Analytical Study on Fingerprint Singular Point Detection

Abstract

Biometric fingerprint features are used to provide an authentication for computer based security system. Fingerprint image analysis is based on the location and pattern of detected singular point is one of the important processing methods. The singular points of fingerprints, namely, core and delta, are important referential points for the classification of fingerprints. The finger image characteristics of local ridge patterns but also determine the fingerprint type and largely influence the orientation field, and are very much used for finger matching. In order to use both the local and global features of the ridge direction patterns and to realize a method with high tolerance to local image noise, singular candidate analysis is adopted in the detection process. This analysis involves the extraction of locations in which the probability of the existence of a singular point is high. In this paper the performance analysis can be compared with singular point detection methods to analyze the algorithmic accuracy and robustness.