Fingerprint Minutia Matching Using Local Alignment

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We proposes a new fingerprint minutia matching algorithm which matches the fingerprint minutiae by using local alignment. In general, fingerprint is deformed by Pressure and orientation when a user presses his fingerprint to the sensor. These nonlinear deformations change the position and the orientation of minutiae which decrease reliability of minutiae. Matching by using global alignment uses one alignment point. But, the problem with this method is that, due to the deformation, matching reliability of a minutia decreases as the distance from the alignment minutia increases. Matching by using local alignment overcomes this problem by considering minutiae which are located in a short distance boundary. Experimental results show that the performance of the proposed algorithm is superior to that of using global alignment.