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1st International Workshop on pattern recognition with Support Vector Machines, SVM 2002

作者： In Kim, Kwang Jung, Keechul Kim Hyung, Jin Artificial Intelligence Lab CS Department Korea Advanced Institute of Science and Technology Taejon305-701 Korea Republic of Pattern Recognition and Image Processing Lab CS and Engineering Department Michigan State University East LansingMI48824-1226 United States

ISBN: (纸本)354044016X

This paper presents a novel color texture-based method for object detection in images. To demonstrate our technique, a vehicle license plate (LP) localization system is developed. A support vector machine (SVM) is used to analyze the color textural properties of LPs. No external feature extraction module is used, rather the color values of the raw pixels that make up the color textural pattern are fed directly to the SVM, which works well even in high-dimensional spaces. Next, LP regions are identified by applying a continuously adaptive meanshift algorithm (CAMShift) to the results of the color texture analysis. The combination of CAMShift and SVMs produces not only robust and but also efficient LP detection as time-consuming color texture analyses for less relevant pixels are restricted, leaving only a small part of the input image to be analyzed. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Object detection

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FVC2002: Second fingerprint verification competition

FVC2002: Second fingerprint verification competition

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作者： Maio, D. Maltoni, D. Cappelli, R. Wayman, J.L. Jain, A.K. Biometric System Lab. DEIS University of Bologna via Sacchi 3 47023 Cessna Italy Biometric Test Center College of Engineering San Jose State University San Jose CA 95192 United States Pattern Recognition and Image Processing Laboratory Michigan State University East Lansing MI 48824 United States

Two years after the first edition, a new Fingerprint Verification Competition (FVC2002) was organized by the authors, with the aim of determining the state-of-the-art in this challenging pattern recognition application. The experience and the feedback received from FVC2000 allowed the authors to improve the organization of FVC2002 and to capture the attention of a significantly higher number of academic and commercial organizations (33 algorithms were submitted). This paper discusses the FVC2002 database, the test protocol and the main differences between FVC2000 and FVC2002. The algorithm performance evaluation will be presented at the 16th ICPR. © 2002 IEEE.

关键词： pattern recognition

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Multiple objects segmentation based on Maximum-likelihood Estimation and Optimum Entropy-distribution(MLE-OED)

Proceedings - International Conference on Pattern Recognitio...

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Proceedings - International Conference on pattern recognition 2002年第1期16卷 707-710页

作者： Jun, Xie Tsui, H.T. Deshen, Xia Image Processing and Computer Vision Lab Department of Electronic Engineering Chinese University of Hong Kong Hong Kong Pattern Recognition Lab Department of Computer Science Nanjing University of Sci. and Tech. China

A new method based on MLE-OED is proposed for unsupervised image segmentation of multiple objects which have fuzzy edges. It adjusts the parameters of a mixture of Gaussian distributions via minimizing a new loss function proposed to implement image segmentation based on the image's local spatial information and global intensity distribution properties . The loss function consists of two terms: a local content fitting term, which optimizes the entropy distribution, and a global statistical fitting term, which maximizes the likelihood of the parameters for the given data. The proposed segmentation method was validated by simulated and real examples. Its performance in the experiments is better than those of two popular methods. © 2002 IEEE.

关键词： Object recognition

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FVC2002: Second Fingerprint Verification Competition

FVC2002: Second Fingerprint Verification Competition

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International Conference on pattern recognition

作者： D. Maio D. Maltoni R. Cappelli J.L. Wayman A.K. Jain Biometric System Lab-DEIS University of Bologna Cesena Italy Biometric Test Center College of Engineering San Jose State University Foundation San Jose CA USA Pattern Recognition and Image Processing Laboratory Michigan State University East Lansing MI USA

ISBN: (纸本)076951695X

关键词： Fingerprint recognition Testing Protocols Biometrics image databases pattern recognition Educational institutions image processing Art Feedback

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Application of a genetic algorithm in triangulation of a 3-D object surface

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International Journal of Computers and Applications 2000年第2期22卷 73-77页

