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Shape Representation and Registration using Vector Distance Functions

Shape Representation and Registration using Vector Distance ...

引用

Conference on computer vision and Pattern Recognition (CVPR)

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

This paper introduces a new method for shape registration by matching vector distance functions. The vector distance function representation is more flexible than the conventional signed distance map since it enables us to better control the shapes registration process by using more general transformations. Based on this model, a variational frame work is proposed for the global and local registration of shapes which does not need any point correspondences. The optimization criterion can handle efficiently the estimation of the global registration parameters. A closed form solution is provided to handle an incremental free form deformation model for covering the local deformations. This is an advantage over the gradient descent optimization which is biased towards the initialization and is more time consuming. Results of real shapes registration will be demonstrated to show the efficiency of the proposed approach with small and large global/local deformations.

关键词： Shape measurement computer vision Shape control image segmentation Distortion measurement image processing laboratories Closed-form solution Deformable models Biomedical imaging

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Shape from Shading for Hybrid Surfaces

Shape from Shading for Hybrid Surfaces

引用

IEEE International Conference on image processing

作者： Abdelrehim Ahmed Aly Farag Computer Vision and Image Processing Laboratory (CVIP) University of Louisville Louisville KY USA

This paper presents a new method for recovering the shape of hybrid surfaces that have both diffuse reflection and specular reflection using shape from shading (SFS). The image irradiance equation has been derived as an explicit partial differential equation (PDE) under the assumptions of orthographic camera projection and distant point light source. The reflectance model of Ward has been used to express the hybrid reflection as a linear combination from the diffuse and specular components. The resulting PDE is solved using the Lax-Friedrichs sweeping method. The proposed algorithm is evaluated by using both synthetic data and real images and the experimental results show the efficiency of the approach.

关键词： Shape Reflectivity Optical reflection Nonlinear equations Light sources laboratories Layout Partial differential equations Brightness computer vision

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Shape from Shading Under Various Imaging Conditions

Shape from Shading Under Various Imaging Conditions

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Conference on computer vision and Pattern Recognition (CVPR)

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

Most of the shape from shading (SFS) algorithms have been developed under the simplifying assumptions of a Lambertian surface, an orthographic projection, and a distant light source. Due to the difficulty of the SFS problem, only a small number of algorithms have been proposed for surfaces with non-Lambertian reflectance, and among those, only very few algorithms are applicable for surfaces with specular and diffuse reflectance. In this paper we propose a unified framework that is capable of solving the SFS problem under various settings of imaging conditions i.e., Lambertian or non-Lambertian, orthographic or perspective projection, and distant or nearby light source. The proposed algorithm represents the image irradiance equation of each setting as an explicit Partial Differential Equation (PDF). In our implementation we use the Lax-Friedrichs sweeping method to solve this PDF. To demonstrate the efficiency of the proposed algorithm, several comparisons with the state of the art of the SFS literature are given.

关键词： Shape Reflectivity Light sources Partial differential equations Nonlinear equations Cameras Brightness computer vision Differential equations Strips

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A NOVEL FRAMEWORK FOR ACCURATE LUNG SEGMENTATION USING GRAPH CUTS

A NOVEL FRAMEWORK FOR ACCURATE LUNG SEGMENTATION USING GRAPH...

引用

IEEE International Symposium on Biomedical Imaging

作者： Asem M. Ali Ayman S. El-baz Aly A. Farag Computer Vision and Image Processing Laboratory (CVIP) University of Louisville USA Bioengineering Department University of Louisville USA

ISBN: (纸本)9781424406715;1424406714

The closeness of the gray levels between lung tissues and the chest tissues makes lung segmentation based only on image signals difficult. This work proposes an automatic segmentation framework of lung consisting of three stages. First is the image signal modelling, and initial labelling stage. The labelling algorithm is based on a probabilistic model, which models the image signal with a linear combination of Gaussian distributions with positive and negative components. In the second stage a new analytically estimated potentials for Potts model parameter is used to identify the spatial interaction between the neighboring pixels. Finally the third stage, where an energy function using the previous models is formulated, and is globally minimized using s/t graph cuts. Experiments show that the developed technique segments CT lung images more accurately than other known algorithms.

