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Pattern Recognition - 3rd Edition - ISBN: 9780123695314, 9780080513614

Pattern Recognition

3rd Edition

Authors: Sergios Theodoridis Konstantinos Koutroumbas
Hardcover ISBN: 9780123695314
eBook ISBN: 9780080513614
Imprint: Academic Press
Published Date: 24th February 2006
Page Count: 856
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Pattern recognition is a fast growing area with applications in a widely diverse number of fields such as communications engineering, bioinformatics, data mining, content-based database retrieval, to name but a few. This new edition addresses and keeps pace with the most recent advancements in these and related areas. This new edition: a) covers Data Mining, which was not treated in the previous edition, and is integrated with existing material in the book, b) includes new results on Learning Theory and Support Vector Machines, that are at the forefront of today's research, with a lot of interest both in academia and in applications-oriented communities, c) for the first time treats audio along with image applications since in today's world the most advanced applications are treated in a unified way and d) the subject of classifier combinations is treated, since this is a hot topic currently of interest in the pattern recognition community.

Key Features

  • The latest results on support vector machines including v-SVM's and their geometric interpretation
  • Classifier combinations including the Boosting approach
  • State-of-the-art material for clustering algorithms tailored for large data sets and/or high dimensional data, as required by applications such as web-mining and bioinformatics
  • Coverage of diverse applications such as image analysis, optical character recognition, channel equalization, speech recognition and audio classification


Researchers, scientists, and engineering professionals working in communications and computer engineering; pattern recognition; informatics; data mining; content-based data retrieval; automation; machine intelligence/machine vision; computer-aided medical diagnostics; speech recognition; and image processing

Table of Contents

Introduction; Classifiers Based on Bayes Decision Theory; Linear Classifiers; Nonlinear Classifiers; Feature Selection; Feature Generation I; Feature Generation II; Template Matching; Context-Dependant Classification; System Evaluation; Clustering: Basic Concepts Clustering Algorithms I (Sequential); Clustering Algorithms II (Hierarchical); Clustering Algorithms III (Functional Optimization); Clustering Algorithms IV (Graph Theory); Cluster Validity


No. of pages:
© Academic Press 2006
24th February 2006
Academic Press
Hardcover ISBN:
eBook ISBN:

About the Authors

Sergios Theodoridis

Sergios Theodoridis

Sergios Theodoridis acquired a Physics degree with honors from the University of Athens, Greece in 1973 and a MSc and a Ph.D. degree in Signal Processing and Communications from the University of Birmingham, UK in 1975 and 1978 respectively. Since 1995 he has been a Professor with the Department of Informatics and Communications at the University of Athens.

Affiliations and Expertise

Department of Informatics and Telecommunications, University of Athens, Greece

Konstantinos Koutroumbas

Konstantinos Koutroumbas acquired a degree from the University of Patras, Greece in Computer Engineering and Informatics in 1989, a MSc in Computer Science from the University of London, UK in 1990, and a Ph.D. degree from the University of Athens in 1995. Since 2001 he has been with the Institute for Space Applications and Remote Sensing of the National Observatory of Athens.

Affiliations and Expertise

Institute for Space Applications & Remote Sensing, National Observatory of Athens, Greece


"The book is written in a very readable, no-nonsense style. I found that there was just the right amount of text to describe a concept, without extraneous verbiage. The same is true for the mathematics, enough for description, not too much to overwhelm." Larry O'Gorman, IAPR Newsletter, April 2006

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