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International Conference on Information Technology and Applications, ICITA

作者： Xiaoyan Yuan Pengfei Shi Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

ISBN: (纸本)0769523161

Iris feature extraction is the crucial stage of the whole iris recognition process for personal identification. A brief survey is made firstly in this paper on the methods that feasibly implemented in iris feature extraction. Because the iris capture devices in use are mostly exposed to the natural scene, so the natural illumination or other variant conditions sometimes can greatly influence the iris images captured and further impact the recognition result. Out of this consideration, we made some experimental try to extract the iris feature using the 2D phase congruency, which invariant to changes in intensity or contrast, to try to avoid those problems

关键词： Feature extraction Frequency Wavelet packets Gabor filters Humans image processing Iris recognition Biometrics Data mining pattern recognition

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Motion segmentation of multiple translating objects using line correspondences

Motion segmentation of multiple translating objects using li...

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Conference on Computer Vision and pattern recognition (CVPR)

作者： Fanhuai Shi Jianhua Wang Jing Zhang Yuncai Liu Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

ISBN: (纸本)0769523722

We present an algebraic approach to multibody motion segmentation from line correspondences. Given three perspective views containing multiple linearly moving objects, we demonstrate that after applying a polynomial embedding to the line correspondences, they became related by the so-called multibody line constraint of translational motions. We show how to linearly estimate the multibody trifocal epipole from line-line-line correspondences. The individual trifocal epipoles are then obtained from the derivatives of the multibody line constraint (up to an unknown factor). Given normalized trifocal epipoles, we can use any special clustering technique to obtain the clustering of the motions and the correspondences. The limitations of the proposed algorithm are also discussed. Experimental results on synthetic and real dynamic scenes are presented.

关键词： Motion segmentation Computer vision Layout Motion estimation Cameras pattern recognition Polynomials Clustering algorithms image motion analysis Motion analysis

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Study on Performances of Car-following Models Induced by Motions of a Leading Car

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Journal of Shanghai Jiaotong University(Science) 2005年第3期E-10卷 217-220页

作者： LI Li SHI Peng-fei Inst.of Image Processing and Pattern Recognition Shanghai Jiaotong Univ.Shanghai 200030China

This paper investigated the performances of a well-known car-following model with numerical simulations in describing the deceleration process induced by the motion of a leading car. A leading car with a pre-specified speed profile was used to test the above model. The results show that this model is to some extent deficient in performing the process aforementioned. Modifications of the model to overcome these deficiencies were demonstrated and a modified car-following model was proposed accordingly. Furthermore, the delay time of car motion of the new model were studied.

关键词： car-following models leading car linear stability delay time

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Segmentation of players and team discrimination in soccer videos

Segmentation of players and team discrimination in soccer vi...

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IEEE International Workshop on VLSI Design and Video Technology, IWVDVT

作者： Zhifei Xu Pengfei Shi Institute of image processing and pattern recognition Shanghai Jiaotong University Shanghai China

ISBN: (纸本)0780390059

In this paper, we introduce methods to extract low-level features for soccer video analysis. A new method is proposed to segment players by using a mean distributed color feature. In order to discriminate which team the player belongs to, we use mutual chromatic correlation degree of players to identify team without extracting templates of players in advance. Experimental results are included to show the effectiveness of the method.

关键词： Videos image segmentation Lighting Games Pixel Colored noise Feature extraction image analysis Event detection image processing

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Background suppression based-on wavelet transformation to detect infrared target

Background suppression based-on wavelet transformation to de...

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International Conference on Machine Learning and Cybernetics, ICMLC 2005

作者： Sun, Y.U.-Qiu Tian, Jin-Wen Liu, Jian School of Information and Mathematics Yangtze University Jingzhou 434023 China State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China State Education Commission Key Laboratory for Image Processing and Intelligent Control Dept. of Electronic Information and Enginery Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)078039092X

Target detection and location in infrared clutter background is very important to infrared search and track system. Especially for small target detection in infrared image in background of sea and sky, there are no geometric and structure character to use. When targets such as ship and naval vessel sailing at long distance, they always appear around the sea-level line, and it is mixed with cloud and sea-wave clutter. It is difficult to segment and locate precisely. Background suppression based-on wavelet transformation is proposed in the paper. Wavelet decomposition makes it possible to analyze a signal both in time and frequency domains. In the paper infrared sea and key background images are processed. For their SNR is low and background is complex, using wavelet transformation decomposes an original image and extract approximate feature to reconstruct an image, which mainly includes background information. A new image will be obtained using background image subtracted from original image. There are mainly target and noise points left in the new image. By setting proper threshold, the target can be detected perfectly. At last, experiment results are given and show the method is practical. © 2005 IEEE.

关键词： pattern recognition

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A Smart Mathematic Morphology Method for recognition and Understanding of Airfield

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Wuhan University Journal of Natural Sciences 2005年第5期10卷 867-872页

作者： WANG Zhi-cheng TIAN Yan TIAN Jin-wen LIU Jian LIANG Chao-sheng TAO Wen-bin State Education Commission Key Laboratory for Image Processing and Intelligence Control Huazhong University of Science and Technology Wuhan430074 Hubei China Department of Electronics and Information Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 Hubei China

A method used for recognition and understanding of airfield based on mathematical morphology is proposed in this paper. The new approach can he divided into three steps. First, to extract the typical geometric structure features of airfield, a segmentation method called recursive Otsu algorithm is employed on an airfield image. Second, thinning and shrinking algorithms are utilized to obtain the contour of airfield with single pixel and to remove diffused small particles. Finally, Radon transform is adopted to extract two typical and important components, primary and secondary runways of airfield exactly. At the same time, region growing algorithm is exploited to get the other components such as parking apron and garages. The experimental results demonstrate that the proposed method gives good performance.