关键词： Lungs image segmentation Computed tomography labeling Pathology Object segmentation Gaussian distribution X-ray imaging Cancer detection computer vision

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A NEW GLOBAL REGISTRATION APPROACH OF MEDICAL IMAGING USING VECTOR MAPS

A NEW GLOBAL REGISTRATION APPROACH OF MEDICAL IMAGING USING ...

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IEEE International Symposium on Biomedical Imaging

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

ISBN: (纸本)1424406714

In this paper, we introduce a novel global image registration approach using vector distance functions (VDF's). Edges of the source and target objects are used to represent their images. The VDF's of these edges are calculated as an implicit representation of these boundaries. An energy is formulated to measure the differences of these vectors. A variational formulation is considered to estimate the transformation parameters. Promising results in 2D and 3D are demonstrated to show the efficiency of the proposed algorithm.

关键词： Biomedical imaging image edge detection image registration Parameter estimation computer vision Mutual information Data mining Shape image processing Energy measurement

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A NEW VARIATIONAL APPROACH FOR 3D SHAPE REGISTRATION

A NEW VARIATIONAL APPROACH FOR 3D SHAPE REGISTRATION

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4th IEEE International Symposium on Biomedical Imaging: Macro to Nano (ISBI'07), vol.3

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

ISBN: (纸本)1424406714

Shape-based approaches became very popular in medical imaging. The key issue in these methods is the shape representation and registration. This paper introduces a new method for the 3D shape registration problem by matching vector distance functions. The vector distance function representation is more flexible than the conventional signed distance map since it enables us to better control the shapes registration process by using more general transformations. Based on this model, a variational frame work is proposed for the global and local registration of shapes which does not need any point correspondences. A gradient descent optimization is used and efficiently can handle both the rigid and the non-rigid operations together. The registration of real 3D human teeth models demonstrates the potential of the proposed approach.

关键词： biomedical measurement dentistry image matching image registration medical image processing physiological models shape measurement variational techniques global shape registration gradient descent optimization human teeth models local shape registration

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CLASSIFICATION TECHNIQUES FOR AUTISTIC VS. TYPICALLY DEVELOPING BRAIN USING MRI DATA

CLASSIFICATION TECHNIQUES FOR AUTISTIC VS. TYPICALLY DEVELOP...

引用

IEEE International Symposium on Biomedical Imaging

作者： Rachid Fahmi Ayman S. El-baz Hossam E. Abd El Munim Aly A. Farag Manuel F. Casanova Computer Vision and Image Processing Laboratory (CVIP Laboratory) University of Louisville USA Bioengineering Department University of Louisville USA Department of Psychiatry and Behavioral Sciences University of Louisville USA

ISBN: (纸本)9781424406715

Autism is a neurodevelopmental disorder that disrupts social and cognitive functions. Various autism studies revealed abnormalities in several brain regions. There is an increasing agreement from structural imaging studies on the abnormal anatomy of the white matter (WM) in autistic brains. In addition, the deficits in the size of the corpus callosum (CC) and its sub-regions in patients with autism relative to controls are well established. This paper presents two novel classification techniques of autism based on structural MRI. Our analysis is based on shape descriptions and geometric models. We compute the 3D distance map to describe the shape of the WM and use it as a statistical feature to discriminate between the two groups. We also use our recently proposed non-rigid registration technique to devise another classification approach by statistically analyzing and comparing the deformation fields generated from registering CC's onto each others. The accuracy of our techniques was tested on postmortem and on in vivo brain MR data. The results are very promising and show that, contrary to traditional methods, the proposed techniques are less sensitive to age and volume effects

关键词： Autism Magnetic resonance imaging Shape computer vision image processing laboratories Biomedical engineering Psychiatry Neuroimaging Pathogens

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A Variational Approach for Shapes Registration Using Vector Maps

A Variational Approach for Shapes Registration Using Vector ...

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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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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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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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