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检索条件"机构=Vision and Image Processing Laboratory"

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A fast level set algorithm for shape-based segmentation with multiple selective priors

A fast level set algorithm for shape-based segmentation with...

引用

IEEE International Conference on image processing

作者： Rachid Fahmi Aly A. Farag Computer Vision & Image Processing laboratory University of Louisville Louisville KY USA

This paper addresses the shape-based segmentation problem using level sets. In particular, we propose a fast algorithm to solve the piece-wise constant Chan-Vese segmentation model with shape priors and labeling functions. Instead of directly solving the underlying PDE, we calculate the energy and check how it changes when we move image points from inside the region enclosed by the evolving interface to the outside region and vice-vera. This algorithm is then extended to the case of multi-phase Chan-Vese model, with multiple selective shape priors and a corresponding labeling function for each prior. This makes our algorithm different from that in [1] and other similar works in different aspects. On one hand, our algorithm is not restricted to two regions, but allows segmentation into several regions. On the other hand, more than one shape prior can be taken into account in our implementation. In addition, the proposed algorithm improves dramatically the computational speed. Experimental results, on both synthetic and real images, demonstrate the performance of our algorithm and the computational improvements it offers.

关键词： Level set image segmentation Shape Labeling Computer vision image processing Laboratories Biomedical imaging Application software Noise shaping

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Analytic Bilinear Appearance Subspace Construction for Modeling image Irradiance Under Natural Illumination and Non-Lambertian Reflectance

Analytic Bilinear Appearance Subspace Construction for Model...

引用

IEEE Conference on Computer vision and Pattern Recognition

作者： Shireen Y. Elhabian Aly A. Farag Computer Vision and Image Processing Laboratory ECE Dept. University of Louisville

ISBN: (纸本)9781467364102

Conventional subspace construction approaches suffer from the need of "large-enough" image ensemble rendering numerical methods intractable. In this paper, we propose an analytic formulation for low-dimensional subspace construction in which shading cues lie while preserving the natural structure of an image sample. Using the frequency-space representation of the image irradiance equation, the process of finding such subspace is cast as establishing a relation between its principal components and that of a deterministic set of basis functions, termed as irradiance harmonics. Representing images as matrices further lessen the number of parameters to be estimated to define a bilinear projection which maps the image sample to a lower-dimensional bilinear subspace. Results show significant impact on dimensionality reduction with minimal loss of information as well as robustness against noise.

关键词： Lighting Harmonic analysis Principal component analysis image reconstruction Materials Gold Surface reconstruction

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An automated vertebra identification and segmentation in CT images

An automated vertebra identification and segmentation in CT ...

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IEEE International Conference on image processing

作者： Melih S. Aslan Asem Ali Ham Rara Aly A. Farag Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA

In this paper, we propose a new 3D framework to identify and segment VBs and TBs in clinical computed tomography (CT) images without any user intervention. The Matched filter is employed to detect the VB region automatically on axial axis. To identify the VB on coronal and sagittal axis, we use a new developed approach based on 4 points automatically placed on cortical shell. To segment the identified VB, the graph cuts method which integrates a linear combination of Gaussians (LCG) and Markov Gibbs Random Field (MGRF) are used. Then, the cortical and trabecular bones are segmented using local volume growing methods. Experiments on the data sets show that the proposed segmentation approach is more accurate than other known alternatives.

关键词： Bones image segmentation Computed tomography Three dimensional displays Accuracy Spine Biomedical imaging

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Stochastic models in image analysis: parameter estimations and case studies in image segmentation

Stochastic models in image analysis: parameter estimations a...

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IEEE/SP Workshop on Statistical Signal processing (SSP)

作者： A. El-Baz A.A. Farag Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA

Stochastic models of images are commonly represented in terms of three random processes (random fields) defined on the region of support of the image. The observed image process G is considered as a composite of two random process: a high level process X, which represents the regions (or classes) that form the observed image; and a low level process Y, which describes the statistical characteristics of each region (or class). The representation G = (X, Y) has been widely used in the image processing literature in the past two decades. In this paper we show how to use expectation maximization (EM) algorithm to get accurate model for the low level image by using mixture of normal distribution. The main idea of the proposed algorithm is as follow: first, we will use the EM algorithm to get the most dominance mixtures in the given density (empirical density), and then we assume that the absolute error between the empirical density and the estimated density is another density and we use the EM algorithm to estimate the number of mixtures in this error and the parameters for each mixtures. Then the estimated density for the absolute error is added or subtracted from the estimated density according to the sign (error). Convergence to the true distribution is tested using the Levy distance. A popular model for the high level process X has been the Gibbs-Markov random field (GMRF) model. In this paper we will use the same approach, which described in A. El-Baz et al. (July 2003) to estimate the parameters of GMRF. The approach has been applied on real images (spiral CT slices) and provides satisfactory results.

