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International Conference on Artificial Reality and Telexistence (ICAT)

作者： Xianyong Fang Fuli Wu Bin Luo Haifeng Zhao Peng Wang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China College of Information Engineering Zhejiang University of Technology China Motorola China Electronics Limited Corporation China

Barcode has been widely applied in the modern world. This paper presents a fast and robust recognition method of noisy code 39 barcode. The proposed method can be divided into two steps: search and decoding. In the first step, all asterisks in the image are found with evenly defined scan lines and then those with the same directions are matched together to get a valid barcode region. In the second step, a local denoise method is first applied to eliminate noise in the barcode region and then a middle band filter is used to decode the barcode. Our method is simple in comparison with former methods and experimental results show that it is efficient for fast barcode recognition on noisy images.

关键词： Decoding Bars Image edge detection Robustness Equations Low pass filters signal processing educational institutions educational technology Image recognition

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Granular Analysis of Time Sequence Based on Quotient Space

Granular Analysis of Time Sequence Based on Quotient Space

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International Conference on Computational Intelligence for Modelling, Control and Automation, and International Conference on intelligent Agents, Web Technologies and Internet Commerce

作者： Liquan Zhao Ling Zhang Bo Zhang Province Key Laboratory of Electronic Business Nanjing University of Finance and Economics Nanjing China Key Laboratory of Intelligent Computing & Signal Processing of Ministry of Education Anhui University Hefei China Computer Science Department Tsinghua University Beijing China

This paper aims to carry out granular analysis of time sequence based on quotient space. Granular methods have long before been adopted to analyze time sequence, but the granularity was based on time, for example, day mean, month mean, year mean and so on in finance forecast. In this paper, the granularity is based on space and some significant results are obtained: we can, in certain circumstances, get characteristics of time sequence in an original space when carrying out granular analysis of it in its coarser-grain space; granular analysis of a Markov chain is equivalent to an hidden Markov model (HMM), contrarily, any HMM is equivalent to granular analysis of a Markov chain. These results deepened our understanding of HMM from the perspective of granular analysis. We can not only use the methods of HMM to study time sequence, but also use the methods of granular analysis based on quotient space theory to solve the problems of HMM.

关键词： Hidden Markov models lab.ratories Artificial intelligence signal analysis Finance signal processing Computer science education Space technology Computational intelligence Economic forecasting

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Bayesian-based Wavelet Shrinkage for SAR Image Despeckling Using Cycle Spinning

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Journal of Electronic Science and Technology 2006年第2期000卷 127-131页

作者： ZHANG De-xiang GAO Qing-wei CHEN Jun-ning Key Lab. Of Intelligent Computing and Signal Processing Anhui University Hefei 230039 China School of Electronic Science and Technology Anhui University Hefei 230039 China School of Electronic Science and Technology Anhui University Hefei 230039 China

A novel and efficient speckle noise reduction algorithm based on Bayesian wavelet shrinkage using cycle spinning is proposed. First, the sub-band decompositions of non-logarithmically transformed SAR images are shown. Then, a Bayesian wavelet shrinkage factor is applied to the decomposed data to estimate noise-free wavelet coefficients. The method is based on the Mixture Gaussian Distributed (MGD) modeling of sub-band coefficients. Finally, multi-resolution wavelet coefficients are reconstructed by wavelet-threshold using cycle spinning. Experimental results show that the proposed despeckling algorithm is possible to achieve an excellent balance between suppresses speckle effectively and preserves as many image details and sharpness as possible. The new method indicated its higher performance than the other speckle noise reduction techniques and minimizing the effect of pseudo-Gibbs phenomena.

关键词： discrete wavelet transform Synthetic Aperture Radar (SAR) despeckling cycle spinning BayesShrink

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Generalizing quotient space theory from structural viewpoint

Generalizing quotient space theory from structural viewpoint

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2005 IEEE International Conference on Granular computing

作者： Chen, Wan L. Cheng, Jia X. Key Lab. of Intelligent Computing and Signal Processing Ministry of Education AnHui University HeiFei 230039 AnHui China

ISBN: (纸本)0780390172

Quotient space theory of problem solving, a formal model of granular computing, is generalized in the sense that topological structure is replaced by Cech's closure space. Some basic issues of granular computing, such as the representation of real world at different levels of granularity, property preserving and the construction of granular world, are discussed in detail. It turns out that most of conclusions of the classical quotient space theory keep being valid, so intension and applicable fields are enriched and enlarged respectively. © 2005 IEEE.

