HDBK PATTE RECOG & COMP (5TH ED)

by Chi Hau Chen (Editor)

Overview

Pattern recognition, image processing and computer vision are closely linked areas which have seen enormous progress in the last fifty years. Their applications in our daily life, commerce and industry are growing even more rapidly than theoretical advances. Hence, the need for a new handbook in pattern recognition and computer vision every five or six years as envisioned in 1990 is fully justified and valid.The book consists of three parts: (1) Pattern recognition methods and applications; (2) Computer vision and image processing; and (3) Systems, architecture and technology. This book is intended to capture the major developments in pattern recognition and computer vision though it is impossible to cover all topics.The chapters are written by experts from many countries, fully reflecting the strong international research interests in the areas. This fifth edition will complement the previous four editions of the book.

Product Details

ISBN-13:	9789814656542
Publisher:	World Scientific Publishing Company, Incorporated
Publication date:	12/15/2015
Sold by:	Barnes & Noble
Format:	eBook
Pages:	584
File size:	26 MB
Note:	This product may take a few minutes to download.

Table of Contents

Preface to the 5th Edition vii

Part 1 Pattern Recognition Methods and Applications 1

Chapter 1.1 Syntactic Pattern Recognition: Paradigm Issues and Open Problems Mariusz Flasinski 3

Chapter 1.2 Deep Discriminative and Generative Models for Speech Pattern Recognition Li Deng Navdeep Jaitly 27

Chapter 1.3 On Measuring and Quantifying Performance: Error Rates, Surrogate Loss, and An Example in Semi-supervised Learning Marco Loog Jesse H. Krijthe Art C. Jensen 53

Chapter 1.4 Information Theoretic Clustering Using a k-Nearest Neighbors-based Divergence Measure Vidar V. Vikjord Robert Jenvsen 69

Chapter 1.5 Pruning Trees in Random Forests for Minimizing Non Detection in Medical Imaging Laurent Heutte Caroline Petitjean Chesner Désir 89

Chapter 1.6 Recent Advances on Optimum-path Forest for Data Classification: Supervised, Semi-supervised, and Unsupervised Learning João Paulo Papa Willian Paraguassu Amorim Alexandre Xavier Falcão João Manuel R. S. Tavares 109

Chapter 1.7 On Curvelet-based Texture Features for Pattern Classification Ching-Chung Li Wen-Chyi Lin 125

Chapter 1.8 Computer Recognition and Evaluation of Coins Bo-Yuan Feng Ke Sun Parmida Atighechian Ching Y. Suen 141

Chapter 1.9 Supervised and Unsupervised Feature Descriptors for Error-resilient Underwater Live Fish Recognition Meng-Che Chuang Jenq-Neng Hwang Kresimir Williams 159

Chapter 1.10 Model Adaptation for Personalized Music Emotion Recognition Yi-Hsuan Yang Ju-Chiang Wang Yu-An Chen Homer H. Chen 175

Part 2 Computer Vision and Image Processing 195

Chapter 2.1 Context Assisted Person Identification for Images and Videos Liyan Zhang Dmitri V. Kalashnikov Shared Mehroira 197

Chapter 2.2 Statistical Shape Spaces for 3D Data: A Review Alan Brunton Augusta Saiazar Tirno Bolkart Stefania Wuhrer 217

Chapter 2.3 Tracking Without Appearance Descriptors Mehrsan Javan Roshtkhari Martin D. Levine 239

Chapter 2.4 Knowledge Augmented Visual Learning Ziheng Wang Qiang Ji 255

Chapter 2.5 Graph Edit Distance - Novel Approximation Algorithms Kaspar Riesen Horst Bunke 275

Chapter 2.6 Latest. Developments of LSTM Neural Networks with Applications of Document Image Analysis Marcus Liwicki Volkmar Frinhen Muhammad Zeshan Afzal 293

Chapter 2.7 Analyzing Remote Sensing Images with Hierarchial Morphological Representations Gabriele Cavallaro Maura Bulla Mura Jón Atli Benediktsson 313

Chapter 2.8 Manifold-based Sparse Representation for Hyperspectral Image Classification Yuan Yan Tang Haoliang Yuan 331

Chapter 2.9 A Review of Texture Classification Methods and Their Applications in Medical Image Analysis of the Brain Rouzbeh Maani Sanjay Kalra Yee-Hong Yang 351

Chapter 2.10 3D Tomosynthesis to Detect Breast Cancer Yanbin Lu Mina Yousefi John Ellenberger Richard H. Moore Daniel B. Kopans Adam Krzyzak Ching Y. Suen 371

Part 3 System, Architecture, and Technology 395

Chapter 3.1 Combining Representations for Improved Sketch Recognition Sonya Gates 397

Chapter 3.2 Visual Object Recognition with Image Retrieval Sedat Ozer 415

Chapter 3.3 Efficient Identification of Faces in Video Streams Using Low-power Multi-core Devices Donavan Prieur Eric Granger Yvon Savaria Claude Thibeault 427

Chapter 3.4 Kernel-bayed Learning for Fault Detection and Identification in Fuel Cell Systems Gabriele Moser Paolo Costamagna Andrea De Giorgi Lissy Pellaco Andrea Trucco Sebastiano B. Serpico 455

Chapter 3.5 Outdoor Shadow Modelling and its Applications Lin Gu Antonio Robles-Kelly 473

Chapter 3.6 Fast Structured Tracker with Improved Motion Model Using Robust Kalman Filter Ivan Bogun Eraldo Ribeiro 491

Chapter 3.7 Using 3D Vision for Automated Industrial Inspection David J. Michael 509

Chapter 3.8 Vision Challenges in Image-based Barcode Readers Xianju Wang Xiangyun (Mary) Ye 521

Chapter 3.9 Parallel Pattern Matching Using the Automata Processor Matt Tanner Matt Grimm Harold B. Noyes 539

Index 561

Editorial Reviews

Presents the latest research findings in theory, techniques, algorithms, and major applications of pattern recognition and computer vision, as well as new hardware and architecture aspects. Contains sections on basic methods in pattern recognition and computer vision, nine recognition applications, inspection and robotic applications, and architectures and technology. Some areas discussed include cluster analysis, 3D vision of dynamic objects, speech recognition, computer vision in food handling, and video content analysis and retrieval. This second edition is extensively revised to describe progress in the field since 1993. Chen is affiliated with the electrical and computer engineering department at the University of Massachusetts-Dartmouth. Annotation c. Book News, Inc., Portland, OR (booknews.com)

Booknews