关键词： Stochastic processes image analysis Parameter estimation image segmentation Random processes image processing Gaussian distribution Convergence Testing Spirals

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Supervised fuzzy and Bayesian classification of high dimensional data: a comparative study

Supervised fuzzy and Bayesian classification of high dimensi...

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IEEE International Conference on image processing

作者： M.G.-H. Mostafa T.C. Perkins A.A. Farag Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA

ISBN: (纸本)0780362977

This paper presents a supervised fuzzy c-mean (SFCM) classifier for the classification of high dimensional data. The proposed SFCM classifier can be iterative or non iterative to reduce the computational time. Comparison with the conventional FCM clustering technique and the Bayesian classification technique is also presented. Performance results of the three algorithms are presented on simulated and real remote sensing multispectral data, which show improvement in the classification accuracy using the SFCM technique.

关键词： Bayesian methods Clustering algorithms Iterative algorithms Remote sensing Computer vision Fuzzy logic Pixel Uncertainty Classification algorithms image processing

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Dynamic Weighting of Facial Features for Automatic Pose-Invariant Face Recognition

Dynamic Weighting of Facial Features for Automatic Pose-Inva...

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Canadian Conference on Computer and Robot vision, CRV

作者： Eslam A. Mostafa Aly A. Farag Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA

This paper proposes an automatic pose-invariant face recognition system. In our approach, we consider the texture information around the facial features to compute the similarity measure between the probe and gallery images. The weight of each facial feature is dynamically estimated based on its robustness to the pose of the captured image. An approach to extract the 9 facial features used to initialize the Active shape model is proposed. The approach is not dependent on the texture around the facial feature only but incorporates the information obtained about the facial feature relations. Our face recognition system is tested on common datasets in pose evaluation CMU-PIE and FERET. The results show out-performance of the state of the art automatic face recognition systems.

关键词： Facial features Face Shape Face recognition Feature extraction Detectors Active appearance model

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The use of mathematical morphology in image enhancement

The use of mathematical morphology in image enhancement

引用

Midwest Symposium on Circuits and Systems (MWSCAS)

作者： J. Song R.L. Stevenson E.J. Delp Computer Vision and Image Processing Laboratory Purdue University West Lafayette IN USA

The structure and properties of several morphological filtering algorithms are discussed. The performance of the algorithms when applied to images corrupted with noise is presented. Several open research problems rela... 详细信息

关键词： Morphology image enhancement Nonlinear filters Filtering algorithms image processing Morphological operations Gray-scale Information filtering Information filters Computer vision

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A neural approach for single- and multi-image camera calibration

A neural approach for single- and multi-image camera calibra...

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IEEE International Conference on image processing

作者： M. Ahmed E. Hemayed A. Farag Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA

This paper presents the neurocalibration approach as a new neural-based solution for the problem of camera calibration. Unlike some existing neural approaches, our calibrating network can match the perspective-projection-transformation matrix between the world 3D points and the corresponding 2D image pixels. Starting from random initial weights, the net can specify the camera model parameters satisfying the orthogonality constraints on the rotational transformation. In order to improve the accuracy of calibration results, the paper demonstrates the application of the neurocalibration technique to multi-image camera calibration. In such a case, many images are taken by the same camera but from different (rotated and/or translated) positions. Experiments have shown the accuracy and the efficiency of our neurocalibration technique.

关键词： Cameras Calibration Matrix decomposition Neural networks Computer vision image processing Laboratories Pixel Parameter estimation Measurement errors

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A new unsupervised approach for the classification of multispectral data

A new unsupervised approach for the classification of multis...

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International Conference on Information Fusion

作者： R.M. Mohamed A.A. Farag Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA

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Monocular, vision based, autonomous refueling system

Monocular, vision based, autonomous refueling system

引用

IEEE Workshop on Applications of Computer vision (WACV)

作者： A. Farag E. Dizdarevic A. Eid A. Lorincz Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA

This paper describes design and implementation of a vision based platform for automated refueling tasks. The platform is an autonomous docking system in principle, with the specific application - refueling of vehicles. The system is. based on monochromatic, monocular vision, and it utilizes very specialized image processing schemes. image processing consists of very fast filtering and segmenting algorithms, as well as moment's computation. A robotic arm with 6 joints (FANUC M-6i), and a controller unit (R-B), does the physical work. A serial interface, with very high-level commands, connects a supercomputing machine and the robot's controller. A practical setup would probably be scaled down to a special design robot, and a single processor, controller with special VLSI chips for image processing. Results are very promising; the robot can identify the cap position, orientation, and height in real time with acceptable accuracy and reliability.

关键词： image processing Robot vision systems Cameras Robotics and automation Shape Computer vision Laboratories image segmentation Robot control Vehicles

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