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Camera Calibration for 3D Color Scanning System Using Virtual 3D Model

Computer Aided Drafting,Design and Manufacturing 2007年第2期17卷 77-81页

作者： SUN Xian-bin LI De-hua YIN Jie YAO Xun State Key Laboratory for Image Processing and Intelligent Control Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Hubei University of Technology Wuhan 430068 China

Instead of traditionally using a 3D physical model with many control points on it, a calibration plate with printed chess grid and movable along its normal direction is implemented to provide large area 3D control points with variable Z values. Experiments show that the approach presented is effective for reconstructing 3D color objects in computer vision system.

关键词： computer vision 3D scan camera calibration calibration plate

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Remote sensing image matching based on corner structures

Remote sensing image matching based on corner structures

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International Conference on image and Graphics (ICIG)

作者： Hongya Tuo Zhongliang Jing Yuncai Liu Institute of Aerospace Sci. & Tech. Shanghai Jiaotong University Shanghai China Inst. of Image Processing & Pattern Recognition Shanghai Jiaotong University Shanghai China

In this paper, we propose a matching method for remote sensing images based on corner structures. Firstly corner angle vector is defined to analysis corner structure, and the process of how to obtain it is discussed in detail. Then some measures are given to eliminate the false corners. Finally a relaxation matching scheme is presented. The experiments show the effectiveness and feasibility of our matching method.

关键词： Remote sensing image matching Arm Computer vision Detectors Bismuth pattern recognition image edge detection Graphics image processing

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Color Active Contour Models Based Tongue Segmentation in Traditional Chinese Medicine

Color Active Contour Models Based Tongue Segmentation in Tra...

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The 1st International Conference on Bioinformatics and Biomedical Engineering(iCBBE 2007)(首届IEEE生物信息与生物医学工程国际会议)

作者： Jie Yang Yonggang Wang Shengyang Yu Yan Zhang Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Dept.of Dept of Computer Science Nanjing University of Science & Technology Nanjing China

Automated tongue image segmentation in tongue diagnosis system of traditional Chinese medicine is difficult due to two factors: There are lots of pathological details on the surface of tongue, and the shapes of tongue bodies are quite different By adequately considering color information of tongue images, knowledge-based initial tongue body boundary detection and a color gradient are introduced into the gradient vector flow snake. The roughly detected tongue body boundary is employed to lead the usage of color gradient and the convergence of *** experiments results show robustness and accuracy of the algorithm. This work establishes a solid foundation for feature analysis of tongue diagnosis.

关键词： tongue diagnosis tongue segmentation gradient vector flow (GVF) color gradient active contours

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A comparision of Model-based methods for knee cartilage segmentation

A comparision of Model-based methods for knee cartilage segm...

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2nd International Conference on Computer Vision Theory and Applications, VISAPP 2007

作者： Cheong, J. Faggian, N. Langs, G. Suter, D. Cicuttini, F. Dept. of Electrical Dept. of Computer Systems Engineering Monash University Australia Clayton School of Information Technology Monash University Australia Institute for Computer Graphics and Vision Graz University of Technology Austria Pattern Recognition and Image Processing Group Vienna University of Technology Austria Dept. of Epidemiology Dept. of Preventive Medicine Monash University Australia

Osteoarthritis is a chronic and crippling disease affecting an increasing number of people each year. With no known cure, it is expected to reach epidemic proportions in the near future. Accurate segmentation of knee cartilage from magnetic resonance imaging (MRI) scans facilitates the measurement of cartilage volume present in a patient's knee, thus enabling medical clinicians to detect the onset of osteoarthritis and also crucially, to study its effects. This paper compares four model-based segmentation methods popular for medical data segmentation, namely Active Shape Models (ASM) (Cootes et al., 1995), Active Appearance Models (AAM) (Cootes et al., 2001), Patch-based Active Appearance Models (PAAM) (Faggian et al., 2006), and Active Feature Models (AFM) (Langs et al., 2006). A comprehensive analysis of how accurately these methods segment human tibial cartilage is presented. The results obtained were benchmarked against the current "gold standard" (cartilage segmented manually by trained clinicians) and indicate that modeling local texture features around each landmark provides the best results for segmenting human tibial cartilage.

关键词： Medical imaging

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Face recognition System Using Ant Colony Optimization-Based Selected Features

Face Recognition System Using Ant Colony Optimization-Based ...

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IEEE Symposium on Computational Intelligence in Security and Defense Applications, CISDA

作者： Hamidreza Rashidy Kanan Karim Faez Mehdi Hosseinzadeh Image Processing and Pattern Recognition Laboratory Electrical Engineering Department Tehran Polytechnic Amirkabir University of Technology슠 Tehran Iran Department of Computer Engineering University of Isfahan Isfahan Iran

Feature selection (FS) is a most important step which can affect the performance of pattern recognition system. This paper presents a novel feature selection method that is based on ant colony optimization (ACO). ACO algorithm is inspired of ant's social behavior in their search for the shortest paths to food sources. In the proposed algorithm, classifier performance and the length of selected feature vector are adopted as heuristic information for ACO. So, we can select the optimal feature subset without the priori knowledge of features. Simulation results on face recognition system and ORL database show the superiority of the proposed algorithm

关键词： Face recognition Ant colony optimization Discrete wavelet transforms pattern recognition Artificial intelligence Particle swarm optimization Computational intelligence Computer security Application software image processing

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A CI feature-based pulmonary nodule segmentation using three-domain mean shift clustering

A CI feature-based pulmonary nodule segmentation using three...

