A novel algorithm for distorted fingerprint matching based on fuzzy features match

Coping with non-linear distortions in fingerprint matching is a real challenging task. This paper proposed a novel method, fuzzy features match (FFM), to match the deformed fingerprints. The fingerprint was represented by the fuzzy features: local triangle features set. The similarity between fuzzy features is used to character the similarity between fingerprints. First, a fuzzy similarity measure for two triangles was introduced. Second, the result is extended to construct a similarity vector which includes the triangle-level similarities for all triangles in two fingerprints. Accordingly, a similarity vector pair is defined to illustrate the similarities between two fingerprints. Finally, the FFM measure maps a similarity vector pair to a scalar quantity, within the real interval [0, 1], which quantifies the overall image to image similarity. To validate the method, fingerprints of FVC2004 were evaluated with the proposed algorithm. Experimental results show that FFM is a reliable and effective algorithm for fingerprint matching with non-liner distortions.