Available:*
Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
|---|---|---|---|---|---|
Searching... | 30000010128140 | TK7882.P3 K82 2005 | Open Access Book | Book | Searching... |
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Summary
Summary
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.
Reviews 1
Choice Review
Kumar (Carnegie Mellon Univ.), Mahalanobis (Lockheed Martin), and Juday (formerly, NASA Johnson Space Center) have contributed an excellent book on this area of statistical pattern recognition. Correlation is a robust and general pattern recognition technique that can be used in many applications, including target recognition, biometric recognition, and optical character recognition. The book begins with a practical introduction to correlation pattern recognition, discusses the various theories to provide the foundation of correlation pattern recognition, and ends with the current state of the art in computer-generated correlation filters. It provides an overview of the discipline and summarizes recent research that should facilitate the seasoned worker in this field. ^BSumming Up: Highly recommended. Graduate students; faculty and researchers; professionals. C. Tappert Pace University
Table of Contents
| 1 Introduction |
| 2 Mathematical background |
| 3 Linear systems and filtering theory |
| 4 Detection and estimation |
| 5 Correlation filter basics |
| 6 Advanced correlation filters |
| 7 Optical considerations |
| 8 Limited-modulation filters |
| 9 Correlation pattern recognition applications |
| References |
| Index |
