Name
Abstract | ||
|---|---|---|
Most fingerprint recognition systems are based on the use of a minutiae set, which is an unordered collection of minutiae locations and orientations suffering from various deformations such as translation, rotation, and scaling. The spectral minutiae representation introduced in this paper is a novel method to represent a minutiae set as a fixed-length feature vector, which is invariant to translation, and in which rotation and scaling become translations, so that they can be easily compensated for. These characteristics enable the combination of fingerprint recognition systems with template protection schemes that require a fixed-length feature vector. This paper introduces the concept of algorithms for two representation methods: the location-based spectral minutiae representation and the orientation-based spectral minutiae representation. Both algorithms are evaluated using two correlation-based spectral minutiae matching algorithms. We present the performance of our algorithms on three fingerprint databases. We also show how the performance can be improved by using a fusion scheme and singular points. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/TIFS.2009.2021692 | IEEE Transactions on Information Forensics and Security |
Keywords | Field | DocType |
fusion scheme,fingerprint verification,fingerprint databases,location-based spectral minutiae representation,orientation-based spectral minutiae representation,fingerprint recognition,template protection.,fixed-length feature vector,fingerprint recognition system,representation method,correlation-based spectral minutia,index terms—biometrics,minutiae location,spectral minutiae representation,minutiae matching,feature vector,fingerprint identification,biometrics,bifurcation,fourier transforms,indexing terms,singular point | Computer vision,Feature vector,Pattern recognition,Fingerprint Verification Competition,Minutiae,Computer science,Fingerprint recognition,Fourier transform,Fingerprint,Artificial intelligence,Invariant (mathematics),Biometrics | Journal |
Volume | Issue | ISSN |
4 | 3 | 1556-6013 |
Citations | PageRank | References |
46 | 2.37 | 12 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Haiyun Xu | 1 | 130 | 15.77 |
| Raymond N. J. Veldhuis | 2 | 439 | 54.16 |
| a m bazen | 3 | 590 | 47.26 |
| Tom A. M. Kevenaar | 4 | 344 | 21.90 |
| Ton A. H. M. Akkermans | 5 | 46 | 2.37 |
| Berk Gokberk | 6 | 113 | 6.23 |