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International Conference on pattern recognition

作者： S. Sener B. Gunsel Institute of Informatics Satellite Communication and Remote Sensing Istanbul Technical University Maslak Istanbul Turkey Multimedia Signal Processing and Pattern Recognition Laboratory Electrical-Electronics Faculty. Department of Electronics and Communications Engineering Istanbul Technical University Maslak Istanbul Turkey

This paper proposes an audio watermark extraction technique which adopts independent component analysis (ICA) for blind watermark decoding. Unlike the existing work, our method allows to combine data synchronization and watermark decoding into one optimization procedure, thus robust to transmission over different channels. Watermark encoder is designed as a nonlinear data embedding machine which is compatible to MPEG Layer 1 Model 1. It is shown that the proposed ICA based watermark decoding scheme allows decoding watermark info accurately even though the watermark to signal ratio is less than -20 dB. The method is robust to stereo-to-mono conversions and performs very well when the channel noise level is high.

关键词： Watermarking Independent component analysis Noise robustness Iterative decoding Frequency synchronization Signal processing pattern recognition Protection Frequency domain analysis Signal to noise ratio

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Modified lifting algorithm and VLSI architecture for the 9/7 wavelet filters

Modified lifting algorithm and VLSI architecture for the 9/7...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Chen-Gyi Xiong Zhi-Rong Gao Jin-Wen Tian Jian Liu The State Key Laboratory of Education Commission for Image Processing and Intelligent Control Institute of Pattern Recognition & Artificial Intelligence Huazhong University of Science and Technology Wuhan China Department of Computer Science Wuhan University of Science and Engineering Hebei China

ISBN: (纸本)0780384032

A new parallel-based lifting algorithm (PBLA) for the 9/7 filters, exploring the parallelism of arithmetic operations in each lifting step, was proposed in this paper. It shortened significantly the critical path of computation, and resulted in a fast VLSI implementation architecture. In comparison with the conventional lifting algorithm based implementation (CLABI), the latency is reduced by more than half from (4T/sub m/ + 8T/sub a/) to (T/sub m/ + 4T/sub a/), which is competitive to that of convolution based implementation CBI, and can be further reduced to Tm by inserting 3 stages of pipeline. The experimental results demonstrate that the proposed architecture has good performances in both speed and area.

关键词： Very large scale integration Discrete wavelet transforms Filters Image coding Delay Parallel processing Arithmetic Convolution Hardware Transform coding

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An efficient algorithm and implementation for residue to binary number conversion

An efficient algorithm and implementation for residue to bin...

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International Conference on Communications, Circuits and Systems (ICCCAS)

作者： Chengyi Xiong Zhirong Gao Jinwen Tian Key Laboratory of Education Commission for Image Processing and Intelligent Control Institute of Pattern Recognition & Artificial Intelligence Huazhong University of Science and Technology Wuhan China Department of Computer Science Wuhan University of Science & Engineering Wuhan China Key Laboratory of Education Commission for Image Processing Huazhong University of Science & Technology China

The residue number system (RNS) has computational advantages in addition and multiplication compared with weighted number systems, such as the binary number system (BNS), since operations on residue digits are performed independently and these processes can be performed in parallel. Thus they are widely used in digital signal processing etc. Since residue to binary conversion is critical and difficult for the practicality of RNS, in this paper, a novel residue to binary (R/B) conversion algorithm for the restricted moduli set (2/sup n/ -1, 2/sup n/, 2n+1), based on exploring the periodicity of modulo (2/sup n/ /spl plusmn/ 1) operations is presented. A new 2n-bit adder based R/B converter is also proposed. The performance comparison results demonstrate that the new converter is faster and requires less area compared with the others reported in the previous literature.

关键词： Signal processing algorithms Image converters Educational institutions computer science Concurrent computing Digital signal processing Arithmetic Laboratories Image processing Intelligent control

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Combining classifiers for face recognition

Combining classifiers for face recognition

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Xiaoguang Lu Yunhong Wang A.K. Jain Department of Computer Science & Engineering Michigan State University East Lansing MI USA National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences Beijing China

Current two-dimensional face recognition approaches can obtain a good performance only under constrained environments. However, in the real applications, face appearance changes significantly due to different illumination, pose, and expression. Face recognizers based on different representations of the input face images have different sensitivity to these variations. Therefore, a combination of different face classifiers which can integrate the complementary information should lead to improved classification accuracy. We use the sum rule and RBF-based integration strategies to combine three commonly used face classifiers based on PCA, ICA and LDA representations. Experiments conducted on a face database containing 206 subjects (2,060 face images) show that the proposed classifier combination approaches outperform individual classifiers.

关键词： Face recognition Principal component analysis Linear discriminant analysis Fingerprint recognition Independent component analysis Image databases Robustness computer science pattern recognition Automation

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Evolutionary self-adaptive multimodel prediction algorithms of the fetal magnetocardiogram 14

Evolutionary self-adaptive multimodel prediction algorithms ...

