). However, the 3D CSF measured at DP:171 was found different from the 2D CSF at frequencies below 1 cpd and above 10 cpd.

  17. Log-Gabor Energy Based Multimodal Medical Image Fusion in NSCT Domain

    PubMed Central

    Yang, Yong; Tong, Song; Huang, Shuying; Lin, Pan

    2014-01-01

    Multimodal medical image fusion is a powerful tool in clinical applications such as noninvasive diagnosis, image-guided radiotherapy, and treatment planning. In this paper, a novel nonsubsampled Contourlet transform (NSCT) based method for multimodal medical image fusion is presented, which is approximately shift invariant and can effectively suppress the pseudo-Gibbs phenomena. The source medical images are initially transformed by NSCT followed by fusing low- and high-frequency components. The phase congruency that can provide a contrast and brightness-invariant representation is applied to fuse low-frequency coefficients, whereas the Log-Gabor energy that can efficiently determine the frequency coefficients from the clear and detail parts is employed to fuse the high-frequency coefficients. The proposed fusion method has been compared with the discrete wavelet transform (DWT), the fast discrete curvelet transform (FDCT), and the dual tree complex wavelet transform (DTCWT) based image fusion methods and other NSCT-based methods. Visually and quantitatively experimental results indicate that the proposed fusion method can obtain more effective and accurate fusion results of multimodal medical images than other algorithms. Further, the applicability of the proposed method has been testified by carrying out a clinical example on a woman affected with recurrent tumor images. PMID:25214889

  18. Performance evaluation of HD camcorders: measuring texture distortions using Gabor filters and spatio-velocity CSF

    NASA Astrophysics Data System (ADS)

    Zhu, Kongfeng; Saupe, Dietmar

    2013-01-01

    This paper presents a new method of measuring physical texture distortions (PhTD) to evaluate the performance of high de_nition (HD) camcorders w.r.t. motion and lossy compression. It is extended to measure perceptual texture distortions (PeTD) by taking into account the spatio-velocity contrast sensitivity function of the human visual system. The PhTD gives an objective (physical) distortion of texture structures, while the PeTD measures the perceptual distortion of textures. The dead leaves chart, invariant to scaling, translation, rotation, and contrast, was selected as a target texture. The PhTD/PeTD metrics of the target distorted by camcorders were measured based on a bank of Gabor _lters with eight orientations and three scales. Experimental results for six HD camcorders from three vendors showed: 1) the PhTD value increases monotonically w.r.t. the motion speed, and decreases monotonically w.r.t. the lossy compression bitrate; 2) the PeTD value decreases monotonically w.r.t. the motion speed, but stays almost constant w.r.t. the lossy compression bitrate. The experiment gives a reasonable result even if the distortions are not radially symmetric. However, some subjective tests should be done in future work to validate the performance of the perceptual texture distortion metric.

  19. Rotation invariant texture retrieval considering the scale dependence of Gabor wavelet.

    PubMed

    Chaorong Li; Guiduo Duan; Fujin Zhong

    2015-08-01

    Obtaining robust and efficient rotation-invariant texture features in content-based image retrieval field is a challenging work. We propose three efficient rotation-invariant methods for texture image retrieval using copula model based in the domains of Gabor wavelet (GW) and circularly symmetric GW (CSGW). The proposed copula models use copula function to capture the scale dependence of GW/CSGW for improving the retrieval performance. It is well known that the Kullback-Leibler distance (KLD) is the commonly used similarity measurement between probability models. However, it is difficult to deduce the closed-form of KLD between two copula models due to the complexity of the copula model. We also put forward a kind of retrieval scheme using the KLDs of marginal distributions and the KLD of copula function to calculate the KLD of copula model. The proposed texture retrieval method has low computational complexity and high retrieval precision. The experimental results on VisTex and Brodatz data sets show that the proposed retrieval method is more effective compared with the state-of-the-art methods. PMID:25879945

  20. Face Detection Using Discrete Gabor Jets and a Probabilistic Model of Colored Image Patches

    NASA Astrophysics Data System (ADS)

    Hoffmann, Ulrich; Naruniec, Jacek; Yazdani, Ashkan; Ebrahimi, Touradj

    Face detection allows to recognize and detect human faces and provides information about their location in a given image. Many applications such as biometrics, face recognition, and video surveillance employ face detection as one of their main modules. Therefore, improvement in the performance of existing face detection systems and new achievements in this field of research are of significant importance. In this paper a hierarchical classification approach for face detection is presented. In the first step, discrete Gabor jets (DGJ) are used for extracting features related to the brightness information of images and a preliminary classification is made. Afterwards, a skin detection algorithm, based on modeling of colored image patches, is employed as a post-processing of the results of DGJ-based classification. It is shown that the use of color efficiently reduces the number of false positives while maintaining a high true positive rate. A comparison is made with the OpenCV implementation of the Viola and Jones face detector and it is concluded that higher correct classification rates can be attained using the proposed face detector.

