On-Line Fingerprint Verification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fingerprint Image Enhancement: Algorithm and Performance Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fingerprint Matching Using Feature Space Correlation
ECCV '02 Proceedings of the International ECCV 2002 Workshop Copenhagen on Biometric Authentication
A Robust Fingerprint Matching Algorithm Using Local Alignment
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Fingerprint verification based on minutiae features: a review
Pattern Analysis & Applications
An efficient algorithm for fingerprint matching
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
A novel fingerprint matching method by excluding elastic distortion
DASFAA'08 Proceedings of the 13th international conference on Database systems for advanced applications
ICCSA'05 Proceedings of the 2005 international conference on Computational Science and its Applications - Volume Part I
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Filterbank-based fingerprint matching
IEEE Transactions on Image Processing
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Fingerprint matching is a challenging problem due to complex distortion in fingerprint image. In this paper, a multi-reference points matching method is proposed to solve the problem. First, a new feature description Minutiae -Cell , which is constructed by the minutiae and its neighbor ridges, is used to represent the local structure of the fingerprint. The proposed matching method consists of three stages, including the original matching stage ,the purifying stage and the fingal matching stage. In the original matching stage, minutiae pairs that potentially matched are found based on the Minutiae -Cell and the. Then the purifying stage is carried out to obtain the true matched minutiae pairs. Instead of using only one reference pair, the final matching stage deals with the remaining minutiae from template and query fingerprints by comparing their distance to the true matched minutiae pair set. The matching score is composed of the results of purifying stage and final matching stage. The proposed method overcomes the problems of distortion and noises existing in the fingerprint image. Experimental results show that the performance of the proposed algorithm is satisfying.