An effective algorithm for fingerprint matching

Fingerprint matching is one of the most important stages in automatic fingerprint identification systems (AFIS). Traditional methods treat this problem as point pattern matching, which is essentially an intractable problem due to the various linear deformations commonly observed in fingerprint images. We propose an effective fingerprint matching algorithm based on error propagation. Firstly, ridge information and Hough transformation are adopted to find several pairs of matching minutiae, the initial correspondences, which are used to estimate the common region of two fingerprints and the alignment parameters. Then a matched set which includes the correspondence and its surrounding matched minutiae pairs is established. The subsequent matching process is guided by the concept of error propagation: the matching errors of each unmatched minutiae are estimated according to those of its most relevant neighbor minutiae. In order to prevent the process from being misguided by mismatched minutiae pairs, we adopt a flexible propagation scheme. Experimental results demonstrate the robustness of our algorithm to non-linear deformation.