Correlation Pattern Recognition
Download Correlation Pattern Recognition PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Correlation Pattern Recognition book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Correlation Pattern Recognition
Author: B. V. K. Vijaya Kumar
language: en
Publisher: Cambridge University Press
Release Date: 2005-11-24
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.
Correlation Pattern Recognition
A review of the background material needed for correlation pattern recognition for graduate students and practitioners.
Progress in Pattern Recognition, Image Analysis and Applications
This book constitutes the refereed proceedings of the 12th Iberoamerican Congress on Pattern Recognition, CIARP 2007, held in Valparaiso, Chile, November 13-16, 2007. The 97 revised full papers presented together with four keynote articles were carefully reviewed and selected from 200 submissions. The papers cover ongoing research and mathematical methods for pattern recognition, image analysis, and applications in areas such as computer vision, robotics, industry and health.