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IEEE International Symposium on Intelligent Signal processing and Communication Systems (ISPACS)

作者： Nattachai Watcharapinchai Supavadee Aramvith Supakorn Siddhichai Sanparith Marukatat Digital Signal Processing Research Laboratory Department of Electrical Engineering Chulalongkom University Bangkok Thailand National Electronics and Computer Technology Center Pathumthani Thailand

The problem of automatic object categorization is investigated under the proposed bag of feature object categorization framework. The framework consists of feature detection and representation which uses the scale invariant feature transform (SIFT) as local feature and bag of feature model to represent the image. Learning process utilizes k-NN (k-nearest neighbour). In this paper, we propose the dimensionality reduction of SIFT using principal component analysis (PCA) on each object category to reduce computational complexity and memory requirement during training process. Experimental results show that our proposed technique can reduce the dimension of SIFT up to around 80% with the same average precision compared to baseline technique without our proposed method.

关键词： Principal component analysis computer vision Histograms Digital signal processing Computational complexity Video compression Testing Training data Vocabulary Feature extraction

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Fingerprint Feature Compression Using Statistical Coding Techniques

Fingerprint Feature Compression Using Statistical Coding Tec...

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IEEE India Conference (INDICON)

作者： C. Saravanan Sanjeev S. Malalur Micahel T. Manry Computer Centre National Institute of Technology Durgapur West Bengal India Department of Electrical Engineering Image Processing & Neural Networks Laboratory University of Technology Arlington USA

ISBN: (纸本)9781424448586;9781424448593

We have proposed a new fingerprint feature compression scheme, which extracts the fingerprint feature using pseudo-spectral fusion approach and compresses the fingerprint feature using statistical coding technique. The compression scheme starts with fingerprint image acquisition, enhancement, and normalization. Further, the direction and density of the fingerprint image are extracted. Fusing these two direction and density data results finger print feature data. The fingerprint feature data is applied directly using a statistical coding technique to get compressed data. The Huffman coding and arithmetic coding is used for compression and found arithmetic coding performs better. This proposed compression scheme achieves nearly 85% compression rate, which is higher compared to other present techniques achieved 45% to 63% compression.

关键词： Fingerprint recognition Image coding Image matching Multiresolution analysis Arithmetic Neural networks Data mining Feature extraction Huffman coding Discrete wavelet transforms

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Brain tissue classification using independent vector analysis (IVA) for magnetic resonance image

Brain tissue classification using independent vector analysi...

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2009 9th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2009

作者： Chiou, Yaw-Jiunn Chen, Hsiang-Min Chai, Jyh Wen Chen, Clayton Chi-Chang Ouyang, Yen-Chieh Su, Wu-Chung Yang, Ching-Wen Lee, San-Kan Chang, Chein-I. Department of Electrical Engineering National Chung Hsing University Taichung Taiwan Department of Radiology College of Medicine China Medical University Taichung Taiwan School of Medicine National Yang-Ming University Taipei Taiwan Department of Radiology Taichung Veterans General Hospital Taichung Taiwan Department of Radiological Technology Central Taiwan University of Science and Technology Taichung 406 Taiwan Computer Center Taichung Veterans General Hospital Taichung 407 Taiwan Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 United States

ISBN: (纸本)9780769536569

The purpose of this study is to present a new method, independent vector analysis (IVA), by extending independent component analysis (ICA) of univariate source signals to multivariate source signals on Magnetic Resonance Imaging (MRI). IVA is utilized to relief the limitation of the conventional ICA approach. The proposed method can resolve the permutation problem during individual ICA runs for group brain MR images. The proposed IVA method in conjunction with support vector machine (SVM), we can effectively separate the different part of gray, white matter and cerebrospinal fluid (CSF) from brain soft tissues. In order to demonstrate the proposed IVA-SVM method, experiments are conducted for performance analysis and evaluation. Simulation results show that using IVA can greatly release from the problem cause from traditional ICA to the situation of analyzing inconsistent results of MR image. © 2009 IEEE.

关键词： Magnetic resonance imaging

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Component analysis-based unsupervised linear spectral mixture analysis for hyperspectral imagery

Component analysis-based unsupervised linear spectral mixtur...

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Workshop on Hyperspectral Image and Signal processing: Evolution in Remote Sensing, WHISPERS

作者： Xiaoli Jiao Yingzi Du Chein-I Chang Remote Sensing Signal and Image Processing Laboratory Department of Computer Science & Electrical Engineering University of Maryland Baltimore MD USA Department of Electrical and Computer Engineering Purdue School of Engineering and Technology Indiana University-Purdue University Indianapolis Indianapolis IN USA Department of Electrical Engineering National Chung Hsing University Taichung Taiwan

One of the most challenging issues in unsupervised linear spectral mixture analysis (LSMA) is how to obtain unknown knowledge of target signatures referred to as virtual endmembers (VEs) directly from the data to be processed. This issue has never arisen in supervised LSMA where the VEs are either assumed to be known a priori or can be provided by visual inspection. With the recent advent of hyperspectral sensor technology many unknown and subtle signal sources can be uncovered and revealed without prior knowledge. This paper addresses this issue and develops a component analysis-based unsupervised LSMA where the desired VEs can be extracted by component analysis-based transforms directly from the data to be processed without appealing for prior knowledge. In order to substantiate the utility of the proposed approach extensive experiments are conducted for demonstration.