关键词： Problem solving

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LPP/QR for under-sampled image recognition

LPP/QR for under-sampled image recognition

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International Conference on Machine Learning and Cybernetics, ICMLC 2005

作者： Chen, Si-Bao Zhao, Hai-Feng Luo, Bin Key Lab of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei 230039 China

ISBN: (纸本)078039092X

In this paper, we propose a dimension reduction method of locality preserving projections based on QR-decomposition of training data matrix, namely LPP/QR. It is efficient and effective in under-sampled recognition of image and text data, especially when the number of dimension of data is greater than the number of training samples. Its theoretical foundation is presented. The equivalence between LPP/QR and generalized LPP is induced although LPP/QR is faster than generalized LPP. Several experiments are conducted on Yale face database. High recognition rates show that the algorithm performs better in under-sampled situations. ©2005 IEEE.

关键词： Pattern recognition

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The quotient structure in granule computing

The quotient structure in granule computing

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2005 IEEE International Conference on Granular computing

作者： Zhao, Shu Zhang, Yan-Ping Zhang, Ling Chen, Jie Wan, Zhong Zhang, Ying-Chun Zhang, Chen-Xi Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei 230039 Institute of Artificial Intelligence Anhui University Hefei 230039

ISBN: (纸本)0780390172

The theory of granule computing based on the quotient space is one of the three main granule computing theories. The emphasis is on the structure of the quotient space theory in this paper. Comparing with Rough Set theory, the authors point out the importance of the structure in granule computing theory. A new method of constructing quotient space according to the structure is also presented in this paper. The differences between the quotient structure and structure-based method are proved. Finally, some examples show the rationality and feasibility of our methods. © 2005 IEEE.

关键词： Data processing

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LPP/QR for under-sampled image recognition

LPP/QR for under-sampled image recognition

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Si-Bao Chen Hai-Feng Zhao Bin Luo Key Laboratory of Intelligent Computing & Signal Processing of Ministry of Education Anhui University Hefei China

关键词： Image recognition Principal component analysis Linear discriminant analysis Face detection Training data Scattering Kernel Independent component analysis Laplace equations signal processing

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The quotient structure in granule computing

The quotient structure in granule computing

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IEEE International Conference on Granular computing (GRC)

作者： Shu Zhao Yan-ping Zhang Ling Zhang Jie Chen Zhong Wan Ying-chun Zhang Chen-xi Zhang Key Laboratory of Intelligent Computing & Signal Processing of Ministry of Education Anhui University Hefei China

The theory of granule computing based on the quotient space is one of the three main granule computing theories. The emphasis is on the structure of the quotient space theory in this paper. Comparing with rough set theory, the authors point out the importance of the structure in granule computing theory. A new method of constructing quotient space according to the structure is also presented in this paper. The differences between the quotient structure and structure-based method are proved. Finally, some examples show the rationality and feasibility of our methods.

关键词： Artificial intelligence Set theory Problem-solving Humans Switches Cognitive science Expert systems Switching circuits Technological innovation signal processing

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A META-SEARCH ENGINE BASED ON QUOTIENT SPACE

A META-SEARCH ENGINE BASED ON QUOTIENT SPACE

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2005中国宁波国际计算机科学与技术学术大会

作者： Wei-min Yang Long-shu Li Ministry of Education Key Lab of Intelligent Computing and Signal Processing at Anhui University Department of Computer Science and Engineering Anhui University

World Wide Web has developed to an inherently distributed information system,which brings people great trouble in finding needed information although huge amount of information availab.e on the *** search engine is a very important tool for people to obtain information on the webs,but the low-precision and low-recall exist widely in current search *** effective and accurate intelligent search engine based on the expert systems technology has become the most important research *** paper analyzes the WWW with different granularities according to quotient space theory,gives summarization of search engine and describes an expert system built by Visual Prolog.

关键词： Quotient space Search engine Expert system Visual Prolog.

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Online infomax algorithm and its application to remove EEG artifacts

Online infomax algorithm and its application to remove EEG a...

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2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005

作者： Xiaopei, Wu Zhongfu, Ye Schoo1 of Information Science and Technology University of Science and Technology of China Hefei 230026 Anhui province China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei 230039 Anhui province China

ISBN: (纸本)0780387406

A online infomax algorithm is proposed in this paper. The performances and properties of this online algorithm is investigated in detail. To the problem of the artifacts removal in real life EEG signal, both the online-and batch infomax algorithm are applied and compared. The experiment results show that the online infomax algorithm proposed in this paper has the good performance both in artifacts removal and convergence in time-varying mixing system. © 2005 IEEE.

关键词： Algorithms

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