  1. General approach for representing and propagating partially coherent terahertz fields with application to Gabor basis sets.

    PubMed

    Berry, Rachel H; Hobson, Michael P; Withington, Stafford

    2004-05-01

    We discuss a general theoretical framework for representing and propagating fully coherent, fully incoherent, and the intermediate regime of partially coherent submillimeter-wave fields by means of general sampled basis functions, which may have any degree of completeness. Partially coherent fields arise when finite-throughput systems induce coherence on incoherent fields. This powerful extension to traditional modal analysis methods by using undercomplete Gaussian-Hermite modes can be employed to analyze and optimize such Gaussian quasi-optical techniques. We focus on one particular basis set, the Gabor basis, which consists of overlapping translated and modulated Gaussian beams. We present high-accuracy numerical results from field reconstructions and propagations. In particular, we perform one-dimensional analyses illustrating the Van Cittert-Zernike theorem and then extend our simulations to two dimensions, including simple models of horn and bolometer arrays. Our methods and results are of practical importance as a method for analyzing terahertz fields, which are often partially coherent and diffraction limited so that ray tracing is inaccurate and physical optics computationally prohibitive. PMID:15139431

  2. Automatic transmission

    SciTech Connect

    Miura, M.; Inuzuka, T.

    1986-08-26

    1. An automatic transmission with four forward speeds and one reverse position, is described which consists of: an input shaft; an output member; first and second planetary gear sets each having a sun gear, a ring gear and a carrier supporting a pinion in mesh with the sun gear and ring gear; the carrier of the first gear set, the ring gear of the second gear set and the output member all being connected; the ring gear of the first gear set connected to the carrier of the second gear set; a first clutch means for selectively connecting the input shaft to the sun gear of the first gear set, including friction elements, a piston selectively engaging the friction elements and a fluid servo in which hydraulic fluid is selectively supplied to the piston; a second clutch means for selectively connecting the input shaft to the sun gear of the second gear set a third clutch means for selectively connecting the input shaft to the carrier of the second gear set including friction elements, a piston selectively engaging the friction elements and a fluid servo in which hydraulic fluid is selectively supplied to the piston; a first drive-establishing means for selectively preventing rotation of the ring gear of the first gear set and the carrier of the second gear set in only one direction and, alternatively, in any direction; a second drive-establishing means for selectively preventing rotation of the sun gear of the second gear set; and a drum being open to the first planetary gear set, with a cylindrical intermediate wall, an inner peripheral wall and outer peripheral wall and forming the hydraulic servos of the first and third clutch means between the intermediate wall and the inner peripheral wall and between the intermediate wall and the outer peripheral wall respectively.

  3. Maturation processes in automatic change detection as revealed by event-related brain potentials and dipole source localization: significance for adult AD/HD.

    PubMed

    Wild-Wall, Nele; Oades, Robert D; Juran, Stephanie A

    2005-10-01

    Mismatch negativity (MMN) is an event-related potential reflecting automatic attention-related information processing marking the detection of auditory change. The bilateral scalp distribution develops by 14 years of age, and is elicited with adult latencies by 17 years. But consistent with reports of continued brain maturation after adolescence, we show here that features of the temporal and frontal lobe dipole sources also continue to develop in the third decade of life. This has consequences for studies of the developmental course of MMN anomalies, from childhood into adulthood, in attention-deficit/hyperactivity disorder. Two groups of healthy subjects with mean ages of 17 and 30 years were presented with a 3-tone auditory oddball. The duration-deviant MMN was recorded during attention to a visual discrimination (auditory-passive condition) and an active auditory discrimination. MMN amplitudes were smaller in the older subjects and the MMN lasted longer over the right hemisphere. Latencies and moments of the four dipoles in the temporal and frontal lobes did not distinguish the two subject-groups. But both temporal lobe sources were located significantly more ventrally and further left in the young adult than in the adolescent subjects. The left cingular source moved posteriorly and the right inferior frontal source moved antero-medially in the older subjects. Brain development in the third decade may cause the two frontal sources to move apart on the rostro-caudal axis but the temporal lobe sources to move left on the lateral and down on the dorsoventral axes. Thus special care is necessary in interpreting putative dysfunctional neurobiological changes in developmental attention-deficit disorders where as-yet-unspecified sub-groups may show a late developmental lag, partial lag, or no lag at all, associated with other impairments. PMID:15922470

  4. The First Results of Testing Methods and Algorithms for Automatic Real Time Identification of Waveforms Introduction from Local Earthquakes in Increased Level of Man-induced Noises for the Purposes of Ultra-short-term Warning about an Occurred Earthquake

    NASA Astrophysics Data System (ADS)

    Gravirov, V. V.; Kislov, K. V.

