Correlation Pattern Recognition

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

390 pages, parution le 24/11/2005

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Résumé

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 state-of-the-art technology presented by the team that developed it and includes case studies of significant current interest, such as face and fingerprint recognition. Suitable for advanced undergraduate or graduate students taking courses in pattern recognition theory, whilst reaching technical levels of interest to the professional practitioner.

A self-contained introduction to the field, covering prerequisite topics

Includes case studies with significant current relevance

Background of authors spans academia, industry and government, giving the material a unique breadth

Sommaire

Introduction
Mathematical background
Linear systems and filtering theory
Detection and estimation
Correlation filter basics
Advanced correlation filters
Optical considerations
Limited-modulation filters
Correlation pattern recognition applications
References
Index

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Cambridge University Press
Auteur(s)	B. V. K. Vijaya Kumar, Abhijit Mahalanobis, Richard D. Juday
Parution	24/11/2005
Nb. de pages	390
Format	18 x 25,5
Couverture	Relié
Poids	945g
Intérieur	Noir et Blanc
EAN13	9780521571036
ISBN13	978-0-521-57103-6