Fingerprint matching based on ridge similarity

This paper proposes a method for fingerprint matching based on the local ridge similarity. Different from traditional methods which estimate rotation angle between a query and template minutia using orientation field, our approach estimates the local rotation angle directly from sampling points of ridges. After fitting samples by least square method, the optimal local rotation angle is obtained, moreover, the similarity between two ridges is measured by virtue of the fitting error. The best reference pair is then determined in the smoothed similarity histogram. Finally, a matching score is computed by projecting the query minutiae set to the template according to the best reference. The experimental results on the public fingerprint database, FVC2002 DB3(800 fingerprints, 8 impressions per finger) and a self-collected database(880 fingerprints, 5 impressions per finger), show that our approach is more effective compared with the conventional ridges-based approach.