    2009-12-01

    The chief hazard posed by earthquakes consists in their suddenness. The number of earthquakes annually recorded is in excess of 100,000; of these, over 1000 are strong ones. Great human losses usually occur because no devices exist for advance warning of earthquakes. It is therefore high time that mobile information automatic systems should be developed for analysis of seismic information at high levels of manmade noise. The systems should be operated in real time with the minimum possible computational delays and be able to make fast decisions. The chief statement of the project is that sufficiently complete information about an earthquake can be obtained in real time by examining its first onset as recorded by a single seismic sensor or a local seismic array. The essential difference from the existing systems consists in the following: analysis of local seismic data at high levels of manmade noise (that is, when the noise level may be above the seismic signal level), as well as self-contained operation. The algorithms developed during the execution of the project will be capable to be used with success for individual personal protection kits and for warning the population in earthquake-prone areas over the world. The system being developed for this project uses P and S waves as well. The difference in the velocities of these seismic waves permits a technique to be developed for identifying a damaging earthquake. Real time analysis of first onsets yields the time that remains before surface waves arrive and the damage potential of these waves. Estimates show that, when the difference between the earthquake epicenter and the monitored site is of order 200 km, the time difference between the arrivals of P waves and surface waves will be about 30 seconds, which is quite sufficient to evacuate people from potentially hazardous space, insertion of moderators at nuclear power stations, pipeline interlocking, transportation stoppage, warnings issued to rescue services

  5. 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.

  6. An automatic early stage alveolar-bone-resorption evaluation method on digital dental panoramic radiographs

    NASA Astrophysics Data System (ADS)

    Zhang, Min; Katsumata, Akitoshi; Muramatsu, Chisako; Hara, Takeshi; Suzuki, Hiroki; Fujita, Hiroshi

    2014-03-01

    Periodontal disease is a kind of typical dental diseases, which affects many adults. The presence of alveolar bone resorption, which can be observed from dental panoramic radiographs, is one of the most important signs of the progression of periodontal disease. Automatically evaluating alveolar-bone resorption is of important clinic meaning in dental radiology. The purpose of this study was to propose a novel system for automated alveolar-bone-resorption evaluation from digital dental panoramic radiographs for the first time. The proposed system enables visualization and quantitative evaluation of alveolar bone resorption degree surrounding the teeth. It has the following procedures: (1) pre-processing for a test image; (2) detection of tooth root apices with Gabor filter and curve fitting for the root apex line; (3) detection of features related with alveolar bone by using image phase congruency map and template matching and curving fitting for the alveolar line; (4) detection of occlusion line with selected Gabor filter; (5) finally, evaluation of the quantitative alveolar-bone-resorption degree in the area surrounding teeth by simply computing the average ratio of the height of the alveolar bone and the height of the teeth. The proposed scheme was applied to 30 patient cases of digital panoramic radiographs, with alveolar bone resorption of different stages. Our initial trial on these test cases indicates that the quantitative evaluation results are correlated with the alveolar-boneresorption degree, although the performance still needs further improvement. Therefore it has potential clinical practicability.

  7. Classification of high spatial resolution images by means of a Gabor wavelet decomposition and a support vector machine

    NASA Astrophysics Data System (ADS)

    Baraldi, Andrea; Bruzzone, Lorenzo

    2004-11-01

    Very high spatial resolution satellite images, acquired by third-generation commercial remote sensing (RS) satellites (like Ikonos and QuickBird), are characterized by a tremendous spatial complexity, i.e. surface objects are described by a combination of spectral, textural and shape information. Potentially capable of dealing with the spatial complexity of such images, context-sensitive data mapping systems, e.g. employing filter sets designed for texture feature analysis/synthesis, have been extensively studied in pattern recognition literature in recent years. In this work, four implementations of a two-stage classification scheme for the analysis of high spatial resolution images are compared. Competing first stage (feature extraction) implementations of increasing complexity are: 1) a standard multi-scale dyadic Gaussian pyramid image decomposition, and 2) an original almost complete (near-orthogonal) basis for the Gabor wavelet transform of an input image at selected spatial frequencies (i.e. band-pass filter central frequency and filter orientation pairs). The second stage of the classification scheme consists of: a) an ensemble of pixel-based two-class support vector machines (SVMs) applied to the multi-class classification problem according to the one-against-one strategy, exploiting the well-known SVM's capability of dealing with high dimensional mapping problems; and b) a traditional two-phase supervised learning pixel-based Radial Basis Function (RBF) network. In a badly-posed Ikonos image classification experiment, SVM combined with the two filter sets provide an interesting compromise between ease of use (i.e. easy free parameter selection), classification accuracy, robustness to changes in surface properties, capability of detecting genuine, but small, image details as well as linear structures. Qualitatively and quantitatively, the multi-scale multi-orientation almost complete Gabor wavelet transform appears superior to the dyadic multi

