This paper proposes a robust method to match distorted fingerprints. We first aligned the query and template fingerprints. To cope with the deformation brought by distorted fingerprints, we trained the distribution of orientation difference at a series of concentric circles around the corresponding pairs, and calculate the posterior probability of matched class using Bayesian method. We compute the score of unmatched absolute reliable minutiae by doubling the size of bounding box. Finally, we fuse the both scores with the score of matched minutiae using the multiplication rule. The experiments have been conducted on the public fingerprint collection, DB3 in FVC2002, and the results present that our method outperforms the conventional matching algorithm.
['Xiaolong Zheng', 'Yangsheng Wang', 'Xuying Zhao']
A Robust Matching Method for Distorted Fingerprints