Bir Bhanu, Xuejun Tan

Computational Algorithms for Fingerprint Recognition (eBook, PDF)

• Format: PDF

Produktbeschreibung

Fingerprints are the most established from of biometrics with 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. This book presents an entire range of novel computational algorithms for fingerprint recognition, all evaluated by the National Institute of Standards and Technology (NIST). 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.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Springer US
• Seitenzahl: 191
• Erscheinungstermin: 6. Dezember 2012
• Englisch
• ISBN-13: 9781461504917
• Artikelnr.: 44053037

Autorenporträt

Fingerprints are the most established from of biometrics with 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. This book presents an entire range of novel computational algorithms for fingerprint recognition, all evaluated by the National Institute of Standards and Technology (NIST). 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.

Inhaltsangabe

1. Introduction.- 2. Learned Templates for Minutiae Extraction.- 3. Fingerprint Indexing.- 4. Fingerprint Matching by Genetic Algorithms.- 5. Genetic Programming for Fingerprint Classification.- 6. Classification and Indexing Approaches for Identification.- 7. Fundamental Performance Analysis - Prediction and Validation.- 8. Summary and Future Work.- References.