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Efficient image watermarking scheme based on Gabor transform

Guangdianzi Jiguang/Journal of Optoelectronics Laser 2005年第11期16卷 1363-1367页

作者： Chen, Jing-Yuan Tao, Liang Key Laboratory of Intelligent Computation and Signal Processing Anhui University Hefei 230039 China

An efficient robust watermarking scheme for digital images is presented, based on the discrete Gabor transforms (DGT), The watermark in digital images is hidden by changing their DGT coefficients to represent special low frequencies. In the proposed watermark-checking algorithm, the geometric transforms and corresponding matching method are applied for geometric transformed images in order to recover them for watermark-checking. The proposed scheme was tested by StirMark 4.0, a well-known software for testing watermarking schemes, and it performed successfully in almost all testing cases with high robustness and efficiency.

关键词： Digital watermarking

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A New Pattern Recognition Algorithm Based on Fuzzy Association Degree

A New Pattern Recognition Algorithm Based on Fuzzy Associati...

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International Conference on Neural Networks and Brain (ICNNB)

作者： Shifei Ding Zhongzhi Shi College of Information Science and Engineering Shandong Agricultural University Taian China Key Laboratory of Intelligent Information Processing Chinese Academy of Sciences Institute for Computing Technology Beijing China

Based on fuzzy association degree, a new pattern recognition algorithm is set up. First, some new concepts of fuzzy association coefficient (FAC), fuzzy association degree (FAD) and fuzzy relative weight (FRW) have been proposed for surveying data information. Second, on the basis of the concepts proposed here, a new pattern recognition algorithm has been set up. At last, the algorithm set up here is applied to surveying data. The results of simulation application show that the recognition algorithm presented here is feasible and effective

关键词： Pattern recognition Fuzzy sets Laboratories Fuzzy neural networks Educational institutions Information science Agricultural engineering History Artificial neural networks Pattern analysis

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R-Chord: A Semantic-based Peer Data Management Model

R-Chord: A Semantic-based Peer Data Management Model

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International Conference on Semantics, Knowledge and Grid (SKG)

作者： Jie Liu Hai Zhuge Graduate School of Chinese Academy of Sciences China China Knowledge Grid Research Group Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

The key issue of peer data management systems (PDMSs) is how to efficiently organize and manage distributed resources in P2P networks to accurately route queries from the peer initiating the query to appropriate peers to avoid network flooding. This paper proposes a semantic-based PDMS model, called R-Chord, by deploying the resource space model above the Chord overlay for uniformly, normally and effectively organizing and managing resources distributed in P2P networks. Experiments show that, compared to the Chord model, the R-Chord model is more flexible to support semantic-based queries and can significantly decrease the average visiting number of and visiting times on peers for answering queries.

关键词： Resource management Peer to peer computing Knowledge management Computer network management Technology management Large-scale systems Relational databases XML Prototypes intelligent networks

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Automatic gait recognition based on wavelet reflective symmetry moments

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Journal of Information and Computational Science 2005年第2期2卷 421-428页

作者： Zhao, Guoying Cui, Li Xiang, Shiming Li, Hua Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Graduate School Chinese Academy of Sciences Beijing 100039 China School of Mathematics Science Beijing Normal University Beijing 100875 China

Gait is an identifying biometric feature. In recent years, Video-based gait recognition is becoming a new challenging problem in the field of computer vision. In this paper, wavelet reflective symmetry moments (WRSMs) have been proposed to describe and recognize gait automatically. WRSMs represent the appearance of people with merits of moments and wavelet analysis and reflect people's symmetrical walking habit. Moments have translation, scale and rotation invariant characteristics;while wavelet analysis is able to extract the multi-resolution features subtly and deal with noise. So combination of wavelet moments and reflective symmetry not only has characteristics of moments and wavelet analysis, but also is in accordance with one of the relative results in psychological researches which state that gait is a type of symmetrical model. Experiments based on USF's database have shown that the application of wavelet reflective symmetry moments in gait recognition leads to relatively high distinguishability of gait with effective noise handling.

关键词： Computer vision

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A logical foundation for ontology representation in NKI

A logical foundation for ontology representation in NKI

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IEEE International Conference on Natural Language processing and Knowledge Engineering (NLP-KE)

作者： Yu Sun Yuefei Sui Institute of Computer Science and Information Technology Yunnan Normal University Kunming China Graduate School Chinese Academy and Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

A formal representation of ontologies is proposed, based on F-logic and O-logic; and the works in the building of ontologies in NKI. An ontology includes class frames, slot frames, class-slot frames, object frames and axioms. The value restrictions of slots are defined in slot frames. For each slot and each class, there is a class-slot frame representing the specific value restrictions of the slot when defining the class; and the relations between class-slot frames and slot frames are discussed. For a slot in a class frame, its values are inherited to its subclasses without blocking; and its default values are inherited to its subclasses taking overriding, revising and conflict resolution into account. After giving the formal representation of ontologies, the semantics of ontologies are discussed, and main results are presented.

