A robust fingerprint matching algorithm using local alignment

This paper describes a minutiae-based fingerprint matching algorithm. Generally, a fingerprint image is nonlinearly deformed by torsion and traction when a finger is pressed on the sensor. This nonlinear deformation changes both position and orientation of minutiae and decreases the reliability of minutiae. Therefore, in matching algorithm using one reference minutiae pair, the reliability of a minutia decreases as the distance from the minutia to the minutia used for alignment increases. The proposed algorithm overcomes this problem by normalizing the distance between minutiae and using local alignment. Experimental results show that the performance of the proposed algorithm is superior to that of using one reference minutiae pair.