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.
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This 2005 book provides a needed review of the diverse background material needed for correlation pattern recognition, developing the signal processing theory, the pattern recognition metrics, and the practical application know-how from basic premises. Includes case studies of interest, such as face and fingerprint recognition. For graduate students and practitioners.
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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