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A Variational Approach for Shapes Registration Using Vector Maps

A Variational Approach for Shapes Registration Using Vector ...

引用

IEEE International Conference on image processing

作者： Hossam Abd El Munim Aly A. Farag Computer Vision and Image Processing Laboratory (CVIP) University of Louisville Louisville KY Computer Vision and Image Processing Laboratory (CVIP) University of Louisville Louisville KY USA

The main focus of this paper is the shape representation and registration using vector level set functions. This powerful representation is more flexible than conventional signed distance level sets since it enables us to control the shapes registration process by using more complicated transforms. Based on this model, a variational frame work is proposed for the rigid and non-rigid registration of shapes which can be extended to the higher dimensional case in a straightforward manner and also does not need any point correspondences. The optimization criterion presented can handle efficiently both the rigid and the non-rigid operations together. Experimental results in 2D for real shapes registration are discussed to show the efficiency of the approach with small and large global deformations of shapes.

关键词： Level set Shape measurement computer vision Shape control image segmentation Topology image processing Laboratories Focusing Energy measurement

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Multiresolution approach for non-contact measurements of arterial pulse using thermal imaging

Multiresolution approach for non-contact measurements of art...

引用

2006 Conference on computer vision and Pattern Recognition Workshops

作者： Chekmenev, Sergey Y. Farag, Aly A. Essock, Edward A. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States Department of Psychological and Brain Sciences University of Louisville Louisville KY 40292 United States

ISBN: (纸本)0769526462

This paper presents a novel, multiresolution (MR) approach for non-contact passive measurements of the arterial pulse along the arterial tree using thermal imaging of the most accessible regions of human face and neck. The method automatically detects Region/s Of Measurement (ROM) of the arterial pulse using the periodic nature of arterial thermal patterns. This ROM constitutes a skin area where the heat pulsation produced by an artery is most pronounced The output of the algorithm is a descriptive arterial pulse waveform. To the best of our knowledge, our results are novel and have not been reported before. Some potential applications of this work are in the field of non-contact health state/ physiology monitoring, magnetic resonance imaging, smart rooms, polygraph testing, and intent identification. © 2006 IEEE.

关键词： Blood vessels

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New Deformable Registration Technique Using Scale Space and Curve Evolution Theory and A Finite Element Based Validation Framework

New Deformable Registration Technique Using Scale Space and ...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Rachid Fahmi Alaa Aly Ayman Elbaz Aly A. Farag Computer Vision & Image Processing laboratory University Of Louisville Louisville KY USA

In this paper, we present a novel and accurate approach for nonrigid registration. New feature descriptors are built as voxel signatures using scale space theory. These descriptors are used to capture the global motion of the imaged object. Local deformations are modelled through an evolution process of equi-spaced closed curves/surfaces (iso-contours/surfaces) which are generated using fast marching level sets and are matched using the built feature descriptors. The performance of the proposed approach is validated using the finite element method. Both 2D and 3D tissue deformations cases are simulated, and the registration accuracy is quantified by co-registering the deformed images with the original ones and comparing the recovered mesh point displacements with the simulated ones. The evaluation results show the potential of the proposed approach in handling local deformation better than some conventional approaches

关键词： Finite element methods Deformable models image edge detection Brain modeling Level set Robustness Spline Cities and towns USA Councils Anatomy

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A new adaptive probabilistic model of blood vessels for segmenting MRA images

引用

9th International Conference on Medical image Computing and computer-Assisted Intervention, MICCAI 2006

作者： El-Baz, Ayman Farag, Aly A. Gimel'Farb, Georgy El-Ghar, Mohamed A. Eldiasty, Tarek Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States Department of Computer Science Tamaki Campus University of Auckland Auckland New Zealand Urology and Nephrology Department University of Mansoura Mansoura Egypt

