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IEEE Conference on Computer Vision and pattern recognition

作者： Wei Li Lei Zhang David Zhang Guangming Lu Jingqi Yan Biometrics Research Center Dept. of Computing The Hong Kong Polytechnic University Biocomputing Research Center Shenzhen Graduate School Harbin Institute of Technology Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University

ISBN: (纸本)9781424469840;9781424469857

Palmprint verification is a relatively new but promising personal authentication technique for its high accuracy and fast matching speed. Two dimensional (2D) palmprint recognition has been well studied in the past decade, and recently three dimensional (3D) palmprint recognition techniques were also proposed. The 2D and 3D palmprint data can be captured simultaneously and they provide different and complementary information. 3D palmprint contains the depth information of the palm surface, while 2D palmprint contains plenty of textures. How to efficiently extract and fuse the 2D and 3D palmprint features to improve the recognition performance is a critical issue for practical palmprint systems. In this paper, an efficient joint 2D and 3D palmprint matching scheme is proposed. The principal line features and palm shape features are extracted and used to accurately align the palmprint, and a couple of matching rules are defined to efficiently use the 2D and 3D features for recognition. The experiments on a 2D+3D palmprint database which contains 8000 samples show that the proposed scheme can greatly improve the performance of palmprint verification.

关键词： Dermatoglyphics Three Dimensions

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The method of image restoration in the environments of dust

The method of image restoration in the environments of dust

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IEEE International Conference on Mechatronics and Automation

作者： Yuanyu Wang Yuanzong Li Tianxu Zhang Department of Computer Fundamental Education TaiYuan University of Technology TaiYuan China College of Mechanical Engineering TaiYuan University of Technology TaiYuan China Institute for Pattern Recognition and A.I State Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology WuHan China

In order to solve the problem of image degradation caused by dust environments, an image degradation model considering multiple scattering factors caused by dust was first established using the first-order multiple scattering method. Then, a dark channel prior principle was applied to present an image restoration algorithm based on the image degradation model. Finally, a particle swarm optimization algorithm was applied to optimize the atmospheric light and the exposure parameters. This optimization algorithm was established according to the criterion of the image evaluation based on kirsch operator with dual threshold. By using the method an optimistic result of image restoration was obtained. The experimental results have shown that the method not only enhanced luminance and contrast, but also discovered more detail edges information. The method provided a foundation for target recognition in the dust environments.

关键词： image edge detection image restoration Degradation Atmospheric modeling Optical scattering Optical imaging

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Study on the Method of image Restoration in the Environment of Dust

Study on the Method of Image Restoration in the Environment ...

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International Conference on Wireless Communications, Networking and Mobile Computing (WiCom)

作者： Yuanyu Wang Yuanzong Li Tianxu Zhang Department of Computer Fundamental Education Taiyuan University Of Technology Taiyuan China College of Mechanical Engineering Taiyuan University Of Technology Taiyuan China Institute of Pattern Recognition and A.I State Key Laboratory of Image Processing and Intelligent Control HuaZhong University of Science and Technology Wuhan China

In order to solve the problem of image degradation caused by dust environments, an image degradation model considering multiple scattering factors caused by dust was first established using the first-order multiple scattering method. Then, a dark channel prior principle was applied to present an image restoration algorithm based on the image degradation model. Finally, GA optimization algorithm was applied to optimize the atmospheric light and the exposure parameters. This optimization algorithm was established according to the criterion of the image evaluation based on kirsch operator with automatic threshold. By using the method an optimistic result of image restoration was obtained. The experimental results have shown that the method not only enhanced luminance and contrast, but also discovered more detail edges information. The method provided a foundation for target recognition in the dust environments.

关键词： image edge detection image restoration Scattering Degradation Gallium Atmospheric modeling Genetic algorithms

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Prediction of protein folding rates from structural topology and complex network properties

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IPSJ Transactions on Bioinformatics 2010年 3卷 40-53页

作者： Song, Jiangning Takemoto, Kazuhiro Shen, Hongbin Tan, Hao Gromiha, M. Michael Akutsu, Tatsuya Bioinformatics Center Institute for Chemical Research Kyoto University Japan Department of Biochemistry and Molecular Biology Monash University Australia PRESTO Japan Science and Technology Agency Japan Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University China Computational Biology Research Center National Institute of Advanced Industrial Science and Technology Japan

As a fundamental biological problem, revealing the protein folding mechanism remains to be one of the most challenging problems in structural bioinformatics. Prediction of protein folding rate is an important step towards our further understanding of the protein folding mechanism and the complex sequencestructure-function relationship. In this article, we develop a novel approach to predict protein folding rates for two-state and multi-state protein folding kinetics, which combines a variety of structural topology and complex network properties that are calculated from protein three-dimensional structures. To take into account the specific correlations between network properties and protein folding rates, we define two different protein residue contact networks, based on two different scales Protein Contact Network (PCN) and Long-range Interaction Network (LIN) to characterize the corresponding network features. The leave-one-out cross-validation (LOOCV) tests indicate that this integrative strategy is more powerful in predicting the folding rates from 3D structures, with the Pearson's Correlation Coefficient (CC) of 0.88, 0.90 and 0.90 for two-state, multi-state and combined protein folding kinetics, which provides an improved performance compared with other prediction work. This study provides useful insights which shed light on the network organization of interacting residues underlying protein folding process for both two-state and multi-state folding kinetics. Moreover, our method also provides a complementary approach to the current folding rate prediction algorithms and can be used as a powerful tool for the characterization of the foldomics protein data. The implemented webserver (termed PRORATE) is freely accessible at http://***/~sjn/folding/. © 2010 Information processing Society of Japan.

