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2nd Indian International Conference on Artificial Intelligence, IICAI 2005

作者： Nanda, P.K. Patra, D. Pradhan, A. Department of Electrical Engineering Image Processing and Computer Vision Laboratory National Institute of Technology Rourkela Orissa 769008 India

ISBN: (纸本)0972741216

In this paper, we propose a hybrid Tabu Expectation Maximization (TEM) Algorithm for segmentation of Brain Magnetic Resonance (MR) images in both supervised and unsupervised framewrok. Gaussian Hidden Markov Random Field (GHMRF) is used to model the available degraded image. In supervised framework, the apriori image MRF model parameters as well as the GHMRF model parameters are assumed to be known. The class labels are estimated using the Maximum a Posteriori (MAP) estimation criterion. In unsupervised framework, the problem of model parameter estimation and label estimation is formulated in Expectation Maximization (EM) framework. The labels are estimated using the proposed Tabu Search algorithm while the model parameters are the maximum likelihood estimates. Our proposed algorithm yields results with arbitrary initial paramater set and thus overcomes the problem of proper choice of initial parameters. The results obtained are comparable with the results obtained by using the algorithm proposed by Zhang ***. [15] , where the Iterated Conditional Mode (ICJM) algorithm is used for computing the MAP estimates. Copyright © IICAI 2005.

关键词： Tabu search

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A volumetric 3D model of the human jaw

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International Congress Series 2005年 1281卷 1244-1249页

作者： Hassan, Hossam El-Baz, Ayman Farag, Aly A. Farman, Allan G. Tasman, D. Miller, William M. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY United States Dental School University of Louisville Louisville KY United States

The purpose of this paper is to introduce a detailed approach for constructing a complete model of the human jaw. Our previous work developed an accurate model of the human jaw surface. Unfortunately this surface is not enough for the analysis purpose which requires a detailed model of the teeth and their roots. A database of volumetric 3D models of teeth is constructed from the CT scans. The crown the tooth coming from the shape modeling algorithm provided in our previous work is matched with one of the database teeth. A registration technique is used to deform the matched tooth with our previous derived surface model. Combining this information with the jaw details and X-ray information of the roots, we can now derive a complete volumetric 3D model of the human jaw. This model is suitable for the analysis process which will include finite element work to analyze the stress and strain for different simulations. The simulations processes will include, among others, tooth-implanting and alignment. © 2005.

关键词： Human jaw Registration Segmentation

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2D and 3D shape based segmentation using deformable models

2D and 3D shape based segmentation using deformable models

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8th International Conference on Medical image Computing and computer-Assisted Intervention - MICCAI 2005

作者： El-Baz, Ayman Yuksel, Seniha E. Shi, Hongjian Farag, Aly A. El-Ghar, Mohamed A. Eldiasty, Tarek Ghoneim, Mohamed A. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 Mansoura University Urology and Nephrology Center Mansoura Egypt

ISBN: (纸本)3540293264

A novel shape based segmentation approach is proposed by modifying the external energy component of a deformable model. The proposed external energy component depends not only on the gray level of the images but also on the shape information which is obtained from the signed distance maps of objects in a given data set. The gray level distribution and the signed distance map of the points inside and outside the object of interest are accurately estimated by modelling the empirical density function with a linear combination of discrete Gaussians (LCDG) with positive and negative components. Experimental results on the segmentation of the kidneys from low-contrast DCE-MRI and on the segmentation of the ventricles from brain MRFs show how the approach is accurate in segmenting 2-D and 3-D data sets. The 2D results for the kidney segmentation have been validated by a radiologist and the 3D results of the ventricle segmentation have been validated with a geometrical phantom. © Springer-Verlag Berlin Heidelberg 2005.

关键词： image segmentation

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3D path planning for virtual endoscopy

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International Congress Series 2005年 1281卷 115-120页

作者： Hassouna, M. Sabry Farag, A.A. Hushek, Stephen G. Computer Vision and Image Processing Laboratory (CVIP) University of Louisville Louisville KY 40292 United States iMRI Department Norton Hospital Louisville KY 40202 United States

Centerline extraction of curvilinear objects is a crucial component of virtual endoscopy (VE) because it provides path planning for automatic navigation. In this paper, we present a guided voxel coding (GVC) algorithm that modifies the original method to extract reliable centerlines suitable for fly-through applications. Our proposed method extracts potential centerline voxels with maximal spheres inscribed in the object and stores them in an a priori guidance map. Centerlines are initially extracted as trajectories inside the object and then centered using a new mechanism that exploits the information contained in that map. A new level set method accurately identifies the topological branching nodes of the joint centerlines. Finally, a thinning method is proposed to guarantee single voxel width centerlines. The proposed algorithm is completely automated and generates reliable, connected, and smoothed navigation paths for complex tree structures. © 2005.