  8. Development of methods based on double Hough transform or Gabor filtering to discriminate between crop and weed in agronomic images

    NASA Astrophysics Data System (ADS)

    Bossu, Jérémie; Gée, Christelle; Guillemin, Jean-Philippe; Truchetet, Frédéric

    2006-02-01

    This paper presents two spatial methods to discriminate between crop and weeds. The application is related to agronomic image with perspective crop rows. The first method uses a double Hough Transform permitting a detection of crop rows and a classification between crop and weeds. The second method is based on Gabor filtering, a band pass filter. The parameters of this filter are detected from a Fast Fourier Transform of the image. For each method, a weed infestation rate is obtained. The two methods are compared and a discussion concludes about the abilities of these methods to detect the crop rows in agronomic images. Finally, we discuss this method regarding the capability of the spatial approach for classifying weeds from crop.

  9. Automatic registration of satellite imagery

    NASA Technical Reports Server (NTRS)

    Fonseca, Leila M. G.; Costa, Max H. M.; Manjunath, B. S.; Kenney, C.

    1997-01-01

    Image registration is one of the basic image processing operations in remote sensing. With the increase in the number of images collected every day from different sensors, automated registration of multi-sensor/multi-spectral images has become an important issue. A wide range of registration techniques has been developed for many different types of applications and data. The objective of this paper is to present an automatic registration algorithm which uses a multiresolution analysis procedure based upon the wavelet transform. The procedure is completely automatic and relies on the grey level information content of the images and their local wavelet transform modulus maxima. The registration algorithm is very simple and easy to apply because it needs basically one parameter. We have obtained very encouraging results on test data sets from the TM and SPOT sensor images of forest, urban and agricultural areas.

  10. Multivariate matching pursuit in optimal Gabor dictionaries: theory and software with interface for EEG/MEG via Svarog

    PubMed Central

    2013-01-01

    Background Matching pursuit algorithm (MP), especially with recent multivariate extensions, offers unique advantages in analysis of EEG and MEG. Methods We propose a novel construction of an optimal Gabor dictionary, based upon the metrics introduced in this paper. We implement this construction in a freely available software for MP decomposition of multivariate time series, with a user friendly interface via the Svarog package (Signal Viewer, Analyzer and Recorder On GPL, http://braintech.pl/svarog), and provide a hands-on introduction to its application to EEG. Finally, we describe numerical and mathematical optimizations used in this implementation. Results Optimal Gabor dictionaries, based on the metric introduced in this paper, for the first time allowed for a priori assessment of maximum one-step error of the MP algorithm. Variants of multivariate MP, implemented in the accompanying software, are organized according to the mathematical properties of the algorithms, relevant in the light of EEG/MEG analysis. Some of these variants have been successfully applied to both multichannel and multitrial EEG and MEG in previous studies, improving preprocessing for EEG/MEG inverse solutions and parameterization of evoked potentials in single trials; we mention also ongoing work and possible novel applications. Conclusions Mathematical results presented in this paper improve our understanding of the basics of the MP algorithm. Simple introduction of its properties and advantages, together with the accompanying stable and user-friendly Open Source software package, pave the way for a widespread and reproducible analysis of multivariate EEG and MEG time series and novel applications, while retaining a high degree of compatibility with the traditional, visual analysis of EEG. PMID:24059247

  11. An anatomy of automatism.

    PubMed

    Mackay, R D

    2015-07-01

    The automatism defence has been described as a quagmire of law and as presenting an intractable problem. Why is this so? This paper will analyse and explore the current legal position on automatism. In so doing, it will identify the problems which the case law has created, including the distinction between sane and insane automatism and the status of the 'external factor doctrine', and comment briefly on recent reform proposals. PMID:26378105

  12. Automatic differentiation bibliography

    SciTech Connect

    Corliss, G.F.

    1992-07-01

    This is a bibliography of work related to automatic differentiation. Automatic differentiation is a technique for the fast, accurate propagation of derivative values using the chain rule. It is neither symbolic nor numeric. Automatic differentiation is a fundamental tool for scientific computation, with applications in optimization, nonlinear equations, nonlinear least squares approximation, stiff ordinary differential equation, partial differential equations, continuation methods, and sensitivity analysis. This report is an updated version of the bibliography which originally appeared in Automatic Differentiation of Algorithms: Theory, Implementation, and Application.

