TY - GEN
T1 - A novel multi-reference points fingerprint matching method
AU - Mao, Keming
AU - Wang, Guoren
AU - Yu, Changyong
AU - Jin, Yan
PY - 2009
Y1 - 2009
N2 - 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.
AB - 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.
KW - Fingerprint matching
KW - Minutiae-cell
KW - Multi-reference
KW - Multi-stage
UR - https://www.scopus.com/pages/publications/59049091914
U2 - 10.1007/978-3-540-92892-8_37
DO - 10.1007/978-3-540-92892-8_37
M3 - Conference contribution
AN - SCOPUS:59049091914
SN - 354092891X
SN - 9783540928911
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 356
EP - 366
BT - Advances in Multimedia Modeling - 15th International Multimedia Modeling Conference, MMM 2009, Proceedings
T2 - 15th International Multimedia Modeling Conference, MMM 2009
Y2 - 7 January 2009 through 9 January 2009
ER -