Paper
12 April 2007 Use of ridge points in partial fingerprint matching
Author Affiliations +
Abstract
Matching of partial fingerprints has important applications in both biometrics and forensics. It is well-known that the accuracy of minutiae-based matching algorithms dramatically decrease as the number of available minutiae decreases. When singular structures such as core and delta are unavailable, general ridges can be utilized. Some existing highly accurate minutiae matchers do use local ridge similarity for fingerprint alignment. However, ridges cover relatively larger regions, and therefore ridge similarity models are sensitive to non-linear deformation. An algorithm is proposed here to utilize ridges more effectively- by utilizing representative ridge points. These points are represented similar to minutiae and used together with minutiae in existing minutiae matchers with simple modification. Algorithm effectiveness is demonstrated using both full and partial fingerprints. The performance is compared against two minutiae-only matchers (Bozorth and k-minutiae). Effectiveness with full fingerprint matching is demonstrated using the four databases of FVC2002- where the error rate decreases by 0.2-0.7% using the best matching algorithm. The effectiveness is more significant in the case of partial fingerprint matching- which is demonstrated with sixty partial fingerprint databases generated from FVC2002 (with five levels of numbers of minutiae available). When only 15 minutiae are available the error rate decreases 5-7.5%. Thus the method, which involves selecting representative ridge points, minutiae matcher modification, and a group of minutiae matchers, demonstrates improved performance on full and especially partial fingerprint matching.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gang Fang, Sargur N. Srihari, Harish Srinivasan, and Prasad Phatak "Use of ridge points in partial fingerprint matching", Proc. SPIE 6539, Biometric Technology for Human Identification IV, 65390D (12 April 2007); https://doi.org/10.1117/12.718941
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Cited by 29 scholarly publications.
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KEYWORDS
Databases

Biometrics

Forensic science

Statistical modeling

Computer simulations

Performance modeling

Tolerancing

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