  13. Automatic crack propagation tracking

    NASA Technical Reports Server (NTRS)

    Shephard, M. S.; Weidner, T. J.; Yehia, N. A. B.; Burd, G. S.

    1985-01-01

    A finite element based approach to fully automatic crack propagation tracking is presented. The procedure presented combines fully automatic mesh generation with linear fracture mechanics techniques in a geometrically based finite element code capable of automatically tracking cracks in two-dimensional domains. The automatic mesh generator employs the modified-quadtree technique. Crack propagation increment and direction are predicted using a modified maximum dilatational strain energy density criterion employing the numerical results obtained by meshes of quadratic displacement and singular crack tip finite elements. Example problems are included to demonstrate the procedure.

  14. Practical automatic Arabic license plate recognition system

    NASA Astrophysics Data System (ADS)

    Mohammad, Khader; Agaian, Sos; Saleh, Hani

    2011-02-01

    Since 1970's, the need of an automatic license plate recognition system, sometimes referred as Automatic License Plate Recognition system, has been increasing. A license plate recognition system is an automatic system that is able to recognize a license plate number, extracted from image sensors. In specific, Automatic License Plate Recognition systems are being used in conjunction with various transportation systems in application areas such as law enforcement (e.g. speed limit enforcement) and commercial usages such as parking enforcement and automatic toll payment private and public entrances, border control, theft and vandalism control. Vehicle license plate recognition has been intensively studied in many countries. Due to the different types of license plates being used, the requirement of an automatic license plate recognition system is different for each country. [License plate detection using cluster run length smoothing algorithm ].Generally, an automatic license plate localization and recognition system is made up of three modules; license plate localization, character segmentation and optical character recognition modules. This paper presents an Arabic license plate recognition system that is insensitive to character size, font, shape and orientation with extremely high accuracy rate. The proposed system is based on a combination of enhancement, license plate localization, morphological processing, and feature vector extraction using the Haar transform. The performance of the system is fast due to classification of alphabet and numerals based on the license plate organization. Experimental results for license plates of two different Arab countries show an average of 99 % successful license plate localization and recognition in a total of more than 20 different images captured from a complex outdoor environment. The results run times takes less time compared to conventional and many states of art methods.

  15. Computer systems for automatic earthquake detection

    USGS Publications Warehouse

    Stewart, S.W.

    1974-01-01

    U.S Geological Survey seismologists in Menlo park, California, are utilizing the speed, reliability, and efficiency of minicomputers to monitor seismograph stations and to automatically detect earthquakes. An earthquake detection computer system, believed to be the only one of its kind in operation, automatically reports about 90 percent of all local earthquakes recorded by a network of over 100 central California seismograph stations. The system also monitors the stations for signs of malfunction or abnormal operation. Before the automatic system was put in operation, all of the earthquakes recorded had to be detected by manually searching the records, a time-consuming process. With the automatic detection system, the stations are efficiently monitored continuously. 

  16. Digital automatic gain control

    NASA Technical Reports Server (NTRS)

    Uzdy, Z.

    1980-01-01

    Performance analysis, used to evaluated fitness of several circuits to digital automatic gain control (AGC), indicates that digital integrator employing coherent amplitude detector (CAD) is best device suited for application. Circuit reduces gain error to half that of conventional analog AGC while making it possible to automatically modify response of receiver to match incoming signal conditions.

  17. Automatic Differentiation Package

    Energy Science and Technology Software Center (ESTSC)

    2007-03-01

    Sacado is an automatic differentiation package for C++ codes using operator overloading and C++ templating. Sacado provide forward, reverse, and Taylor polynomial automatic differentiation classes and utilities for incorporating these classes into C++ codes. Users can compute derivatives of computations arising in engineering and scientific applications, including nonlinear equation solving, time integration, sensitivity analysis, stability analysis, optimization and uncertainity quantification.

  18. Automatic Contrail Detection and Segmentation

    NASA Technical Reports Server (NTRS)

    Weiss, John M.; Christopher, Sundar A.; Welch, Ronald M.

    1998-01-01

    Automatic contrail detection is of major importance in the study of the atmospheric effects of aviation. Due to the large volume of satellite imagery, selecting contrail images for study by hand is impractical and highly subject to human error. It is far better to have a system in place that will automatically evaluate an image to determine 1) whether it contains contrails and 2) where the contrails are located. Preliminary studies indicate that it is possible to automatically detect and locate contrails in Advanced Very High Resolution Radiometer (AVHRR) imagery with a high degree of confidence. Once contrails have been identified and localized in a satellite image, it is useful to segment the image into contrail versus noncontrail pixels. The ability to partition image pixels makes it possible to determine the optical properties of contrails, including optical thickness and particle size. In this paper, we describe a new technique for segmenting satellite images containing contrails. This method has good potential for creating a contrail climatology in an automated fashion. The majority of contrails are detected, rejecting clutter in the image, even cirrus streaks. Long, thin contrails are most easily detected. However, some contrails may be missed because they are curved, diffused over a large area, or present in short segments. Contrails average 2-3 km in width for the cases studied.

