A Score-Level Fusion Method with Prior Knowledge for Fingerprint Matching

Fingerprint matching is one of the most widely used biometrics for personal identification. However, the performance of fingerprint identification system is insufficient for many applications. Lots of methods were proposed to improve system performance by introducing more information into matching process. In this paper, we introduced a new kind of information named prior knowledge and proposed a score-level fusion method with prior knowledge for fingerprint matching. The trend and discrimination of scores are used as prior knowledge with sigmoid function to search the optimal fusion parameters. Experimental results show that the proposed prior knowledge is useful for fingerprint matching and the score-level fusion algorithm is effective to improve system performance and comparative to the best ones in FVC2004.