A modified singular point detection algorithm

Abstract

Automatic Fingerprint Identification Systems (AFIS) are widely used for personal identification due to uniqueness of fingerprints. Fingerprint reference points are useful for fingerprint classification and even for fingerprint matching algorithms. In this paper, we present a modified algorithm for singular points detection (cores and deltas) with high accuracy. Optimally located cores and deltas are necessary for classification and matching of fingerprint images. The previous techniques detect only a single core point which is inefficient to classify an image. The basic feature of our technique is that it computes all the cores along with all the deltas present in a fingerprint image. The proposed algorithm is applied on FVC2002, and experimental results are compared with the previous techniques, which verify the accuracy of our algorithm. © 2008 Springer-Verlag Berlin Heidelberg.