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Canadian Conference on computer and Robot vision, CRV

作者： Hossam Abdelmunim Aly A. Farag Computer & Systems Engineering Department Faculty of Engineering Ain Shams University Cairo Egypt Computer Vision and Image Processing Laboratory Electrical & Computer Engineering Department University of Louisville KY USA

Shape registration is one of the most challenging problems in computer vision and medical imaging. The process is affected by the way the shape is represented and the form of transformation used to move the source shape. Our paper handles the elastic shape registration by combining the incremental free form deformation (IFFD) with the point-based registration technique using the sum of least squares method. The iterative closest point (ICP) algorithm is used as a criteria to establish point correspondences in each level of the IFFD framework. The free form deformation (FFD) is well known in the literature and works by forming a lattice of control points that can move and hence deform the domain grid points smoothly and uniformly under some shape constrains. The control lattice resolution is increased step by step to achieve a satisfactory deformation of the source shape to exactly match the target boundaries. Our point-based registration is based on least squares that measure the Euclidean distance between source and target boundaries in addition to the shape constrains. The minimization gives a closed form solution of the lattice control points positions. Promising results will be demonstrated for closed and open shapes and structures. The approach can also work for structures that contain multiple parts without any problems.

关键词： Shape Lattices Iterative closest point algorithm image resolution Mathematical model Equations Energy resolution

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Performance Bound of Position Estimation in image Matching

Performance Bound of Position Estimation in Image Matching

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2011 International Conference on Advanced Materials in Microwaves and Optics（AMMO 2011）

作者： Bao-shu XU Ze-lin SHI Shenyang Institute of Automation Chinese Academy of Sciences Graduate University of Chinese Academy of Sciences Key Laboratory of Optical-Electronics Information Processing Chinese Academy of Sciences Key Laboratory of Image Understanding and Computer Vision Liaoning Province

Position estimation in image matching is a fundamental step in computer vision and image processing. To deal with the problem of performance prediction, we formulate it under statistical parameter estimation aspect. The lower bound of position estimation variance is obtained based on Cramer-Rao lower bound(CRLB) theory. This paper analyses the impact of noise to 1-D signal matching, derives the lower bound of variance, and then extends it to 2-D image matching. Furthermore, we derive numerical expression that can be computed from observed data. Finally, we use Monte Carlo simulation method to verify the derived analytical expressions. Experimental results show that the derived CRLB is tight to simulation estimated variance. The CRLB can characterize the performance bound of position estimation in image matching.

关键词： Performance prediction image matching Cramer-Rao Lower Bound Fisher information

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Edge direction dispersion and its application in automatic suitable-matching area selection

Edge direction dispersion and its application in automatic s...

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Chinese Control and Decision Conference

作者： Qing-Hai, Ding Xin-Rong, Yu Hai-Bo, Luo Hong-Mei, Liu Research Institute of General Development and Demonstration of Equipment Equipment of Air Force Bejing 100076 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 China Graduate School Chinese Academy of Sciences Beijing 100039 China Key Laboratory of Optical-Electronics Information Processing Chinese Academy of Science Shenyang 110016 China Key Laboratory of Image Understanding Computer Vision Liaoning Province 110016 China AVIC HONGDU Aviation Industry Group Ltd. Nanchang 330024 China

ISBN: (纸本)9781424487363

Automatic suitable-matching area selection is an important research in visual guidance, scene matching and local non-texture target tracking. Meanwhile, it is the major research subject in computer vision and accurate guidance. In this paper, a new characteristic quantity, i.e., the edge direction dispersion was defined. Then the computation method, parameters selection and real-time realization of this characteristic quantity were investigated. Furthermore, the application of its characteristic in automatic suitable-matching area selection was studied. With a reasonable design for calculation precision, solving method for arctan(x) function in [-∞,+∞ ] could be simplified to linearization calculations in [0, 0.25], then a fast algorithm for arctan(x) function was presented. Experimental results showed that the sub-image extracted by our fast algorithm had higher matching level and was suitable to be a matching template. All the calculations involved in the proposed matching algorithm could be done in one filed period and the real-time request could be satisfied. Moreover, this characteristic of edge direction could also be used to measure the comparability of template and real-time images, which could be widely used in automatic target recognition and target tracking. © 2011 IEEE.

关键词： Target tracking

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Variational approach for segmentation of lung nodules

Variational approach for segmentation of lung nodules

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IEEE International Conference on image processing

作者： Amal A. Farag Hossam Abdelmunim James Graham Aly A. Farag Salwa Elshazly Sabry El-Mogy Mohamed El-Mogy Robert Falk Sahar Al-Jafary Hani Mahdi Rebecca Milam Computer Vision and Image Processing Laboratory (CVIP Lab) University of Louisville Louisville KY USA Computer & Systems Engineering Department Faculty of Engineering Ain Shams University Cairo Egypt School of Medicine Mansoura University Egypt FJewish Hospital and 3DR Louisville KY USA Department of Radiology University of Louisville USA

Lung nodules from low dose CT (LDCT) scans may be used for early detection of lung cancer. However, these nodules vary in size, shape, texture, location, and may suffer from occlusion within the tissue. This paper presents an approach for segmentation of lung nodules detected by a prior step. First, regions around the detected nodules are segmented; using automatic seed point placement levels sets. The outline of the nodule region is further improved using the curvature characteristics of the segmentation boundary. We illustrate the effectiveness of this method for automatic segmentation of the Juxta-pleural nodules.