作者： Zhenyu, Chen Mbede, J.B. Yan, Zhou Dehua, Li Hanping, Hu State Commn. Res. Open Lab. Image P. Inst. Pattern Recog. Artif. Intell. Huazhong Univ. of Sci. and Technol. 430074 Wuhan China Intelligent Contr. and Robotics Lab. Dept. of Contr. Sci. and Engineering Huazhong Univ. of Sci. and Technol. 430074 Wuhan China Second Artillery Institute Huazhong Univ. of Sci. and Technol. Inst. Pattern Recog. Artif. Intell. Huazhong Univ. of Sci. and Technol. Second Artillery Institute China Wuhan University China Artificial Intelligence Department University of Edinburgh Inst. of AI and Pattern Recognition Huazhong Univ. of Sci. and Technol. China Cogn. Sci. Natl. Key Found. Res. P. Douala University Cameroon Tübingen University Germany Automatic Control Laboratory Darmstadt University Department of Service Cameroon Min. of National Education Robotics Laboratory Huazhong Univ. of Sci. and Technol. Wuhan China Assoc. Connectionnistes These-ACTH Rennes France IEEE Soc. of Robotics and Automation IEEE Society of Control Systems IASTED Assoc. Jeunes Chercheurs Robotique France Navy University of Engineering China Huazhong Univ. of Sci. and Technol. China Department of Computer Science Airforce Radar Acad. of Engineering China Inst. of P.R and AI Huazhong Univ. of Sci. and Technol.

This paper proposes a genetic-based algorithm for surface reconstruction of three-dimension (3-D) objects from a group of contours representing its section plane lines. The algorithm can optimize the triangulation of the surface of 3-D objects with a multi-objective optimization function to meet the needs of a wide range of applications. Further, a new crossover operator for triangulation and a new 3-D quadrilateral mutation operator are also introduced.

关键词： Object recognition

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Normalized separability measures based on likelihood criteria and their properties

Denshi Gijutsu Sogo Kenkyusho Iho/Bulletin of the Electrotec...

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Denshi Gijutsu Sogo Kenkyusho Iho/Bulletin of the Electrotechnical lab.ratory 1999年第7期63卷 1-7页

作者： Saito, Taiichi Object Recognition Lab. Machine Understanding Division Image Processing Analysis of Character Databases

As a multi-thresholding technique for gray images, the maximum likelihood method under the assumption of mixture of normal distributions and the thresholding method considering the quantization error have already been proposed. In this report, separability measures are defined from the likelihood criteria which are used as evaluation functions in these methods. The proposed separability measures are invariant under affine transformations of gray level scale and are normalized to be within values from 0 to 1. Binarization for a gray image whose distribution is uniform is considered. By investigating properties of the separability measures in this case, it is shown that consideration of the quantization error is effective and the defined separability measures are valid.

关键词： Vector quantization

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A PARALLEL COORDINATIVE VISUAL MODEL—THE PLATE PARALLEL RETRIEVAL MODEL(PPRM)

A PARALLEL COORDINATIVE VISUAL MODEL—THE PLATE PARALLEL RET...

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1998 Fourth International Conference Signal processing

作者： Wang Tianzhen Li Zhou Chang Suwen Wu Zhongyi Du ping Image Processing Lab.Wuhan Automative Polytechnical University National lab.of Pattern Recognition Institute of Automation Chinese Academy of Sciences Station Education Commission Laboratory for Image Processing and Intelligent Control China

In this paper,a parallel coordinative visual model—The revised Plate Parallel Retrieval Model(Wang 1994) [1]is presented based on the analysis of the global effect of Chinese Characters and the recent neurobiological researches on the function of neuroglia in learning and *** theory assumes that visual neurons possess the function of memory and retrieval in addition to the commonly recognised function of signal *** supposes all the pixels on the array of a Chinese character are encoded,stored and relieved simultaneously and sychronously by each neuron separately.