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International Conference on Wavelet Analysis and pattern recognition (ICWAPR)

作者： Sheng-Dong Nie Li-Hong LI Zhao-Xue Chen Institute of Medical Imaging Engineering School of Medical Instrumentation & Foodstuff University of Shanghai for Science and Technology Shanghai China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University China

A novel and more effective algorithm used for segmenting pulmonary nodules in thoracic spiral CT images was presented. The algorithm is based on mean shift clustering method and CI (Convergence Index) features, which can represent the multiple Gaussian model of pulmonary nodules both for solid and sub-solid, substantially. The algorithm has the following steps: (1) calculating the CI features of all pixels in the region of interest (ROI), (2) combining the CI features with the intensity range and the spatial position of the pixels to form a feature vector set, (3) grouping the feature vector set to clusters with mean shift clustering algorithm. Owing to our algorithm can represent the multiple Gaussian model both for solid and sub-solid nodules, it can be used in any user interested nodule regions, especially suitable for the segmentation of sub-solid nodules. Experiments demonstrated that our algorithm can figure out the outline of pulmonary nodules of different forms more precisely.

关键词： Clustering algorithms image segmentation Lungs Computed tomography Cancer pattern recognition Biomedical imaging Solid modeling Wavelet analysis image analysis

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Reducing the power consumption in the EL displays

Reducing the power consumption in the EL displays

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作者： Kang, Hao Li, Rongyu Yang, Xin Xiao, Tian Department of Electronic and Engineering Shanghai Jiaotong University Shanghai 200240 China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200240 China Flat Panel Display Technology R and D Center SVA Electron Co. Ltd. 196 Ouyang Rd. Shanghai 200081 China

ISBN: (纸本)9787561752289

In the Electroluminescent display panels, the largest portion of power consumption of data driver circuits comes from charging and discharging quite large capacitive loads, data lines. The proposed multi-steps data driving method can reduce the panel AC power consumption into only a few percent of that of conventional ones if the number of steps is large enough. In the proposed driving method, external capacitors supply charge to loads in multi-steps manner, and the charge returns to the capacitors instead of being discharged to ground. This charge recycling is the basis of reduction of the panel AC power. In this paper, the author gives a hardware implementation of 4-steps voltage generator with a minimum complexity.

关键词： Electric power utilization

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Watermarking Polygonal Lines Using V-Descriptors

Watermarking Polygonal Lines Using V-Descriptors

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International Conference on Pervasive Computing and Applications (ICPCA)

作者： Xiaoyun Tie Jiancheng Zou Wenqi Zhong Dongxu Qi Institute of Image Processing and Pattern Recognition North-China University of Technology Beijing China North China University of Technology Beijing Beijing CN Macau University of Science and Technology Macau Macao China

Based on the V-descriptors, a novel watermarking algorithm to protect the copyright of vector images is proposed in this paper. Watermarks are embedded in the image's contours. Experiments show that the algorithm ... 详细信息

关键词： Watermarking Graphics Signal processing algorithms Protection Polynomials Streaming media Robustness Geographic Information Systems image processing pattern recognition

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Multi-label image segmentation via max-sum solver

Multi-label image segmentation via max-sum solver

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Conference on Computer Vision and pattern recognition (CVPR)

作者： Banislav Micusik Tomas Pajdla Pattern Recognition and Image Processing Group Inst. of Computer Aided Automation University of Technology Vienna Austria Center for Machine Perception Dpt. of Cybernetics Czech Technical University Czech Republic

We formulate single-image multi-label segmentation into regions coherent in texture and color as a MAX-SUM problem for which efficient linear programming based solvers have recently appeared. By handling more than two labels, we go beyond widespread binary segmentation methods, e.g., MIN-CUT or normalized cut based approaches. We show that the MAX-SUM solver is a very powerful tool for obtaining the MAP estimate of a Markov random field (MRF). We build the MRF on superpixels to speed up the segmentation while preserving color and texture. We propose new quality functions for setting the MRF, exploiting priors from small representative image seeds, provided either manually or automatically. We show that the proposed automatic segmentation method outperforms previous techniques in terms of the global consistency error evaluated on the Berkeley segmentation database.

关键词： image segmentation image databases Belief propagation pattern recognition image processing Automation Cybernetics Color Linear programming Markov random fields

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Robust real-time tracking for visual surveillance

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Eurasip Journal on Advances in Signal processing 2007年 2007卷

作者： Thirde, David Borg, Mark Aguilera, Josep Wildenauer, Horst Ferryman, James Kampel, Martin School of Systems Engineering Computational Vision Group University of Reading Reading RG6 6AY United Kingdom Computer Science Department Pattern Recognition and Image Processing Group Vienna University of Technology Vienna 1040 Austria

This paper describes a real-time multi-camera surveillance system that can be applied to a range of application domains. This integrated system is designed to observe crowded scenes and has mechanisms to improve tracking of objects that are in close proximity. The four component modules described in this paper are (i) motion detection using a layered background model, (ii)object tracking based on local appearance, (iii) hierarchical object recognition, and (iv) fused multisensor object tracking using multiple features and geometric constraints. This integrated approach to complex scene tracking is validated against a number of representative real-world scenarios to show that robust, real-time analysis can be performed. Copyright © 2007 Hindawi Publishing Corporation. All rights reserved.

关键词： Tracking (position)

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