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14th International Conference on Digital Signal Processing, DSP 2002

作者： Adamopoulos, A.V. Anninos, P.A. Likothanassis, S.D. Beligiannis, G.N. Skavlas, L.V. Demiris, E.N. Papadopoulos, D. Department of Medicine Medical Physics Laboratory Democritus University of Thrace AlexandroupolisGR-68100 Greece Department of Computer Engineering and Informatics Laboratory of Pattern Recognition University of Patras PatrasGR-26500 Greece Computer Technology Institute 3 Kolokotroni str. PatrasGR-26222 Greece

ISBN: (纸本)0780375033

A novel technique for the analysis, nonlinear model identification and prediction of the fetal Magneto Cardio Gram (f-MCG) is presented. f-MCGs can be recorded with the use of specific totally non-invasive Superconductive Quantum Interference Devices (SQUID). For the analysis and classification of the f-MCG signals we introduce an intelligent method that combines the following well known advanced signal processing techniques: The Genetic Algorithms (GA), the Multi Model Partitioning (MMP) theory and the Extended Kalman Filters (EKF). Simulations illustrate that the proposed method is selecting the correct model structure and identifies the model parameters m a sufficiently small number of iterations and tracks successfully changes in the signal, in real time. The information provided by the proposed analysis is easily interpreted and assessed by gynecologists and is consisted to the clinical status of the fetus. The proposed algorithm can be parallel implemented and also a VLSI implementation is feasible. © 2002 IEEE.

关键词： Magnetos

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Evolutionary self-adaptive multimodel prediction algorithms of the fetal magnetocardiogram

Evolutionary self-adaptive multimodel prediction algorithms ...

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International Conference on Digital Signal Processing (DSP)

作者： A.V. Adamopoulos P.A. Anninos S.D. Likothanassis G.N. Beligiannis L.V. Skarlas E.N. Demiris D. Papadopoulos Department of Computer Engineering and Informatics Laboratory of Pattern Recognition University of Patras Patras Greece Department of Medicine Medical Physics Laboratory Democritus University of Thrace Alexandroupolis Greece Computer Technology Institute Patras Greece

A novel technique for the analysis, nonlinear model identification and prediction of the fetal magnetocardiogram (f-MCG) is presented. f-MCGs can be recorded with the use of specific totally non-invasive superconductive quantum interference devices (SQUID). For the analysis and classification of the f-MCG signals we introduce an intelligent method that combines the following well known advanced signal processing techniques: the genetic algorithms (GA), the multimodel partitioning (MMP) theory and the extended Kalman filters (EKF). Simulations illustrate that the proposed method is selecting the correct model structure and identifies the model parameters in a sufficiently small number of iterations and tracks successfully changes in the signal, in real time. The information provided by the proposed analysis is easily interpreted and assessed by gynecologists and consist of the clinical status of the fetus. The proposed algorithm can be parallel implemented and also a VLSI implementation is feasible.

关键词： Prediction algorithms Signal processing algorithms Superconducting magnets Magnetic analysis Signal processing Predictive models Magnetic devices Superconductivity Interference SQUIDs

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Multiple objects segmentation based on maximum-likelihood estimation and optimum entropy-distribution (MLE-OED)

Multiple objects segmentation based on maximum-likelihood es...

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International Conference on pattern recognition

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

ISBN: (纸本)076951695X

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. The performance in the experiments is better than those of two popular methods.

关键词： Object segmentation Maximum likelihood estimation Image segmentation Layout Uncertainty Image edge detection Shape measurement Image processing pattern recognition Gaussian distribution

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DGLC: a density-based global logical combinatorial clustering algorithm for large mixed incomplete data

DGLC: a density-based global logical combinatorial clusterin...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： J. Ruiz-Shulcloper E. Alba-Cabrera G. Sanchez-Diaz IRIS Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville USA Institute of Cybernetics Mathematics and Physics Laboratory of Pattern Recognition Havana Cuba

Clustering has been widely used in areas as pattern recognition, data analysis and image processing. Recently, clustering algorithms have been recognized as one of a powerful tool for data mining. However, the well-known clustering algorithms offer no solution to the case of large mixed incomplete data sets. The authors comment the possibilities of application of the methods, techniques and philosophy of the logical combinatorial approach for clustering in these kinds of data sets. They present the new clustering algorithm DGLC for discovering /spl beta//sub 0/-density connected components from large mixed incomplete data sets. This algorithm combines the ideas of logical combinatorial pattern recognition with the density based notion of cluster. Finally, an example is showed in order to illustrate the work of the algorithm.

关键词： Clustering algorithms pattern recognition Physics computing Iris Data engineering Cybernetics Mathematics Digital images Power engineering computing Data analysis

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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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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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