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.
Cambridge University Press (Virtual Publishing)
|Country of origin:
• Abhijit Mahalanobis
• Richard D. Juday
||Electronic book text
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