Computational Algorithms for Fingerprint Recognition
Authors: Bhanu, Bir, Tan, Xuejun
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- About this book
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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.
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Computational Algorithms for Fingerprint Recognition
- Authors
-
- Bir Bhanu
- Xuejun Tan
- Series Title
- International Series on Biometrics
- Series Volume
- 1
- Copyright
- 2004
- Publisher
- Springer US
- Copyright Holder
- Springer Science+Business Media New York
- eBook ISBN
- 978-1-4615-0491-7
- DOI
- 10.1007/978-1-4615-0491-7
- Hardcover ISBN
- 978-1-4020-7651-0
- Softcover ISBN
- 978-1-4613-5103-0
- Edition Number
- 1
- Number of Pages
- XX, 191
- Topics
