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.

Author Biography

Professor B. V. K. Vijaya Kumar has been a faculty member of the Department of Electrical and Computer Engineering at Carnegie Mellon University since 1982 and was made a full Professor in 1991. He is a senior member of the IEEE and a fellow of the SPIE and the OSA. He has authored or co-authored 7 book chapters and over 300 technical papers. Dr Abhijit Mahalanobis is a Principal Research Engineer at Lockheed Martin, Orlando, and is currently the technical lead for the Automatic Target Recognition programs in the Research and Technology group. He was elected a fellow of the SPIE in 1997 and has published over 100 journal and conference publications. Dr Juday retired from NASA after 35 years of varied technical work, including several forms of digital and optical image processing. His several patents concentrate on image processing by both of these means. He is a Fellow of the SPIE and a member of the OSA.

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