Computational Algorithms for Fingerprint Recognition

Bhanu, Bir; Tan, Xuejun

ISBN 10: 1402076517 / ISBN 13: 9781402076510

Published by Springer, 2003

About this Item

Unread book in perfect condition.

Seller Inventory # 1988912

Bibliographic Details

• Title: Computational Algorithms for Fingerprint Recognition
• Publisher: Springer
• Publication Date: 2003
• Language: English
• ISBN 10: 1402076517
• ISBN 13: 9781402076510
• Binding: Hardcover
• Condition: As New

About this title

Synopsis

Biometrics such as fingerprint, face, gait, iris, voice and signature, recognizes one's identity using his/her physiological or behavioral characteristics. Among these biometric signs, fingerprint has been researched the longest period of time, and shows the most promising future in real-world applications. However, because of the complex distortions among the different impressions of the same finger, fingerprint recognition is still a challenging problem.

Computational Algorithms for Fingerprint Recognition presents an entire range of novel computational algorithms for fingerprint recognition. These include feature extraction, indexing, matching, classification, and performance prediction/validation methods, which have been compared with state-of-art algorithms and found to be effective and efficient on real-world data. All the algorithms have been evaluated on NIST-4 database from National Institute of Standards and Technology (NIST). Specific algorithms addressed include:
-Learned template based minutiae extraction algorithm,
-Triplets of minutiae based fingerprint indexing algorithm,
-Genetic algorithm based fingerprint matching algorithm,
-Genetic programming based feature learning algorithm for fingerprint classification,
-Comparison of classification and indexing based approaches for identification,
-Fundamental fingerprint matching performance prediction analysis and its validation.

Computational Algorithms for Fingerprint Recognition is designed for a professional audience composed of researchers and practitioners in industry. This book is also suitable as a secondary text for graduate-level students in computer science and engineering.