  19. Oil species identification technique developed by Gabor wavelet analysis and support vector machine based on concentration-synchronous-matrix-fluorescence spectroscopy.

    PubMed

    Wang, Chunyan; Shi, Xiaofeng; Li, Wendong; Wang, Lin; Zhang, Jinliang; Yang, Chun; Wang, Zhendi

    2016-03-15

    Concentration-synchronous-matrix-fluorescence (CSMF) spectroscopy was applied to discriminate the oil species by characterizing the concentration dependent fluorescence properties of petroleum related samples. Seven days weathering experiment of 3 crude oil samples from the Bohai Sea platforms of China was carried out under controlled laboratory conditions and showed that weathering had no significant effect on the CSMF spectra. While different feature extraction methods, such as PCA, PLS and Gabor wavelet analysis, were applied to extract discriminative patterns from CSMF spectra, classifications were made via SVM to compare their respective performance of oil species recognition. Ideal correct rates of oil species recognition of 100% for the different types of oil spill samples and 92% for the closely-related source oil samples were achieved by combining Gabor wavelet with SVM, which indicated its advantages to be developed to a rapid, cost-effective, and accurate forensic oil spill identification technique. PMID:26795119

  20. Automatic classification for pathological prostate images based on fractal analysis.

    PubMed

    Huang, Po-Whei; Lee, Cheng-Hsiung

    2009-07-01

    Accurate grading for prostatic carcinoma in pathological images is important to prognosis and treatment planning. Since human grading is always time-consuming and subjective, this paper presents a computer-aided system to automatically grade pathological images according to Gleason grading system which is the most widespread method for histological grading of prostate tissues. We proposed two feature extraction methods based on fractal dimension to analyze variations of intensity and texture complexity in regions of interest. Each image can be classified into an appropriate grade by using Bayesian, k-NN, and support vector machine (SVM) classifiers, respectively. Leave-one-out and k-fold cross-validation procedures were used to estimate the correct classification rates (CCR). Experimental results show that 91.2%, 93.7%, and 93.7% CCR can be achieved by Bayesian, k-NN, and SVM classifiers, respectively, for a set of 205 pathological prostate images. If our fractal-based feature set is optimized by the sequential floating forward selection method, the CCR can be promoted up to 94.6%, 94.2%, and 94.6%, respectively, using each of the above three classifiers. Experimental results also show that our feature set is better than the feature sets extracted from multiwavelets, Gabor filters, and gray-level co-occurrence matrix methods because it has a much smaller size and still keeps the most powerful discriminating capability in grading prostate images. PMID:19164082

  1. Linearity Can Account for the Similarity Among Conventional, Frequency-Doubling, and Gabor-Based Perimetric Tests in the Glaucomatous Macula

    PubMed Central

    DUL, MITCHELL W.; SWANSON, WILLIAM H.

    2006-01-01

    Purposes The purposes of this study are to compare macular perimetric sensitivities for conventional size III, frequency-doubling, and Gabor stimuli in terms of Weber contrast and to provide a theoretical interpretation of the results. Methods Twenty-two patients with glaucoma performed four perimetric tests: a conventional Swedish Interactive Threshold Algorithm (SITA) 10-2 test with Goldmann size III stimuli, two frequency-doubling tests (FDT 10-2, FDT Macula) with counterphase-modulated grating stimuli, and a laboratory-designed test with Gabor stimuli. Perimetric sensitivities were converted to the reciprocal of Weber contrast and sensitivities from different tests were compared using the Bland-Altman method. Effects of ganglion cell loss on perimetric sensitivities were then simulated with a two-stage neural model. Results The average perimetric loss was similar for all stimuli until advanced stages of ganglion cell loss, in which perimetric loss tended to be greater for size III stimuli than for frequency-doubling and Gabor stimuli. Comparison of the experimental data and model simulation suggests that, in the macula, linear relations between ganglion cell loss and perimetric sensitivity loss hold for all three stimuli. Conclusions Linear relations between perimetric loss and ganglion cell loss for all three stimuli can account for the similarity in perimetric loss until advanced stages. The results do not support the hypothesis that redundancy for frequency-doubling stimuli is lower than redundancy for size III stimuli. PMID:16840860

  2. Supervised Material Classification in Oblique Aerial Imagery Using Gabor Filter Features

    NASA Astrophysics Data System (ADS)

    Harris, Michael L.

