Pavel Kisilev, Daniel Freedman, et al.
ICPR 2012
Fingerprint matching is challenging as the matcher has to minimize two competing error rates: the False Accept Rate and the False Reject Rate. We propose a novel, efficient, accurate and distortion-tolerant fingerprint authentication technique based on graph representation. Using the fingerprint minutiae features, a labeled, and weighted graph of minutiae is constructed for both the query fingerprint and the reference fingerprint. In the first phase, we obtain a minimum set of matched node pairs by matching their neighborhood structures. In the second phase, we include more pairs in the match by comparing distances with respect to matched pairs obtained in first phase. An optional third phase, extending the neighborhood around each feature, is entered if we cannot arrive at a decision based on the analysis in first two phases. The proposed algorithm has been tested with excellent results on a large private livescan database obtained with optical scanners.
Pavel Kisilev, Daniel Freedman, et al.
ICPR 2012
Michelle X. Zhou, Fei Wang, et al.
ICMEW 2013
Sudeep Sarkar, Kim L. Boyer
Computer Vision and Image Understanding
James E. Gentile, Nalini Ratha, et al.
BTAS 2009