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Shape from Shading Under Various Imaging Conditions

Shape from Shading Under Various Imaging Conditions

引用

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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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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A NEW GLOBAL REGISTRATION APPROACH OF MEDICAL IMAGING USING VECTOR MAPS

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

引用

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 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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Experiments on Sensitivity of Template Matching for Lung Nodule Detection in Low Dose CT Scans

Experiments on Sensitivity of Template Matching for Lung Nod...

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IEEE International Symposium on Signal processing and Information Technology (ISSPIT)

作者： Shireen Y Elhabian Hossam Abd el Munim Salwa Elshazly AlyA. Farag Mohamed Aboelghar Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Urology and Nephrology Center Mansoura University Mansoura Egypt

Template matching is a common approach for detection of lung nodules from CT scans. Templates may take different shapes, size and intensity distribution. The process of nodule detection is essentially two steps: isolation of candidate nodules, and elimination of false positive nodules. The processes of outlining the detected nodules and their classification (i.e., assigning pathology for each nodule) complete the CAD system for early detection of lung nodules. This paper is concerned with the template design and evaluating the effectiveness of the first step in the nodule detection process. The paper will neither address the problem of reducing false positives nor would it deal with nodule segmentation and classification. Only parametric templates are considered. Modeling the gray scale distribution for the templates is based on the prior knowledge of typical nodules extracted by radiologists. The effectiveness of the template matching is investigated by cross validation with respect to the ground truth and is described by hit rate curves indicating the probability of detection as function of shape, size and orientation, if applicable, of the templates. We used synthetic and sample real CT scan images in our experiments. It is found that template matching is more sensitive to additive noise than image blurring when tests conducted on synthetic data. On the sample CT scans small size circular and hollow-circular templates provided comparable results to human experts.

关键词： Lungs Computed tomography Shape image segmentation Design automation Pathology image analysis Signal processing Information technology computer vision

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A NEW VARIATIONAL APPROACH FOR 3D SHAPE REGISTRATION

A NEW VARIATIONAL APPROACH FOR 3D SHAPE REGISTRATION

引用

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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Frequency-Domain Analysis of the Human Brain for Studies of Autism

Frequency-Domain Analysis of the Human Brain for Studies of ...

引用

IEEE International Symposium on Signal processing and Information Technology (ISSPIT)

作者： Hossam Abd el Munim Aly A. Farag Manuel F. Casanova Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Department of Psychiatry and Behavioral Sciences University of Louisville Louisville KY USA

Geometric analysis of normal and autistic human subjects reveal distinctions in deformations in the corpus callosum (CC) that may be used for image analysis-based studies of autism. Preliminary studies showed that the CC of autistic patients is quite distinct from normal controls. We use an implicit vector representation of CC to carry out the registration process which reduces the pose differences between the CC's models. Then the complex Fourier descriptor analysis is used to extract a feature vector of each CC model. This feature is used to build a criteria of discrimination between the normal and autistic subjects. This paper introduces a new method for the 2D shape registration problem by matching vector distance functions. A variational frame work is proposed for the global and local registration of CC's. A gradient descent optimization is used which can efficiently handle both the rigid and the non-rigid operations together. The registration of real CC extracted from MRI data sets demonstrates the potential of the proposed approach. Discrimination results will be demonstrated as well to show the efficiency of the discrimination technique.

关键词： Frequency domain analysis Humans Autism Shape measurement Magnetic resonance imaging computer vision image analysis Information analysis Signal analysis Signal processing

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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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On Cluster Validity Indexes in Fuzzy and Hard Clustering Algorithms for image Segmentation

On Cluster Validity Indexes in Fuzzy and Hard Clustering Alg...

引用

IEEE International Conference on image processing

作者： Moumen El-Melegy E.A. Zanaty Walaa M. Abd-Elhafiez Aly Farag Electrical Department Assiut University Asyut Egypt Computer Science Department Taif University Saudi Arabia Mathematics Department Sohag University Sohag Egypt Computer Vision and Image Processing Laboratory University of Louisville KY USA

This paper addresses the issue of assessing the quality of the clusters found by fuzzy and hard clustering algorithms. In particular, it seeks an answer to the question on how well cluster validity indexes can automatically determine the appropriate number of clusters that represent the data. The paper surveys several key existing solutions for cluster validity in the domain of image segmentation. In addition, it suggests two new indexes. The first one is based on Akaike's information criterion (AIC). While AIC was devoted to other domains such as statistical estimation of model fitting, it is implemented here for the first time as a validation index. The second index is developed from the well-established idea of cross-validation. The existing and new indexes are evaluated and compared on several synthetic images corrupted with noise of varying levels and volumetric MR data.

关键词： Clustering algorithms image segmentation Partitioning algorithms Biomedical imaging Clustering methods computer science Information systems computer vision image processing Fuzzy systems

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