    RIT's Digital Imaging and Remote Sensing Image Generation (DIRSIG) tool allows modeling of real world scenes to create synthetic imagery for sensor design and analysis, trade studies, algorithm validation, and training image analysts. To increase model construction speed, and the diversity and size of synthetic scenes which can be generated it is desirable to automatically segment real world imagery into different material types and import a material classmap into DIRSIG. This work contributes a methodology based on standard texture recognition techniques to supervised classification of material types in oblique aerial imagery. Oblique imagery provides many challenges for texture recognition due to illumination changes with view angle, projective distortions, occlusions and self shadowing. It is shown that features derived from a set of rotationally invariant bandpass filters fused with color channel information can provide supervised classification accuracies up to 70% with minimal training data.

  3. Real-time automatic registration in optical surgical navigation

    NASA Astrophysics Data System (ADS)

    Lin, Qinyong; Yang, Rongqian; Cai, Ken; Si, Xuan; Chen, Xiuwen; Wu, Xiaoming

    2016-05-01

    An image-guided surgical navigation system requires the improvement of the patient-to-image registration time to enhance the convenience of the registration procedure. A critical step in achieving this aim is performing a fully automatic patient-to-image registration. This study reports on a design of custom fiducial markers and the performance of a real-time automatic patient-to-image registration method using these markers on the basis of an optical tracking system for rigid anatomy. The custom fiducial markers are designed to be automatically localized in both patient and image spaces. An automatic localization method is performed by registering a point cloud sampled from the three dimensional (3D) pedestal model surface of a fiducial marker to each pedestal of fiducial markers searched in image space. A head phantom is constructed to estimate the performance of the real-time automatic registration method under four fiducial configurations. The head phantom experimental results demonstrate that the real-time automatic registration method is more convenient, rapid, and accurate than the manual method. The time required for each registration is approximately 0.1 s. The automatic localization method precisely localizes the fiducial markers in image space. The averaged target registration error for the four configurations is approximately 0.7 mm. The automatic registration performance is independent of the positions relative to the tracking system and the movement of the patient during the operation.

  4. Automatic amino acid analyzer

    NASA Technical Reports Server (NTRS)

    Berdahl, B. J.; Carle, G. C.; Oyama, V. I.

    1971-01-01

    Analyzer operates unattended or up to 15 hours. It has an automatic sample injection system and can be programmed. All fluid-flow valve switching is accomplished pneumatically from miniature three-way solenoid pilot valves.

  5. Automatic Payroll Deposit System.

    ERIC Educational Resources Information Center

    Davidson, D. B.

    1979-01-01

    The Automatic Payroll Deposit System in Yakima, Washington's Public School District No. 7, directly transmits each employee's salary amount for each pay period to a bank or other financial institution. (Author/MLF)

  6. Automatic switching matrix

    DOEpatents

    Schlecht, Martin F.; Kassakian, John G.; Caloggero, Anthony J.; Rhodes, Bruce; Otten, David; Rasmussen, Neil

    1982-01-01

    An automatic switching matrix that includes an apertured matrix board containing a matrix of wires that can be interconnected at each aperture. Each aperture has associated therewith a conductive pin which, when fully inserted into the associated aperture, effects electrical connection between the wires within that particular aperture. Means is provided for automatically inserting the pins in a determined pattern and for removing all the pins to permit other interconnecting patterns.

  7. Automatic removal of outliers in hydrologic time series and quality control of rainfall data: processing a real-time database of the Local System for Flood Monitoring in Klodzko County, Poland

    NASA Astrophysics Data System (ADS)

    Mizinski, Bartlomiej; Niedzielski, Tomasz; Kryza, Maciej; Szymanowski, Mariusz

    2013-04-01

    Real-time hydrological forecasting requires the highest quality of both hydrologic and meteorological data collected in a given river basin. Large outliers may lead to inaccurate predictions, with substantial departures between observations and prognoses considered even in short term. Although we need the correctness of both riverflow and rainfall data, they cannot be processed in the same way to produce a filtered output. Indeed, hydrologic time series at a given gauge can be interpolated in time domain after having detected suspicious values, however if no outlier has been detected at the upstream sites. In the case of rainfall data, interpolation is not suitable as we cannot verify the potential outliers at a given site against data from other sites especially in the complex terrain. This is due to the fact that very local convective events may occur, leading to large rainfall peaks at a limited space. Hence, instead of interpolating data, we rather perform a flagging procedure that only ranks outliers according to the likelihood of occurrence. Following the aforementioned assumptions, we have developed a few modules that serve a purpose of a fully automated correction of a database that is updated in real-time every 15 minutes, and the main objective of the work was to produce a high-quality database for a purpose of hydrologic rainfall-runoff modeling and ensemble prediction. The database in question is available courtesy of the County Office in Kłodzko (SW Poland), the institution which owns and maintains the Local System for Flood Monitoring in Kłodzko County. The dedicated prediction system, known as HydroProg, is now being built at the University of Wrocław (Poland). As the entire prediction system, the correction modules work automatically in real time and are developed in R language. They are plugged in to a larger IT infrastructure. Hydrologic time series, which are water levels recorded every 15 minutes at 22 gauges located in Kłodzko County, are