关键词： mathematical morphology shrinking algorithm Radon transform Region growing

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Efficient VLSI architecture for multi-dimensional discrete wavelet transform

Efficient VLSI architecture for multi-dimensional discrete w...

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MIPPR 2005: SAR and Multispectral image processing

作者： Xiong, Cheng-Yi Tian, Jin-Wen Liu, Jian College of Electronic Information Engineering South-Center University for Nationalities Wuhan 430074 China Institute of Pattern Recognition and Artificial Intelligence Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

Efficient VLSI architectures for multi-dimensional (m-D) discrete wavelet transform (DWT), e.g. m=2, 3, are presented, in which the lifting scheme of DWT is used to reduce efficiently hardware complexity. The parallelism of 2 m subbands transforms in lifting-based m-D DWT is explored, which increases efficiently the throughput rate of separable m-D DWT. The proposed architecture is composed of m2m-1 1-D DWT modules working in parallel and pipelined, which is designed to process 2m input samples per clock cycle, and generate 2m subbands coefficients synchronously. The total time of computing one level of decomposition for a 2-D image (3-D image sequence) of size N2 (MN2) is approximately N2/4 (MN2/8) intra- clock cycles (ccs). An efficient line-based architecture framework for both 2D+t and t+2D 3-D DWT is first proposed. Compared with the similar works reported in previous literature, the proposed architecture has good performance in terms of production of computation time and hardware cost. The proposed architecture is simple, regular, scalable and well suited for VLSI implementation.

关键词： VLSI circuits

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Modulation Classification Based on Spectrogram

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Journal of Systems Engineering and Electronics 2005年第3期000卷 475-488页

作者： Yang Jie Ye Chenzhou Zhou Yue Inst.of Image Processing & Pattern Recognition，Shanghai Jiaotong Univ.，Shanghai 200030，P.R.China

The aim of modulation classification (MC) is to identify the modulation type of a communication signal. It plays an important role in many cooperative or noncooperative communication applications. Three spectrogram-based modulation classification methods are proposed. Their reccgnition scope and performance are investigated or evaluated by theoretical analysis and extensive simulation studies. The method taking moment-like features is robust to frequency offset while the other two, which make use of principal component analysis (PCA) with different transformation inputs,can achieve satisfactory accuracy even at low SNR (as low as 2 dB). Due to the properties of spectrogram, the statistical pattern recognition techniques, and the image preprocessing steps, all of our methods are insensitive to unknown phase and frequency offsets, timing errors, and the arriving sequence of symbols.

关键词： modulation classification spectrogram image processing principal component analysis support vector machine

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Global Motion Estimation with Gabor Wavelet Transform

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Journal of Systems Engineering and Electronics 2005年第3期000卷 645-650页

作者： Wang Peng Liu Chongqing Inst.of Image Processing & Pattern Recognition，Shanghai Jiaotong Univ.，Shanghai 200030，P.R.China

A novel algorithm of global motion estimation is proposed. First, through Gabor wavelet transform (GWT), a kind of energy distribution of image is obtained and checkpoints are selected according to a probability decision approach proposed. Then, the initialized motion vectors are obtained via a hierarchal block-matching based on these ***, by employing a 3-parameter motion model, precise parameters of global motion are found. From the experiment, the algorithm is reliable and robust.

关键词： global motion estimation Gabor wavelet transform probability decision block-matching

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Two-band Infrared Data Fusion Method Based-on Fractal Dimension

Two-band Infrared Data Fusion Method Based-on Fractal Dimens...

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2005 International Conference on Neural Networks and Brain(ICNN&B’05)

作者： Yuqiu Sun Jinwen Tian Jian Liu Image Processing and Intelligence Control Key Laboratory of State Educational Ministry Institute of Pattern Recognition and Artificial IntelligenceHuazhong University of Science and Technology School of information and mathematics Yangtze University Dept.of Electronic Information and Enginery of Huazhong University of Science and Technology

ISBN: (纸本)0780394224

＜正＞Researches indicate that the gray-scale images mapped from most nature objects accord to the fractal Brown stochastic field which foundation is self-similarity,an image is self-similarity means the image is made up of copies of itself in a reduced *** fractal dimension can quantificational depict the fractal character and the property of an image. Therefore,a new method based-on fractal dimension to fuse mid-wave infrared images and long-wave infrared images is presented in the ***,images are decomposed into different scale using wavelet ***,the fractal dimensions of sub-images of original images are computed,and then take them as weight to fuse sub-images at the same level according to different ***,reconstruct the fused images by wavelet inverse *** experimental results imply that the method can effectively preserve the information of source images with a high contrast and may be very practical.

关键词： Fractals Infrared imaging Artificial intelligence Fuses Educational technology image reconstruction Layout Infrared detectors Intelligent control Process control

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