关键词： A PARALLEL COORDINATIVE VISUAL MODEL THE PLATE PARALLEL RETRIEVAL MODEL

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A Region-Based Representation of images in MARS

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Journal of VLSI Signal processing Systems for Signal, image, and Video Technology 1998年第1-2期20卷 137-150页

作者： Servetto, Sergio D. Rui, Yong Ramchandran, Kannan Huang, Thomas S. Beckman Inst. Adv. Sci. and Technol. Univ. Illinois at Urbana-Champaign Urbana IL 61801 United States Universidad Nacional de La Plata Argentina Univ. Illinois at Urbana-Champaign United States Comp. Res. Adv. Applications Group IBM Argentina Argentina Image Formation and Processing Group Beckman Institute UIUC United States Department of Computer Science UNLP Argentina Dept. of Elec. and Comp. Engineering UIUC United States Multimedia Commun. Res. Department Bell Laboratories Murray Hill NJ United States Info. Sciences Research Department AT and T Labs. Florham Park NJ United States Department of Computer Science UIUC United States Southeast University China Tsinghua University China University of Illinois Urbana-Champaign IL United States Image Formation and Processing Group Beckman Inst. Advance Sci. Technol. UIUC United States Vis. Technol. Grp. of Microsoft Res. Redmond WA United States City College of New York United States Columbia University United States AT and T Bell Labs. United States Ctr. for Telecommunications Research Columbia University United States Elec. and Comp. Eng. Department United States Beckman Institute Coordinated Science Laboratory IL United States IEEE Signal Processing Society United States IEEE IMDSP Technical Committee United States IEEE Transactions on Image Proc. United States National Taiwan University Taipei Taiwan Massachusetts Inst. of Technology Cambridge MA United States Department of Electrical Engineering MIT United States School of Electrical Engineering United States Lab. for Info. and Signal Processing Purdue University United States Dept. of Elec. and Comp. Engineering United States Coordinated Science Laboratory United States Image Formation and Processing Group Beckman Inst. Adv. Sci. and Technol. United States MIT Lincoln Laboratory IBM Thomas J. Watson Research Center Rheinishes Landes Museum Bonn Germany Swiss Institutes of Technology Zurich Switzerland Swiss Institutes of Technology Lausanne S

We study the problem of representing images within a multimedia Database Management System (DBMS), in order to support fast retrieval operations without compromising storage efficiency. To achieve this goal, we propose new image coding techniques which combine a wavelet representation, embedded coding of the wavelet coefficients, and segmentation of image-domain regions in the wavelet domain. A bitstream is generated in which each image region is encoded independently of other regions, without having to explicitly store information describing the regions. Simulation results show that our proposed algorithms achieve coding performance which compares favorably, both perceptually and objectively, to that achieved using state-of-the-art image/video coding techniques while additionally providing region-based support.

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On integration of vision modules

On integration of vision modules

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IEEE Computer Society Conference on Computer Vision and pattern recognition Workshops (CVPRW)

作者： Pankanti Jain Tuceryan Pattern Recognition and Image Proc. Lab. Michigan State University East Lansing MI USA European Computer-Industry Research Centre Munchen Germany

Individual cues from visual modules are fallible and often ambiguous. As a result, only integrated vision systems can be expected to give a reliable performance in practice. The design of such systems is challenging since each vision module works under different and possibly conflicting sets of assumptions. We have proposed and implemented a multiresolution system which integrates perceptual grouping, segmentation, stereo, shape from shading, and line lab.lling modules. The output of the integrated system is shown to be relatively insensitive to the constraints imposed by the individual modules.< >

关键词： Machine vision image segmentation Stereo vision

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Texture analysis in the presence of speckle noise 12

Texture analysis in the presence of speckle noise

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12th Annual International Geoscience and Remote Sensing Symposium, IGARSS 1992

作者： Schistad, Anne H. Jain, Anil K. Norwegian Computing Center P.O. Box 114 Blindern Oslo 3N-0314 Norway Pattern Recognition and Image Processing Lab. Computer Science Department Michigan State University East LansingMI48824 United States

ISBN: (纸本)0780301382

We investigate the performance of selected texture models for the purpose of land use classification. The texture models are evaluated based on the resulting classification error rates. Three classes of texture models are evaluated: fractal models, lognormal random fields and grey level co-occurrence matrices. The effect of filtering and noise transformation is investigated. The lognormal random field model gives the best performance. © IEEE 1992.

关键词： Land use

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