  8. Parallelized multi–graphics processing unit framework for high-speed Gabor-domain optical coherence microscopy

    PubMed Central

    Tankam, Patrice; Santhanam, Anand P.; Lee, Kye-Sung; Won, Jungeun; Canavesi, Cristina; Rolland, Jannick P.

    2014-01-01

    Abstract. Gabor-domain optical coherence microscopy (GD-OCM) is a volumetric high-resolution technique capable of acquiring three-dimensional (3-D) skin images with histological resolution. Real-time image processing is needed to enable GD-OCM imaging in a clinical setting. We present a parallelized and scalable multi-graphics processing unit (GPU) computing framework for real-time GD-OCM image processing. A parallelized control mechanism was developed to individually assign computation tasks to each of the GPUs. For each GPU, the optimal number of amplitude-scans (A-scans) to be processed in parallel was selected to maximize GPU memory usage and core throughput. We investigated five computing architectures for computational speed-up in processing 1000×1000 A-scans. The proposed parallelized multi-GPU computing framework enables processing at a computational speed faster than the GD-OCM image acquisition, thereby facilitating high-speed GD-OCM imaging in a clinical setting. Using two parallelized GPUs, the image processing of a 1×1×0.6  mm3 skin sample was performed in about 13 s, and the performance was benchmarked at 6.5 s with four GPUs. This work thus demonstrates that 3-D GD-OCM data may be displayed in real-time to the examiner using parallelized GPU processing. PMID:24695868

  9. Contrast sensitivity function in stereoscopic viewing of Gabor patches on a medical polarized three-dimensional stereoscopic display

    NASA Astrophysics Data System (ADS)

    Rousson, Johanna; Haar, Jérémy; Santal, Sarah; Kumcu, Asli; Platiša, Ljiljana; Piepers, Bastian; Kimpe, Tom; Philips, Wilfried

    2016-03-01

    While three-dimensional (3-D) imaging systems are entering hospitals, no study to date has explored the luminance calibration needs of 3-D stereoscopic diagnostic displays and if they differ from two-dimensional (2-D) displays. Since medical display calibration incorporates the human contrast sensitivity function (CSF), we first assessed the 2-D CSF for benchmarking and then examined the impact of two image parameters on the 3-D stereoscopic CSF: (1) five depth plane (DP) positions (between DP: -171 and DP: 2853 mm), and (2) three 3-D inclinations (0 deg, 45 deg, and 60 deg around the horizontal axis of a DP). Stimuli were stereoscopic images of a vertically oriented 2-D Gabor patch at one of seven frequencies ranging from 0.4 to 10 cycles/deg. CSFs were measured for seven to nine human observers with a staircase procedure. The results indicate that the 2-D CSF model remains valid for a 3-D stereoscopic display regardless of the amount of disparity between the stereo images. We also found that the 3-D CSF at DP≠0 does not differ from the 3-D CSF at DP=0 for DPs and disparities which allow effortless binocular fusion. Therefore, the existing 2-D medical luminance calibration algorithm remains an appropriate tool for calibrating polarized stereoscopic medical displays.

  10. Time-frequency analysis of nonstationary vibration signals for deployable structures by using the constant-Q nonstationary gabor transform

    NASA Astrophysics Data System (ADS)

    Liu, Tao; Yan, Shaoze; Zhang, Wei

    2016-06-01

    Deployable structures have been widely used in on-orbit servicing spacecrafts, and the vibration properties of such structures have become increasingly important in the aerospace industry. The constant-Q nonstationary Gabor transform (CQ-NSGT) is introduced in this paper to accurately evaluate the variation in the frequency and amplitude of vibration signals along with time. First, an example signal is constructed on the basis of the vibration properties of deployable structures and is processed by the short-time Fourier transform, Wigner-Ville distribution, Hilbert-Huang transform, and CQ-NSGT. Results show that time and frequency resolutions are simultaneously fine only by employing CQ-NSGT. Subsequently, a zero padding operation is conducted to correct the calculation error at the end of the transform results. Finally, a set of experimental devices is constructed. The vibration signal of the experimental mode is processed by CQ-NSGT. On this basis, the experimental signal properties are discussed. This time-frequency method may be useful for formulating the dynamics for complex deployable structures.