ISBN: (纸本)354044727X

A new physically justified adaptive probabilistic model of blood vessels on magnetic resonance angiography (MRA) images is proposed. The model accounts for both laminar (for normal subjects) and turbulent blood flow (in abnormal cases like anemia or stenosis) and results in a fast algorithm for extracting a 3D cerebrovascular system from the MRA data. Experiments with synthetic and 50 real data sets confirm the high accuracy of the proposed approach. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Magnetic resonance imaging

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Accurate Tracking of Monotonically Advancing Fronts

Accurate Tracking of Monotonically Advancing Fronts

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Conference on computer vision and Pattern Recognition (CVPR)

作者： M.S. Hassouna A.A. Farag Computer Vision and Image Processing Laboratory (CVIP) University of Louisville Louisville KY USA

A wide range of computer vision applications such as distance field computation, shape from shading, and shape representation require an accurate solution of a particular Hamilton-Jacobi (HJ) equation, known as the Eikonal equation. Although the fast marching method (FMM) is the most stable and consistent method among existing techniques for solving such equation, it suffers from large numerical error along diagonal directions as well as its computational complexity is not optimal. In this paper, we propose an improved version of the FMMthat is both highly accurate and computationally efficient for Cartesian domains. The new method is called the multi-stencils fast marching (MSFM), which computes the solution at each grid point by solving the Eikonal equation along several stencils and then picks the solution that satisfies the fast marching causality relationship. The stencils are centered at each grid point x and cover its entire nearest neighbors. In 2D space, 2 stencils cover the 8-neighbors of x, while in 3D space, 6 stencils cover its 26-neighbors. For those stencils that are not aligned with the natural coordinate system, the Eikonal equation is derived using directional derivatives and then solved using a higher order finite difference scheme.

关键词： computer vision Shape Finite difference methods Application software Computational complexity Nonlinear equations Partial differential equations image processing Laboratories Grid computing

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Level Set Segmentation Using Statistical Shape Priors

Level Set Segmentation Using Statistical Shape Priors

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IEEE computer Society Conference on computer vision and Pattern Recognition Workshops (CVPRW)

作者： A.S. El-Baz A.A. Farag H.A. El Munim S.E. Yuksel Computer Vision & Image Processing Laboratory (CVIP) University of Louisville Louisville KY USA

A novel and robust 3-D segmentation approach is proposed using level sets based on shape constraints. The approach depends on both the gray level and shape information. A partial differential equation (PDE) is developed to control the evolution of the level sets. The PDE does not include weighting coefficients to be tuned, overcoming the disadvantages of other PDE approaches. The shape information is gathered from a set of the signed distance maps representing the training data as a histogram of the occurrences of the points inside and outside the object. We use a novel statistical approach to get a probability density function (pdf) for the signed distance map of the points inside and outside and also the distribution of gray level inside and outside the object. The proposed statistical approach is based on modelling the empirical density function (normalized histogram of occurrence) for either the gray level distribution or signed distance map with a linear combination of Gaussians (LCG) with positive and negative components. We modify an Expectation-Maximization (EM) algorithm to deal with the LCGs and also propose a novel EM-based sequential technique to get a close initial LCG approximation for the modified EM algorithm to start with. The pdf’s of the signed distance and intensity gray level are embedded in the speed function of the level set specifying the direction of evolution. Experimental results show how the approach is accurate in segmenting different types of 2-D and 3-D data sets including medical images.

关键词： Level set Shape Histograms Approximation algorithms Robustness Partial differential equations Training data Probability density function Density functional theory Gaussian distribution

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CSIFT: A SIFT Descriptor with Color Invariant Characteristics

CSIFT: A SIFT Descriptor with Color Invariant Characteristic...

