Verifying Fingerprint Match by Local Correlation Methods

Most fingerprint matching algorithms are based on finding correspondences between minutiae in two fingerprints. In this paper we present a modification of minutiae matching method, which utilizes correlation scores between the local neighborhood areas of corresponding minutiae pairs and the edges that connect neighboring matched minutiae pairs. Minutiae based matching approach considers the overall minutiae distribution pattern between the two fingerprints. Neighborhood correlation score represents the local similarity between the matched pair of minutiae. Edge correlation score gives the resemblance of areas that in between the two corresponding minutiae pairs. Thus, both the global minutiae distribution structure and the local matching similarity between the two fingerprints are considered for final decision. The described matching approach has been tested on FVC2002's DB1 and DB3 database. The experimental results confirm the effectiveness of combining matching scores of different origin - minutia matching score and local correlation matching scores.