Correlation Pattern Recognition

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Cambridge University Press, Nov 24, 2005 - Computers
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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 2005 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.
 

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Contents

1 Introduction
1
2 Mathematical background
13
3 Linear systems and filtering theory
48
4 Detection and estimation
108
5 Correlation filter basics
130
6 Advanced correlation filters
196
7 Optical considerations
244
8 Limitedmodulation filters
295
9 Application of correlation filters
357
References
383
Index
388
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