A fingerprint matching algorithm based on probabilistic graphical model and three-tree model

Xiang Fu; Junjie Bian; Chongjin Liu; Jufu Feng

doi:10.1117/12.901645

2 December 2011 A fingerprint matching algorithm based on probabilistic graphical model and three-tree model

Xiang Fu, Junjie Bian, Chongjin Liu, Jufu Feng

Proceedings Volume 8004, MIPPR 2011: Pattern Recognition and Computer Vision; 800405 (2011) https://doi.org/10.1117/12.901645
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China

Abstract

Fingerprint matching is the most important part in the field of fingerprint recognition. In this paper, a novel fingerprint matching algorithm based on the probabilistic graphical model and 3-tree model is proposed. First, minutiae matching problems are considered as a special point-set matching. Fingerprint minutiae are viewed as random variables. Each minutia pairs have some probability to be matched. Second, an algorithm is proposed to generate the graphical model and choose "signal points", which dynamically have corresponding points in other point set. We choose three base minutiae pairs as signal pairs. Third, the model is converted into a Junction Tree. A 3-tree model is built and the potentials of other minutiae pairs are calculated through Junction Tree (J.T.) algorithm. Then we translate the matching problem into the best matching problem of a weighted bipartite graph. Finally, the number of common matching pairs can be got through maximum flow algorithm. The similarity of two fingerprints is evaluated using the number of common matching pairs and the maximal posteriori probability. In order to deal with part-matching problems, we use the smallest convex hull which contains all the matched minutiae. Experiments evaluated on FVC 2004 show both effectiveness and efficiency of our methods.

Citation Download Citation

Xiang Fu, Junjie Bian, Chongjin Liu, and Jufu Feng "A fingerprint matching algorithm based on probabilistic graphical model and three-tree model", Proc. SPIE 8004, MIPPR 2011: Pattern Recognition and Computer Vision, 800405 (2 December 2011); https://doi.org/10.1117/12.901645

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KEYWORDS

Detection and tracking algorithms

Fluctuations and noise

Databases

Distributed interactive simulations

Stars

Fingerprint recognition

Distance measurement

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