Fingerprint matching using the distribution of the pairwise distances between minutiae

Authors:
Chul-Hyun Park;Mark J. T. Smith;Mireille Boutin;Joon-Jae Lee
Affiliations:
School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN;School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN;School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN;Division of Internet Engineering, Dongseo University, Busan, Korea
Venue:
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Year:
2005

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Abstract

This paper presents an efficient minutiae-based fingerprint representation and matching method using the distribution of distances between points. The proposed method uses the distribution of pairwise distances between minutiae as fingerprint features. The fingerprint matching between the input and the template fingerprints is performed by considering the Euclidean distance between the distributions. Most conventional minutiae matching methods require intensive comparing in order to align the two fingerprints translationally and rotationally, whereas the proposed method does not need such an intensive comparison procedure for the alignment. In addition, the feature vector generated by the proposed method has a small and fixed length, which is more advantageous in some applications such as smart cards. The experiments using the randomly generated 800 minutiae sets and our database consisting of 800 fingerprints show that the proposed method can be used effectively in applications that have limited memory and require high speed.