关键词： Image analysis Spectral analysis Hyperspectral imaging Independent component analysis Personal communication networks Inspection Statistics Signal analysis Hyperspectral sensors Principal component analysis

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Achieving Close-Capacity Performance with Simple Concatenation Scheme on Multiple-Antenna Channels

Achieving Close-Capacity Performance with Simple Concatenati...

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GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference

作者： Nghi H. Tran Tho Le-Ngoc Tad Matsumoto Ha H. Nguyen Department of Electrical & Computer Engineering McGill University Montreal QUE Canada Information Theory and Signal Processing Laboratory School of Information Science Japan Advanced Institute of Science and Technology Japan Department of Electrical & Computer Engineering University of Saskatchewan Saskatoon SAS Canada

This paper proposes a simple yet capacity-approaching concatenation of a mixture of short memory length convolutional codes and simple rate-1 block code followed by either complex 1-dimensional (1-D) anti-Gray or Gray mapping over multiple antenna channels with quadrature phase-shift keying (QPSK). By interpreting rate-1 code together with 1-D mapping as a multi-D mapping employed over multiple transmit antennas, the error performance is analyzed in two regions, the error-floor and turbo pinch-off regions. In the former one, a tight union bound and design criterion on the asymptotic performance are first derived, which provide an useful tool to predict the error performance. Based on the design criterion, an optimal rate-1 code for each 1-D mapping is then constructed to achieve the best asymptotic performance. In the turbo pinch-off area, by using extrinsic information transfer (EXIT) chart, the most suitable mixed codes are selected for both symmetric and asymmetric antenna setups. It is demonstrated that the simple concatenation scheme can achieve near-capacity. Furthermore, its error performance is comparable to that obtained by using well-designed irregular low-density parity-check (LDPC) and repeat accumulate (RA) codes, and thereby, outperforms a scheme employing a parallel concatenated turbo code.

关键词： Parity check codes Convolutional codes Block codes Phase shift keying Quadrature phase shift keying Transmitting antennas Error analysis Performance analysis Concatenated codes Turbo codes

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An automatic computer-aided detection system for meniscal tears on magnetic resonance images

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IEEE Transactions on Medical Imaging 2009年第8期28卷 1308-1316页

作者： Ramakrishna, Bharath Liu, Weimin Saiprasad, Ganesh Safdar, Nabile Chang, Chein-I Siddiqui, Khan Kim, W. Siegel, Eliot Chai, Jyh-Wen Chen, Clayton Chi-Chang Lee, San-Kan Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore MD 21250 United States University of Maryland School of Medicine Baltimore MD 21201 United States Department of Electrical Engineering and Environmental Restoration Disaster Reduction Research Center National Chung Hsing University Taichung 402 Taiwan VA Maryland Health Care System Baltimore MD 21201 United States Hospital of the University of Pennsylvania Philadelphia PA 19104 United States Department of Radiology College of Medicine China Medical University Taichung 404 Taiwan Department of Radiology Taichung Veterans General Hospital Taichung 40705 Taiwan Department of Radiological Technology Central Taiwan University of Science and Technology Taichung 406 Taiwan Department of Radiology Taichung Veterans General Hospital Taichung 407 Taiwan

Knee-related injuries including meniscal tears are common in both young athletes and the aging population, and require accurate diagnosis and surgical intervention when appropriate. With proper techniques and radiologists' experienced skills, confidence in detection of meniscal tears can be quite high. This paper develops a novel computer-aided detection (CAD) diagnostic system for automatic detection of meniscal tears in the knee. Evaluation of this CAD system using an archived database of images from 40 individuals with suspected knee injuries indicates that the sensitivity and specificity of the proposed CAD system are 83.87% and 75.19%, respectively, compared to the mean sensitivity and specificity of 77.41% and 81.39%, respectively, obtained by experienced radiologists in routine diagnosis without using the CAD. The experimental results suggest that the developed CAD system has great potential and promise in automatic detection of both simple and complex meniscal tears of the knee. © 2009 IEEE.

