A Novel Method of Score Level Fusion Using Multiple Impressions for Fingerprint Verification

How to improve the performance of an existing biometric system is always interesting and meaningful. In this paper, we present a novel method of score level fusion using multiple enrolled impressions to achieve higher verification accuracy of existing fingerprint systems. The main idea of the method is to build a representation of the biometric reference as a polyhedron by taking into account the matching results of multiple enrolled impressions. The verification step consists in measuring a distance between the centroid of the polyhedron and the acquired image. This novel method outperforms the traditional uni-matcher based scheme over a wide range of FAR and FRR values. The equal error rate of our method is observed to be 2.25%, while that of the uni-matcher is 5.75%.