Correlation Pattern Recognition

by B. V. K. Vijaya Kumar, Richard D. Juday, Abhijit Mahalanobis

Overview

Correlation is a robust and general technique for pattern recognition and is used in many applications, such as automatic target recognition, biometric recognition and optical character recognition. The design, analysis and use of correlation pattern recognition algorithms requires background information, including linear systems theory, random variables and processes, matrix/vector methods, detection and estimation theory, digital signal processing and optical processing. This book provides a needed review of this diverse background material and develops the signal processing theory, the pattern recognition metrics, and the practical application know-how from basic premises. It shows both digital and optical implementations. It also contains technology presented by the team that developed it and includes case studies of significant interest, such as face and fingerprint recognition. Suitable for graduate students taking courses in pattern recognition theory, whilst reaching technical levels of interest to the professional practitioner.

Product Details

ISBN-13:	9780521153485
Publisher:	Cambridge University Press
Publication date:	06/10/2010
Pages:	404
Product dimensions:	6.60(w) x 9.50(h) x 1.00(d)

Table of Contents

Preface; 1. Introduction; 2. Mathematical background; 3. Linear systems and filtering theory; 4. Detection and estimation; 5. Correlation filter basics; 6. Advanced correlation filters; 7. Optical considerations; 8. Limited-modulation filters; 9. Applications of correlation filters; References; Index.

Editorial Reviews

“An excellent book...It provides an overview of the discipline and summarizes recent research that should facilitate the seasoned worker in this field. Highly recommended.”
Choice

"This book educates the reader on the richness of correlation...This book is well-written with many diagrams and gray-scale images to illustrate the concepts...This book is intended for advanced undergraduate and graduate students, and would be especially useful for pattern recognition practitioners interested in expanding their tool chest beyond basic correlation."
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