关键词： Ontologies Databases Laboratories intelligent structures Information processing Computer science Information technology Vocabulary Logic

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Knowledge Energy in Knowledge Flow Networks

Knowledge Energy in Knowledge Flow Networks

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International Conference on Semantics, Knowledge and Grid (SKG)

作者： Hai Zhuge Weiyu Guo Xiang Li Lianhong Ding China Knowledge Grid Research Group Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Graduate School of Chinese Academy of Sciences Beijing China Chinese Academy of Sciences Beijing Beijing CN

A knowledge flow is invisible but it plays an important role in ordering knowledge exchange in teamwork. It can help achieve effective team knowledge management by modeling, optimizing, monitoring and controlling the operation of knowledge flow processes. This paper proposes the notion of knowledge energy as the driving cause of forming an autonomous knowledge flow network, and explores the behind principles. Knowing these principles can help team managers and the support systems improve cooperation by monitoring the knowledge energy of nodes, and by evaluating and adjusting knowledge flows. A knowledge flow network management system can be the high layer of the knowledge grid to help improve the efficiency of distributed knowledge-intensive teamwork.

关键词： Knowledge management Teamwork intelligent networks Monitoring Energy management Information processing Computers IP networks Prototypes Routing

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A novel feature extraction algorithm

A novel feature extraction algorithm

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Shi-Fei Ding Zhong-Zhi Shi Vun-Cheng Wang Shu-Shan Li College of Information Science and Engineering Shandong Agricultural University Taian China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China College of Information Science and Engineering Shandong University of Science and Technology Qingdao China

Feature extraction or selection is one of the most important steps in pattern recognition or pattern classification, data mining, machine learning and so on. In this paper, we introduce the information theory, propose a new concept of probability information distance (PID) and prove that the PID satisfies four requests of axiomatization of the distance. So the PID is a kind of distance measure, which can be used to measure the degree of variation between two random variables. We make the PID be separability criterion of the classes for information feature extraction, and call it PID criterion (PIDC). Based on PIDC, we design a novel algorithm for information feature extraction. Compared with principal components analysis (PCA), correlation analysis etc., the algorithm put forward in this paper had regarded for the class information, and so it is a kind of supervised algorithm of feature extraction. The experimental results demonstrate that the algorithm is valid and reliable, and it provides a new research approach for feature extraction, data mining and pattern recognition.

关键词： Feature extraction Pattern recognition Data mining Algorithm design and analysis Principal component analysis Machine learning algorithms Pattern classification Machine learning Information theory Random variables

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Information feature analysis and improved algorithm of PCA

Information feature analysis and improved algorithm of PCA

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Shi-Fei Ding Zhong-Zhi Shi Yong Liang Feng-Xiang Jin College of Information Science and Engineering Shandong Agricultural University Taian China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China College of Geo-Information Science and Engineering Shandong University of Science and Technology Qingdao China

Principal component analysis (PCA) is an important method in multivariate statistical analysis, and its main idea is compression of dimensionality including variables and samples. In this paper, based on the ideas concerned with information function and information entropy of Shannon information theory, consider the inherent characteristic of eigenvalues of matrix, two new concepts of possibility information function (PIF) and possibility information entropy (PIE) are proposed firstly. On the basis of these, the formulae of information rate (IR) and accumulated information rate (AIR) are set up, by which the degree of information compression is measured. In the end, we improve the PCA algorithm called improved principal component analysis (PCA). Through simulated application in practice, the results show that the IPCA proposed here is efficient and satisfactory. It provides a new research approach of information feature compression for pattern recognition.

关键词： Information analysis Algorithm design and analysis Principal component analysis Information entropy Educational institutions Agricultural engineering Statistical analysis Information theory Information rates Geographic Information Systems

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Survey of 3D mesh model segmentation and application

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Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics 2005年第8期17卷 1647-1655页

作者： Sun, Xiaopeng Li, Hua Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Graduate School Chinese Academy of Sciences Beijing 100039 China

In this paper, we present a brief summary to 3D mesh model segmentation techniques, including definition, latest achievements, classification and application in this field. Then evaluations on some of typical methods, such as Watershed, topological and geometrical method, are introduced. After some applications are presented, problems and prospect of the techniques are also discussed.

关键词： 3D segmentation Mesh model Segmentation/decomposition Shape features

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Non-parametric foreground/background segmentation method by fusion of intensity and edge feature

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Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics 2005年第6期17卷 1278-1284页

作者： Chen, Rui Deng, Yu Xiang, Shiming Li, Hua Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Graduate School Chinese Academy of Sciences Beijing 100039 China

This paper presents a novel segmentation method based on a non-parametric background model that has the ability of modeling multi-model. Firstly, both the intensity and edge features are used to improve robustness of the foreground detection. Secondly, we also present an adaptive shadow detection model to find the accurate moving objects. The experiment results show that our proposed method is effective.

关键词： Background subtraction Kernel density estimation Segmentation Shadow removal

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