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Novel surface registration using the grid closest point (GCP) transform

引用

IEEE International Conference on image processing

作者： S.M. Yamany M.N. Ahmed E.E. Hemayed A.A. Farag Computer Vision and Image Processing Laboratory Electrical Engineering Department University of Louisville Louisville KY USA

ISBN: (纸本)0818688211

A novel approach has been developed for fast registration of two sets of 3-D curves or surfaces. The technique is an extension of Besl and Mackay's (1992) iterative closest point (ICP) algorithm. This technique solves the computational complexity associated with the ICP algorithm by applying a novel grid closest point (GCP) transform and a genetic algorithm to minimize the cost function. A detailed description of the algorithm is presented along with a comparison of its performance versus several registration techniques. Two applications are presented in this paper. In the first, the algorithm is used to register 2-D head contours extracted from CT/MRI data to correct for possible mis-alignment caused by motion artifacts during scanning. In the second, the algorithm is used to register 3-D segments of the human jaw obtained using the shape from shading technique. Registration using the GCP/GA technique is found to be significantly faster and of comparable accuracy than two popular techniques in the computer vision and medical imaging literature.

关键词： Iterative algorithms Iterative closest point algorithm Computational complexity Genetic algorithms Cost function Head Data mining Computed tomography Magnetic resonance imaging Registers

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Multiresolution sequential edge linking

Multiresolution sequential edge linking

引用

IEEE International Conference on image processing

作者： G.W. Cook E.J. Delp School of Electrical Engineering Computer Vision and Image Processing Laboratory Purdue University West Lafayette IN USA

We describe a multiresolution approach to edge detection using a sequential search algorithm. The use of a multiresolution image pyramid allows the integration of global edge information contained in lower resolutions to guide the sequential search at higher resolutions. As a consequence, the dependence on a priori knowledge of the image edges is greatly reduced. Estimating the sequential search parameters from lower resolution images provides for a more accurate and less costly search of edge paths in the image.

关键词： Joining processes image edge detection image resolution Spatial resolution Pixel computer vision image processing Signal to noise ratio Technological innovation Laboratories

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3D vertebrae segmentation using graph cuts with shape prior constraints

3D vertebrae segmentation using graph cuts with shape prior ...

引用

IEEE International Conference on image processing

作者： Melih S. Aslan Asem Ali Dongqing Chen Ben Arnold Aly A. Farag Ping Xiang University of Louisville Computer Vision and Image Processing Laboratory Louisville KY USA Image Analysis Inc Columbia KY USA

Osteoporosis is a bone disease characterized by a reduction in bone mass, resulting in an increased risk of fractures. To diagnose the osteoporosis accurately, bone mineral density (BMD) measurements and fracture analysis (FA) of the Vertebral bodies (VBs) are required. In this paper, we propose a robust and 3D shape based method to segment VBs in clinical computed tomography (CT) images in order to make BMD measurements and FA accurately. In this experiment, image appearance and shape information of VBs are used. In the training step, 3D shape information is obtained from a set of data sets. Then, we estimate the shape variations using a distance probabilistic model which approximates the marginal densities of the VB and background in the variability region. In the segmentation step, the Matched filter is used to detect the VB region automatically. We align the detected volume with 3D shape prior in order to be used in distance probabilistic model. Then, the graph cuts method which integrates the linear combination of Gaussians (LCG), Markov Gibbs Random Field (MGRF), and distance probabilistic model obtained from 3D shape prior is used.

关键词： Shape image segmentation Three dimensional displays Computed tomography Bones Solid modeling image color analysis

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Parameter estimation and segmentation of noisy or textured images using the EM algorithm and MPM estimation

Parameter estimation and segmentation of noisy or textured i...

引用

IEEE International Conference on image processing

作者： M.L. Comer E.J. Delp Computer Vision and Image Processing Laboratory School of Electrical Engineering Purdue University West Lafayette IN USA

Presents a new algorithm for segmentation of noisy or textured images using the expectation-maximization (EM) algorithm for estimating parameters of the probability mass function of the pixel class labels and the maximization of the posterior marginals (MPM) criterion for the segmentation operation. A Markov random field (MRF) model is used for the pixel class labels. The authors present experimental results demonstrating the use of the new algorithm on synthetic images and medical imagery.< >

关键词： Parameter estimation image segmentation Pixel Markov random fields Probability computer vision image processing Laboratories Tellurium Biomedical imaging

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Improving Shape from Focus Using Defocus Information

Improving Shape from Focus Using Defocus Information

引用

International Conference on Pattern Recognition

作者： K.S. Pradeep A.N. Rajagopalan Image Processing and Computer Vision Laboratory Department of Electrical Engineering Indian Institute of Technology Madras India

