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Pattern recognition and computer vision and their applications have experienced enormous progress in research and development over the last two decades. This comprehensive handbook, with chapters by leading experts in their fields, documents both the basics and new and advanced results.The book gives the most total treatment of basic methods in pattern recognition including statistical, neurocomputing, syntactic/structural/grammatical approaches, feature selection and cluster analysis; and an extensive presentation of basic methods in computer vision including texture analysis and models, color, geometrical tools, image sequence analysis, etc. Major and unique applications are also covered, such as food handling using computer vision, non-destructive evaluation of materials, applications in economics and business, medical image recognition and understanding, etc. Broader system aspects are also examined, including optical pattern recognition and architectures for computer vision.Researchers, students and users of pattern recognition and computer vision will find the book an essential reference tool. The volume is also an invaluable collection of basic techniques and principles, which would otherwise be hard to assemble, in one convenient volume.

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CONTENTS
Preface / C. H. Chen ; L. F. Pau ; P. S. P. Wang = ⅶ
PART 1. BASIC METHODS IN PATTERN RECOGNITION
  1.1 Cluster Analysis and Related Issues / Richard C. Dubes = 3
  1.2 Statistical Pattern Recognition / Keonosuke Fukunaga = 33
  1.3 Large-Scale Feature Selection / Jack Sklansky ; Wojciech Siedlecki = 61
    1.3.1 On Automatic Feature Selection［reprint］/ Wojciech siedlecki ; Jack Sklansky = 63
    1.3.2 A Note on Genetic Algorithms for Large-Scale Feature Selection［reprint］/ W. Siedlecki ; J. Sklansky = 88
    1.3.3 Constrained Genetic Optimization Via Dynamic Reward-Penalty Balancing and Its Use in Pattern Recognition［reprint］/ W. Siedlecki ; J. Sklansky = 108
  1.4 Neural Net Computing for Pattern Recognition / Yoh-Han Pao = 125
  1.5 Structural and Syntactic Pattern Recognition / Horst Bunke = 163
  1.6 A Formal Parallel Model for Three-Dimensional Object Pattern Representation / P. S. P. Wang = 211
PART 2. BASIC METHODS IN COMPUTER VISION
  2.1 Texture Analysis / Mihran Tuceryan ; Anil K. Jain = 235
  2.2 Model-Based Texture Segmentation and Classification / R. Chellappa ; R. L. Kashyap ; B. S. Manjunath = 277
  2.3 Color in Computer Vision / Quang-Tuan Luong = 311
  2.4 Projective Geometry and Computer Vision / Roger Mohr = 369
  2.5 3-D motion Analysis from Image Sequences Using Point Correspondences / John J. Weng ; Thomas S. Huang = 395
  2.6 Segmentation Tools in Mathematical Morphology［reprint］/ Serge Beucher = 443
  2.7 Parallel Thinning Algorithm for Binary Digital Patterns / Yung-Sheng Chen ; Wen-Hing Hsu = 457
PART 3. RECOGNITION APPLICATIONS
  3.1 Pattern Recognition in Nondestructive Evaluation of Materials / C. H. Chen = 493
  3.2 Pattern Recognition in Geophysical Signal Processing and Interpretation / Yanda Li ; Zhaoqi Bian ; Pinfan Yan ; Tong Chang = 511
  3.3 Signal Transient Analyses and Classification Techniques / R. Craig Olson = 541
  3.4 Analysis of Economic and Business Information / Claudio Gianotti = 569
  3.5 Optical Handwritten chinese Character Recognition / Jun S. Huang = 595
  3.6 Automatic Analysis and Understanding of Documents Yuan Y. Tang ; Chang D. Yan ; M. Cheret ; Ching Y. Suen = 625
  3.7 Pattern Recognition and Visualization of Sparsely Sampled Biomedical Signals / Ching-Chung Li ; T. P. Wang ; A. H. Vagnucci = 655
  3.8 Understanding Microvessels in Two and Three Dimensions / Carl E. Wick ; Murray H. Loew ; Joseph Kurantsin-Mills = 667
PART 4. INSPECTION AND ROBOTICS APPLICATIONS
  4.1 Computer Vision in Food Handling and Sorting / H o ·· rdur Arnarson ; Magn$u'$$s A' smundsson = 697
  4.2 Image Information Retrieval Systems / Ang Yew-Hock ; Arcot Desai Naracimhalu ; Suliman Al-Hawamdeh = 719
  4.3 Context Related Issues in Image Understanding / L. F. Pau = 741
  4.4 Positional Estimation Techniques for An Autonomous Mobile Robot - A Review / Raj Talluri ; J. K. Aggarwal = 769
PART 5. ARCHITECTURES AND TECHNOLOGY
  5.1 Vision Engineering : Designing Computer Vision Systems / Rama Chellappa ; Azriel Rosenfeld = 805
  5.2 Optical Pattern Recognition for Computer Vision / David Casasent = 817
  5.3 Spatial Knowledge Representation for Iconic Image Database / Suh-yin Lee ; Fang-Jung Hsu = 839
  5.4 Viewer-Centered Representations in Object Recognition : A Computational Approach / Ronen Basri = 863
  5.5 Connectionist Architectures in Low Level Image Segmentation / W. Ekkehard Blanz ; Charles E. Cox ; Sheri L. Gish = 883
  5.6 Architectures for Image Processing and Computer Vision［reprint］/ Giovanni Garibotto = 921
  5.7 Image Information Systems : Where Do We Go from Here?［reprint］/ Shi-Kuo Chang ; Arding Hsu = 941
Subject Index = 967