关键词： 3D path planning Flight path generation Virtual endoscopy

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Stochastic deformable model

Stochastic deformable model

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2005 16th British Machine vision Conference, BMVC 2005

作者： El-Baz, Ayman Farag, Aly Gimelfarb, Georgy 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

ISBN: (纸本)1901725294

Deformable or active contour, and surface models are powerful image segmentation techniques. We introduce a novel fast and robust bi-directional parametric deformable model which is able to segment regions of intricate shape in multi-modal greyscale images. The power of the algorithm in terms of computation time and robustness is owing to the use of joint probabilities of the signals and region labels in individual points as external forces guiding the model evolution. These joint probabilities are derived from a Markov-Gibbs random field (MGRF) image model considering an image as a sample of two interrelated spatial stochastic processes. The low level process with conditionally independent and arbitrarily distributed signals relates to the observed image whereas its hidden map of regions is represented with the high level MGRF of interdependent region labels. Marginal probability distributions of signals in each region are recovered from a mixed empirical signal distribution over the whole image. In so doing, each marginal is approximated with a linear combination of Gaussians (LCG) having both positive and negative components. The LCG parameters are estimated using our previously proposed modification of the EM algorithm, and the high-level Gibbs potentials are computed analytically. Comparative experiments show that the proposed model outlines complicated boundaries of different modal objects much more accurately than other known counterparts.

关键词： Random processes

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Robust robotic path planning using level sets

Robust robotic path planning using level sets

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IEEE International Conference on image processing

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

In this paper, we propose a general and robust robotic path planning framework for both planar and terrain environments using level set methods. The framework is general in the sense that it can be used for both 2D and 3D environments. It generates a collision-free optimum paths for the entire or a portion of the configuration space. The optimum planned path can be controlled to follow the safest, shortest, or hybrid path. We have demonstrated the robustness of the proposed framework by correctly extracting all planned paths of complex maps with several obstacles.

关键词： Robustness Path planning Orbital robotics Navigation Level set Robot sensing systems Topology computer vision image processing Laboratories

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Virtual Forces for Camera Planning in Smart vision Systems

Virtual Forces for Camera Planning in Smart Vision Systems

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IEEE Workshop on Applications of computer vision (WACV)

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

In this paper, we present a novel and robust approach for camera planning in smart vision systems. The proposed approach uses virtual forces to adjust the camera parameters (pan, tilt, translation ... etc.) toward the most proper values with respect to the application. It employs the physical spring model to direct the motion of the camera toward its target. Our approach is a general framework and any vision system can be easily modeled to use it. This approach has several advantages over previous work in camera planning. It is portable, expandable, robust, and flexible. We present a case study of a two degree-of-freedom stereo vision system to test our approach. The results show the efficiency of our approach even with poor system initialization and its robustness against possible weakness in the auxiliary algorithms used.

关键词： Smart cameras Machine vision Process planning Robustness Sensor systems Sensor phenomena and characterization Application software computer vision Springs System testing

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PDE-based robust robotic navigation

PDE-based robust robotic navigation

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Canadian Conference on computer and Robot vision, CRV

作者： M.S. Hassouna A.E. Abdel-Hakim A.A. Farag Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA

In this paper, we propose a general, robust, and fast path planning framework for robotic navigation using level set methods. A medial point of the map is selected automatically to be a point source that transmits two wave fronts of different speeds. The first front propagates with a moderate speed to capture the map topology, while the second one propagates much faster at medial points such that the safest paths intersect the propagating fronts at those points of maximum positive curvature, which are identified by solving an ordinary differential equation (ODE). The motion of the front is governed by a nonlinear partial differential equation (PDE), which is efficiently solved using robust level set methods. The framework is general in the sense that it can be used for both 2D and 3D environments. It generates a collision-free optimum paths for partial or complete configuration space. Optimum planned paths can be controlled according to the surrounding environment and running conditions in order to follow the safest, shortest, or hybrid paths. We demonstrate the robustness of the proposed method by correctly extracting planned paths of complex maps with several obstacles.

关键词： Robustness Navigation Path planning Orbital robotics Robot vision systems Level set computer vision Topology image processing Laboratories

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Color segmentation using an Eigen color representation

Color segmentation using an Eigen color representation

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International Conference on Information Fusion

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

In real images, color segmentation is a challenging problem because of natural variations in light and shadows. Most existing color models have limitations in distinctive representation of colors in real scenes. Color segmentation approaches are highly dependent on the robustness of the used color model to these variations. In this paper, we present a novel color representation for color segmentation. The proposed model is a fusion of classical color representations. It is calculated using a closed form linear transformation from a high dimensional classical feature space to a lower dimensional new space. We prove the high performance of the proposed model in terms of robustness to natural variations and distinction between different colors, when compared with classical color models. Through color segmentation of real images, we provide a quantitative and qualitative comparison between the proposed model and classical models. The experimental results support the potential of the proposed model.

关键词： image segmentation Robustness computer vision image processing Layout Color Laboratories Application software computer graphics Digital images

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A silhouette-contour based 3-D registration methodology as a pre-evaluation step of 3-D reconstruction techniques

A silhouette-contour based 3-D registration methodology as a...

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IEEE International Conference on image processing

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

Data registration is a crucial step in performance evaluation procedures that aim at localizing errors in given measured data. Under the performance evaluation topic, the probably corrupted measured data should be accurately registered/aligned to the ground truth data such that the registration process would not affect the accuracy of the consequent evaluation steps. To cope with this problem, another registration methodology that can go beyond the conventional ones should be used. Here we propose a novel approach for 3-D data registration. The performance of the approach is totally independent of the measured data set. The key advantage of this approach is that it keeps the registration process away from being affected by the probably corrupted data sets, hence it permits confidential evaluation results.

关键词： Three dimensional displays computer vision Iterative closest point algorithm Application software Iterative algorithms Calibration image processing Laboratories computer errors Object recognition

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