关键词： Magnetic resonance imaging

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Neuro-fuzzy based fault diagnosis of a Steam Generator

Neuro-fuzzy based fault diagnosis of a Steam Generator

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7th IFAC International Symposium on Fault Detection, Supervision and Safety of Technical Systems, SAFEPROCESS'09

作者： Razavi-Far, Roozbeh Davilu, Hadi Palade, Vasile Lucas, Caro Department of Nuclear Engineering Amirkabir University of Technology P.O. Box 15875 4413 Tehran Iran Computing Laboratory Oxford University Wolfson Building Parks Road Oxford OX1 3QD United Kingdom Center of Excellence on Control and Intelligent Processing Department of Electrical and Computer Engineering University of Tehran P.O. Box 14395 1515 Tehran Iran

ISBN: (纸本)9783902661463

This paper focuses on the development and application of a Neuro-Fuzzy (NF) networks-based scheme for Fault Detection and Isolation (FDI) in a U-tube Steam Generator (UTSG). First, a NF network is trained with data collected from a full scale UTSG simulator, and residuals are generated for fault detection. To identify the UTSG, a Locally Linear Neuro-Fuzzy (LLNF) model is used. This model is trained using the Locally Linear Model Tree (LOLIMOT) algorithm which is an incremental tree structure algorithm. Then, an evolutionary algorithm is used to train a Mamdani type NF network to classify the residuals. The residuals are analyzed by using this NF classifier for fault isolation purposes. © 2009 IFAC.

关键词： Fault detection

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Editorial: Game theory in signal processing and communications

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Eurasip Journal on Advances in Signal processing 2009年 2009卷

作者： Jorswieck, Eduard A. Boche, Holger Han, Zhu Larsson, Erik G. Department of Mobile Communications School of Electrical Engineering and Computer Sciences Technical University of Berlin Berlin Germany Wireless Networking Signal Processing and Security Lab Department of Electrical and Computer Engineering University of Houston Houston TX 77004 United States Linkping University SE-581 83 Linkping Sweden Communications Laboratory Faculty of Electrical Engineering and Information Technology Dresden University of Technology 01062 Dresden Germany

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Magnetization relaxation in YBCO films with improved supercurrent transport properties

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Journal of Physics: Conference Series 2010年第1期234卷

作者： L Miu I Ivan P Badica G Jakob D Miu P Mele K Matsumoto M Mukaida Y Yoshida T Horide A Ichinose S Horii National Institute of Materials Physics 77125 Bucharest-Magurele Romania Institute of Physics University of Mainz 55128 Mainz Germany National Institute of Laser Plasma and Radiation Physics 77125 Bucharest-Magurele Romania Department of Materials Science and Engineering Kyushu Institute of Technology 1-1 Sensui-cho Tobata-ku Kitakyushu 804-8550 Japan Department of Materials Science and Engineering Kyushu University 744 Motooka Nishi-ku Fukuoka 819-0395 Japan Department of Electrical Engineering and Computer Science Nagoya University Furo-cho Chikikusa-ku Nagoya 464-8603 Japan Department of Materials Science and Engineering Kyoto University Yoshida-honmachi Sakyo-ku Kyoto 606-8501 Japan Electric Power Engineering Research Laboratory Central Research Institute of Electric Power Industry 2-6-1 Nagasaka Yokosuda Kanazawa 240-0196 Japan Department of Environmental Systems Engineering Kochi University of Technology Kami-shi Kochi 782-8502 Japan

The relaxation of the irreversible magnetization in optimally doped YBCO films with natural and artificial pinning centres was measured in zero-field cooling conditions using SQUID magnetometry. The external magnetic field H was oriented along the c axis. An appropriate method for the determination of the characteristic vortex pinning energy from the normalized vortex-creep activation energy is discussed. This is based on the existence of a crossover elastic (collective) vortex creep at low temperatures T – plastic vortex creep at high T, caused by the T dependent macroscopic currents induced in the sample during magnetization measurements.

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Comparative evaluation of spatial context techniques for semantic image analysis

Comparative evaluation of spatial context techniques for sem...

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International Workshop on Image Analysis for Multimedia Interactive Services, WIAMIS

作者： G. Th. Papadopoulos C. Saathoff M. Grzegorzek V. Mezaris I. Kompatsiaris S. Staab M. G. Strintzis Centre of Research & Technology Hellas Informatics and Telematics Institute Thessaloniki Greece Information Processing Laboratory Electrical & Computer Engineering Department Aristotle University of Thessaloniki Thessaloniki Greece Information Systems & Semantic Web Research Group Institute of Computer Science University of Koblenz Koblenz Germany

In this paper, two approaches to utilizing contextual information in semantic image analysis are presented and comparatively evaluated. Both approaches make use of spatial context in the form of fuzzy directional relations. The first one is based on a Genetic Algorithm (GA), which is employed in order to decide upon the optimal semantic image interpretation by treating semantic image analysis as a global optimization problem. On the other hand, the second method follows a Binary Integer Programming (BIP) technique for estimating the optimal solution. Both spatial context techniques are evaluated with several different combinations of classifiers and low-level features, in order to demonstrate the improvements attained using spatial context in a number of different image analysis schemes.

关键词： Image analysis Image segmentation Classification algorithms Information processing Image generation Image retrieval Informatics Telematics Information systems Semantic Web

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