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Solving non-linear distortion problems in fingerprint matching is important and still remains as a challenging topic. We have developed a new fingerprint matching method to deal with non-linear distortion problems efficiently by clustering locally matched minutiae and warping the fingerprint surface using minutiae clusters. Specifically, local invariant structures encoding the neighborhood information of each minutia are utilized in clustering the matched minutiae and then the fingerprint surface is warped to describe the deformation pattern properly. Finally, to make an additional increase in performance, the overlapped region of two fingerprints is considered in the score computation stage. Experimental results show that the proposed algorithm is performed best compared with other ones
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