A novel algorithm for fingerprint singular points detection based on vecrot orthogonal theory

Fingerprint recognition is a widely used biometric identification mechanism. The singular points of fingerprints are important referential points for the fingerprint classification and fingerprint matching. In this paper, we propose a novel algorithm for detecting the singular points. The method is based on vector orthogonal theory and the fact that the singular points have special pattern of the orientation field. We use the same mask to detect the core points and delta points in different field. After applying the special mask, the core points and delta points will be detected in the orientation field and double orientation field respectively. To substantiate the performance of our approach, we have experimented with fvc2002 and fvc2004 database. Experimental results show that our algorithm is accurate and robust, giving better results than competing approaches.