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Conference on computer vision and Pattern Recognition (CVPR)

作者： A.E. Abdel-Hakim A.A. Farag Computer Vision and Image Processing Laboratory (CVIP) University of Louisville Louisville KY USA

SIFT has been proven to be the most robust local invariant feature descriptor. SIFT is designed mainly for gray images. However, color provides valuable information in object description and matching tasks. Many objects can be misclassified if their color contents are ignored. This paper addresses this problem and proposes a novel colored local invariant feature descriptor. Instead of using the gray space to represent the input image, the proposed approach builds the SIFT descriptors in a color invariant space. The built Colored SIFT (CSIFT) is more robust than the conventional SIFT with respect to color and photometrical variations. The evaluation results support the potential of the proposed approach.

关键词： Colored noise Robustness Histograms Photometry Feature extraction Lighting computer vision image retrieval image processing Laboratories

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Line-Based Affine Invariant Object Location Using Transformation Space Decomposition

Line-Based Affine Invariant Object Location Using Transforma...

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International Conference on Pattern Recognition

作者： R. Yang Yongsheng Gao Computer Vision and Image Processing Laboratory School of Engineering Griffith University Brisbane Australia

This paper presents a novel line-based affine invariant object location methodology. Our algorithm employs a new line-based transformation space decomposition technique to exploit intrinsic structural information provided by line features. Furthermore, we propose a new line-based distance transform to integrate with our algorithm to provide efficient transformation cell evaluation and subdivision in a coarse to fine manner. The algorithm is able to rapidly accelerate the searching process while maintaining high discriminative power and minimal storage requirement. The efficiency and discriminative power of this methodology are demonstrated using real-world examples with promising results

关键词： OFDM modulation image segmentation Object detection computer vision image processing Acceleration Machine vision Detectors Pixel Pattern recognition

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A New Formulation for Shape from Shading for Non-Lambertian Surfaces

A New Formulation for Shape from Shading for Non-Lambertian ...

引用

Conference on computer vision and Pattern Recognition (CVPR)

作者： A.H. Ahmed A.A. Farag Computer Vision and Image Processing Laboratory (CVIP) University of Louisville Louisville KY USA

Lambert’s model for diffuse reflection is a main assumption in most of shape from shading (SFS) literature. Even with this simplified model, the SFS is still a difficult problem. Nevertheless, Lambert’s model has been proven to be an inaccurate approximation of the diffuse component of the surface reflectance. In this paper, we propose a new solution of the SFS problem based on a more comprehensive diffuse reflectance model: the Oren and Nayar model. In this work, we slightly modify this more realistic model in order to take into account the attenuation of the illumination due to distance. Using the modified non-Lambertian reflectance, we design a new explicit Partial Differential Equation (PDE) and then solve it using Lax-Friedrichs Sweeping method. Our experiments on synthetic data show that the proposed modeling gives a unique solution without any information about the height at the singular points of the surface. Additional results for real data are presented to show the efficiency of the proposed method . To the best of our knowledge, this is the first non-Lambertian SFS formulation that eliminates the concave/convex ambiguity which is a well known problem in SFS.

关键词： Shape Reflectivity Cameras Lighting Brightness Optical imaging Light sources Rough surfaces Surface roughness computer vision

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Super-resolution in the presence of space-variant blur

Super-resolution in the presence of space-variant blur

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International Conference on Pattern Recognition

作者： K.V. Suresh A.N. Rajagopalan Image Processing and Computer Vision Laboratory Department of Electrical Engineering IIT Madras Chennai India

An efficient algorithm using maximum a posteriori-Markov random field (MAP-MRF) based approach for recovering a high-resolution image from multiple sub-pixel shifted low-resolution images is proposed. The algorithm can be used for super-resolution of both space-invariant and space-variant blurred images. We prove an important theorem that the posterior is also Markov and derive the exact posterior neighborhood structure in the presence of warping, blurring and down-sampling operations. The posterior being Markov enables us to perform all matrix operations as local image domain operations thereby resulting in a considerable speedup. Experimental results are given to demonstrate the effectiveness of our method

关键词： Spatial resolution image resolution Cameras image processing computer vision Laboratories Layout Frequency domain analysis Markov random fields Reconstruction algorithms

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