ISBN: (纸本)0769525210

Shape from focus (SFF) method determines the degree of focus in a sequence of observations to estimate the shape of a 3-D object. Existing SFF algorithms use an ad hoc interpolation strategy to account for the error due to the finite step-size by which the translational table is moved while capturing the images. We propose an improved SFF method that uses relative defocus blur derived from actual image data to arrive at the final estimates of the shape of the object. A space-variant image restoration scheme is also proposed to obtain a focused image of the 3-D object. The shape estimates as well as the quality of the restored image using the proposed method are superior to that of traditional SFF

关键词： Shape Focusing Cameras Lenses image restoration Interpolation Pixel Polynomials image sensors image processing

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Invariant reconstruction of visual surfaces

Invariant reconstruction of visual surfaces

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Workshop on Interpretation of 3D Scenes

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

This study addresses a problem that arises in the early stages of visual processing. Low-level vision processing tasks generate information describing distances and orientations at sparse locations of visible surfaces in a scene. The information from these various low-level tasks need to be combined to form an estimate of the visual surface for all points in the scene. This step is commonly referred to as the surface reconstruction problem. The problem is cast as an ill-posed inverse problem, which must be stabilized using a priori information relative to image and constraint formation. A desirable property of any reconstruction algorithm is invariance with respect to rigid transformations of the surface in three-dimensional space. Two surface reconstruction algorithms that are based on invariant surface characteristics are proposed. These algorithms are studied in detail, and an example is presented to demonstrate their effectiveness. The discrete realization of the algorithms is also briefly discussed.< >

关键词： Surface reconstruction image reconstruction Layout Reconstruction algorithms Face detection computer vision image processing Laboratories Inverse problems Object recognition

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A fast algorithm for video parsing using MPEG compressed sequences

A fast algorithm for video parsing using MPEG compressed seq...

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IEEE International Conference on image processing

作者： K. Shen E.J. Delp School of Electrical Engineering Computer Vision and Image Processing Laboratory Purdue University West Lafayette IN USA

Video parsing is a fundamental operation used in many digital video applications such as digital libraries and video servers. The accuracy and execution speed of the parsing algorithm is critical if large amounts of video data are to be processed, particularly in real-time. We present a new algorithm to reconstruct DC coefficient images of a DCT and motion compensation compressed video sequence, e.g. MPEG. The histograms of the DC coefficient images can be used to detect scene changes.

关键词： Video compression Transform coding Software libraries image reconstruction Discrete cosine transforms Motion compensation image coding Video sequences Histograms Layout

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3D reconstruction of the human jaw from a sequence of images

3D reconstruction of the human jaw from a sequence of images

引用

Conference on computer vision and Pattern Recognition (CVPR)

作者： M. Ahmed S. Yamany E. Hemayed S. Ahmed S. Roberts A. Farag Computer Vision and Image Processing Laboratory Department of Electrical Engineering University of Louisville Louisville KY USA

A novel approach is proposed to obtain a record of the patient's occlusion using computer vision. Data acquisition is obtained using intra-oral video cameras. The technique utilizes shape from shading to extract 3D information from 2D views of the jaw, and a novel technique for 3D data registration using genetic algorithms. The resulting 3D model can be used for diagnosis, treatment planning, and implant purposes. The overall purpose of this research is to develop a model-based vision system for orthodontics to replace traditional approaches. This system will be flexible, accurate, and will reduce the cost of orthodontic treatments.

关键词： image reconstruction Humans computer vision Data acquisition Cameras Shape Data mining Genetic algorithms Implants Machine vision

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The EM/MPM algorithm for segmentation of textured images: analysis and further experimental results

The EM/MPM algorithm for segmentation of textured images: an...

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IEEE International Conference on image processing

作者： M.L. Comer E.J. Delp Computer Vision and Image Processing Laboratory School of Electrical Engineering Purdue University West Lafayette IN USA

In this paper we present new results relative to the "expectation-maximization/maximization of the posterior marginals" (EM/MPM) algorithm for simultaneous parameter estimation and segmentation of textured images. The goal of the EM/MPM algorithm is to minimize the expected value of the number of misclassified pixels. We present new theoretical results in this paper which show that the algorithm can be expected to achieve this goal, to the extent that the EM estimates of the model parameters are close to the true values of the model parameters. We also present new experimental results demonstrating the performance of the algorithm.

关键词： image segmentation image analysis image texture analysis Algorithm design and analysis Parameter estimation Pixel Stochastic processes computer vision image processing

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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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