A Novel Fingerprint Matching Algorithm Using Ridge Curvature Feature

Authors:
Peng Li;Xin Yang;Qi Su;Yangyang Zhang;Jie Tian
Affiliations:
Institute of Automation, Chinese Academy of Sciences, Beijing, China 100190;Institute of Automation, Chinese Academy of Sciences, Beijing, China 100190;Institute of Automation, Chinese Academy of Sciences, Beijing, China 100190;Institute of Automation, Chinese Academy of Sciences, Beijing, China 100190;Institute of Automation, Chinese Academy of Sciences, Beijing, China 100190
Venue:
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Year:
2009

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Abstract

Fingerprint matching based on solely minutiae feature ignore the abundant ridge information in fingerprint images. We propose a novel fingerprint matching algorithm which integrates minutiae feature with ridge curvature map(RCM). The RCM is approximated by a polynomial model which is computed by Least Square(LS) method. In the matching stage, phase-only correlation matching method is employed to match two RCMs. Then sum fusion rule is selected to combine the minutiae matching score and the RCM matching score. Experiments conducted on FVC2002 and FVC2004 databases show that proposed algorithm can obtain more promising performance than solely minutiae-based algorithm and several other multi-feature fusion algorithms.