关键词： Lungs image segmentation Computed tomography Level set Shape Conferences Databases

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Extraction of the superficial facial vasculature, vital signs waveforms and rates using thermal imaging

Extraction of the superficial facial vasculature, vital sign...

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2010 IEEE computer Society Conference on computer vision and Pattern Recognition - Workshops, CVPRW 2010

作者： Gault, Travis R. Blumenthal, Nicholas Farag, Aly A. Starr, Tom Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States

ISBN: (纸本)9781424470297

This work deals with non-invasive and non-intrusive measurements of the human facial vasculature from thermal imaging, and estimates the waveforms and rates of the arterial pulse. The paper addresses the issues involved with use of Long-Wave IR imaging in studies of human biometrics, and focuses on measurements of human's heart rate based on a small number of thermal video frames. Infrared videos of 30 subjects were recorded at two distances. Vascular mapping and multi-resolution analysis are used to calculate a subject's heart rate using only 512 Long-Wave IR video frames (17.07 seconds). This semi-automatic process is typically 89-99% accurate, with average accuracies at both distances at approximately 93%. The work is a step in a comprehensive computer vision system for computational studies on humanmachine interface. © 2010 IEEE.

关键词： Infrared imaging

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Unscented transformation for depth from motion-blur in videos

Unscented transformation for depth from motion-blur in video...

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2010 IEEE computer Society Conference on computer vision and Pattern Recognition - Workshops, CVPRW 2010

作者： Paramanand, C. Rajagopalan, A.N. Image Processing and Computer Vision Laboratory Department of Electrical Engineering Indian Institute of Technology Madras Chennai 600 036 India

ISBN: (纸本)9781424470297

In images and videos of a 3D scene, blur due to camera shake can be a source of depth information. Our objective is to find the shape of the scene from its motion-blurred observations without having to restore the original image. In this paper, we pose depth recovery as a recursive state estimation problem. We show that the relationship between the observation and the scale factor of the motion-blur kernel associated with the depth at a point is nonlinear and propose the use of the unscented Kalman filter for state estimation. The performance of the proposed method is evaluated on many examples. © 2010 IEEE.

关键词： State estimation

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Target state estimation based on particle filter

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Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument 2011年第12 SUPPL.期32卷 36-40页

作者： Zhao, Yongting Xiao, Yanghui Tong, Xinxin Zhu, Dan Shenyang Institute of Automation Chinese Acad. of Sci. Shenyang 110016 China Key Laboratory of Optical-Electronics Information Processing Chinese Acad. of Sci. Shenyang 110016 China Key Laboratory of Image Understanding and Computer Vision Liaoning Province Shenyang 110016 China Graduate School of Chinese Acad. of Sci. Beijing 100049 China

A state estimation method based on the particle filter is proposed, and the current statistical model is used. A reasonable method, that discrete the noise distribution coefficient, is proposed. It enhances the state estimation performance of the maneuvering target. Experiments show the effectiveness of the method. In the Kalman filter framework USES the current statistical model of state estimation methods are compared. The experimental results show that this method can not only approximate the optimal estimate, but also has strong robustness of the maneuverability.

关键词： State estimation

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An automated vertebra identification and segmentation in CT images

An automated vertebra identification and segmentation in CT ...

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IEEE International Conference on image processing

作者： Melih S. Aslan Asem Ali Ham Rara Aly A. Farag Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA

In this paper, we propose a new 3D framework to identify and segment VBs and TBs in clinical computed tomography (CT) images without any user intervention. The Matched filter is employed to detect the VB region automatically on axial axis. To identify the VB on coronal and sagittal axis, we use a new developed approach based on 4 points automatically placed on cortical shell. To segment the identified VB, the graph cuts method which integrates a linear combination of Gaussians (LCG) and Markov Gibbs Random Field (MGRF) are used. Then, the cortical and trabecular bones are segmented using local volume growing methods. Experiments on the data sets show that the proposed segmentation approach is more accurate than other known alternatives.

关键词： Bones image segmentation Computed tomography Three dimensional displays Accuracy Spine Biomedical imaging

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Extraction of the superficial facial vasculature, vital signs waveforms and rates using thermal imaging

Extraction of the superficial facial vasculature, vital sign...

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

作者： Travis R. Gault Nicholas Blumenthal Aly A. Farag Tom Starr Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA

关键词： Optical imaging computer vision Humans Heart rate Photothermal effects Pulse measurements Anthropometry Man machine systems Face recognition Wavelet analysis

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Inpainting Large Missing Regions in Range images

Inpainting Large Missing Regions in Range Images

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International Conference on Pattern Recognition

作者： Arnav V Bhavsar A.N. Rajagopalan Image Processing and Computer Vision Laboratory Indian Institute of Technology Madras Chennai India

ISBN: (纸本)9781424475421

We propose a technique to in paint large missing regions in range images. Such a technique can be used to restore degraded/occluded range maps. It can also serve to reconstruct dense depth maps from sparse measurements which can speed up the acquisition. Our method uses the visual cue from segmentation of an intensity image registered to the range image. Our approach enforces that pixels in the same segment should have similar range. Our simple strategy involves plane-fitting and local medians over segments to compute local energies for labeling unknown pixels. Our results exhibit high quality in painting with very low errors.

关键词： Pixel image segmentation computer vision Pattern recognition Spatial resolution Bandwidth Conferences

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