关键词： Forecasting

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Spatial and spectral based segmentation of text in multispectral images of ancient documents

Spatial and spectral based segmentation of text in multispec...

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ICDAR2009 - 10th International Conference on Document Analysis and recognition

作者： Lettner, Martin Sablatnig, Robert Pattern Recognition and Image Processing Group Institute of Computer Aided Automation Vienna University of Technology Austria

ISBN: (纸本)9780769537252

In this paper we propose a character segmentation method for multispectral images of ancient documents. Due to the low quality of the images the main idea of this study is to combine the multispectral behavior and contextual spatial information. Therefore we utilize a Markov Random Field model using the spectral information of the images and stroke properties to include spatial dependencies of the characters. Since the stroke properties and the Gaussian parameters for the imaging model are evaluated automatically the proposed segmentation method requires no training phase. We compared the method to state of the art character segmentation methods and demonstrate the effectiveness of combining spectral and spatial features for the segmentation of characters in multispectral images. © 2009 IEEE.

关键词： image segmentation

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Automated multi-camera surveillance for the prevention and investigation of bank robberies in Austria: A case study

Automated multi-camera surveillance for the prevention and i...

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3rd International Conference on Imaging for Crime Detection and Prevention, ICDP 2009

作者： Zambanini, S. Blauensteiner, P. Kampel, M. Pattern Recognition and Image Processing Group Vienna University of Technology Favoritenstr. 9/1832 1040 Vienna Austria

ISBN: (纸本)9781849192071

In this paper we present the recently granted tripleB-ID project that aims to detect suspicious actions and criminal offences in bank foyers. Based on the situation in Austria and on the actual needs of our partner bank, we deduce scenarios of interest and analyse the technical challenges. As a preliminary work, we furthermore present a fully automated method for the mapping between a static and a dynamic camera and show how this can be used to easily and fast set up a master-slave camera system.

关键词： Mapping

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Multispectral imaging for analyzing ancient manuscripts

Multispectral imaging for analyzing ancient manuscripts

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17th European Signal processing Conference, EUSIPCO 2009

作者： Lettner, Martin Sablatnig, Robert Pattern Recognition and Image Processing Group Institute of Computer Aided Automation Vienna University of Technology 1040 Vienna Austria

In this paper we propose a method for segmenting characters in multispectral images of ancient documents. Due to the low quality of the document images the main idea of our study is to combine the multispectral behavior and contextual spatial information. Therefore we utilize a Markov Random Field model using the spectral information of the images and stroke properties to include spatial dependencies of the characters. The whole process is parameter free since we calculate the stroke properties and the Gaussian parameters for the imaging model automatically. The study shows the effectiveness of using multispectral data for a computer aided analysis of ancient text documents. We compare the results of the proposed segmentation method to traditional methods based on color images as well as gray level images. © EURASIP, 2009.

关键词： Computer aided analysis

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A self-calibration method for smart video cameras

A self-calibration method for smart video cameras

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2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009

作者： Nebehay, Georg Pflugfelder, Roman Pattern Recognition and Image Processing Vienna University of Technology A-1040 Vienna Austria Video and Security Technology Austrian Institute of Technology A-1220 Vienna Austria

ISBN: (纸本)9781424444427

The automatic calibration of the intrinsic camera parameters such as the focal length and the camera orientation is an important pre-requisite for many computer vision algorithms in video surveillance. Despite its importance only a few number of methods show their applicability in embedded systems. This paper shows new results of previous work done in camera self-calibration on images of the York Urban data-set. These 102 images show typical urban scenes one might expect in practice. The evaluation shows that in 52 of 102 images the proposed method achieves less than 5% relative error in the focal length at a mean computation time per image of 14.45 s on a standard PC. We believe that these results show a fair balance between accuracy and computational performance and encourage an embedded implementation on a smart camera. ©2009 IEEE.

关键词： Video cameras

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Automated multi-camera surveillance for the prevention and investigation of bank robberies in Austria: A case study

Automated multi-camera surveillance for the prevention and i...

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3rd International Conference on Imaging for Crime Detection and Prevention (ICDP 2009)

作者： S. Zambanini P. Blauensteiner M. Kampel Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria

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A comparative study of radial basis function neural networks in dynamic clustering algorithm

A comparative study of radial basis function neural networks...

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MIPPR 2009 - pattern recognition and Computer Vision: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Zhou, Peng Li, Dehua Wu, Hong Zeng, Jun Chen, Feng State Key Lab. for Image Processing and Intelligent Control Institute for Pattern Recognition and Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478078

This paper developed two learning procedure, respectively, based on the orthogonal least squares (OLS) method and the "Innovation- Contribution" criterion (ICc) proposed newly. The orthogonal use of the stepwise-regression algorithm of the ICc mages the model structure independent of the selected term sequence and reduces the cluster region further as compared with orthogonal least squares (OLS). as the Bayesian information criteria (BIC) method is incorporate into the clustering process of the ICc, except for the widths of Gaussian functions, it has no other parameter that need tuning ,but the user is required to specify the tolerance ρ, which is relevant to noises and will be difficult to implement in the real system, for the OLS algorithm. The two algorithms are employed to the Radial Basis Function Neural Networks (RBFNN) to compare its performance for different noise nonlinear dynamic systems. Experimental results show that they provide an efficient approximation to the required results for fitting models, but the clustering procedures of the ICc is substantially better solutions than does the OLS. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Radial basis function networks

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