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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