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Pattern Recognition Techniques, Technology and Applications PDF

636 Pages·2016·59.699 MB·English
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Pattern Recognition Techniques, Technology and Applications Edited by Peng-Yeng Yin Pattern Recognition Techniques, Technology and Applications Edited by Peng-Yeng Yin Published by ExLi4EvA Copyright © 2016 All chapters are Open Access distributed under the Creative Commons Attribution 3.0 license, which allows users to download, copy and build upon published articles even for commercial purposes, as long as the author and publisher are properly credited, which ensures maximum dissemination and a wider impact of our publications. After this work has been published, authors have the right to republish it, in whole or part, in any publication of which they are the author, and to make other personal use of the work. Any republication, referencing or personal use of the work must explicitly identify the original source. As for readers, this license allows users to download, copy and build upon published chapters even for commercial purposes, as long as the author and publisher are properly credited, which ensures maximum dissemination and a wider impact of our publications. Notice Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published chapters. The publisher assumes no responsibility for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained in the book. Publishing Process Manager Technical Editor AvE4EvA MuViMix Records Cover Designer ISBN-10: 953-7619-24-9 ISBN-13: 978-953-7619-24-4 Preface A wealth of advanced pattern recognition algorithms are emerging from the inter- discipline between technologies of effective visual features and the human-brain cognition process. Effective visual features are made possible through the rapid developments in appropriate sensor equipments, novel filter designs, and viable information processing architectures. While the understanding of human-brain cognition process broadens the way in which the computer can perform pattern recognition tasks. The present book is intended to collect representative researches around the globe focusing on low-level vision, filter design, features and image descriptors, data mining and analysis, and biologically inspired algorithms. The 27 chapters coved in this book disclose recent advances and new ideas in promoting the techniques, technology and applications of pattern recognition. Editor Peng-Yeng Yin National Chi Nan University, Taiwan Contents Preface V 1. Local Energy Variability as a Generic Measure of Bottom-Up Salience 001 Antón Garcia-Diaz, Xosé R. Fdez-Vidal, Xosé M. Pardo and Raquel Dosil 2. Real-Time Detection of Infrared Profile Patterns and Features Extraction 025 Rubén Usamentiaga, Daniel F. García and Julio Molleda 3. A Survey of Shape Feature Extraction Techniques 043 Yang Mingqiang, Kpalma Kidiyo and Ronsin Joseph 4. Computational Intelligence Approaches to Brain Signal 091 Pattern Recognition Pawel Herman, Girijesh Prasad and Thomas Martin McGinnity 5. Automatic Calibration of Hybrid Dynamic Vision System for High 121 Resolution Object Tracking Julie Badri, Christophe Tilmant, Jean-Marc Lavest, Patrick Sayd and Quoc Cuong Pham 6. Image Representation Using Fuzzy Morphological Wavelet 143 Chin-Pan Huang 7. Multidimensional Texture Analysis for Unsupervised 163 Pattern Classification K.Hammouche and J.-G. Postaire 8. Rock Particle Image Segmentation and Systems 197 Weixing Wang 9. Unsupervised Texture Segmentation 227 Michal Haindl and Stanislav Mikeš VIII 10. Optimization of Goal Function Pseudogradient in the Problem of 249 Interframe Geometrical Deformations Estimation A.G. Tashlinskii 11. New Digital Approach to CNN On-chip Implementation 281 for Pattern Recognition Daniela Durackova 12. Distortion-Invariant Pattern Recognition 289 with Adaptive Correlation Filters Vitaly Kober and Erika M. Ramos-Michel 13. Manifold Matching for High-Dimensional Pattern Recognition 309 Seiji Hotta 14. Output Coding Methods: Review and Experimental Comparison 327 Nicolás García-Pedrajas and Aida de Haro García 15. Activity Recognition Using Probabilistic Timed Automata 345 Lucjan Pelc and Bogdan Kwolek 16. Load Time-Series Classification Based 361 on Pattern Recognition Methods George J. Tsekouras, Anastasios D. Salis, Maria A. Tsaroucha and Irene S. Karanasiou 17. Theory of Cognitive Pattern Recognition 433 Youguo Pi, Wenzhi Liao, Mingyou Liu and Jianping Lu 18. Parametric Circle Approximation Using Genetic Algorithms 463 Victor Ayala-Ramirez, Raul E. Sanchez-Yanez, Jose A. Gasca-Martinez and Sergio A. Mota-Gutierrez 19. Registration of Point Patterns Using Modern Evolutionary Algorithms 479 Peng-Yeng Yin 20. Investigation of a New Artificial Immune System Model Applied 495 to Pattern Recognition José Lima Alexandrino, Cleber Zanchettin, Edson C. de B. Carvalho Filho 21. Designing a Pattern Recognition Neural Network with 507 a Reject Output and Many Sets of Weights and Biases Le Dung and Makoto Mizukawa IX 22. A SIFT-Based Fingerprint Verification System Using 523 Cellular Neural Networks Giancarlo Iannizzotto and Francesco La Rosa 23. The Fourth Biometric - Vein Recognition 537 Li Xueyan and Guo Shuxu 24. A Hybrid Pattern Recognition Architecture for Cutting Tool 547 Condition Monitoring Pan Fu and A. D. Hope 25. Mining Digital Music Score Collections: Melody Extraction 559 and Genre Recognition Pedro J. Ponce de León, José M. Iñesta and David Rizo 26. Application of Forward Error Correcting Algorithms 591 to Positioning Systems Nikos Petrellis, Fotios Gioulekas, Michael Birbas, John Kikidis and Alex Birbas 27. Pattern Recognition in Time-Frequency Domain: Selective Regional 613 Correlation and Its Applications Ervin Sejdić and Jin Jiang

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