A Novel Method for Fingerprint Core Point Detection

Abstract

Abstract- Fingerprint recognition is a method of biometric authentication that uses pattern recognition techniques based on highresolution fingerprints images of the individual. Fingerprints have been used in forensic as well as commercial applications for identification as well as verification. Singular point detection is the most important task of fingerprint image classification operation. Two types of singular points called core and delta points are claimed to be enough to classify the fingerprints. The classification can act as an important indexing mechanism for large fingerprint databases which can reduce the query time and the computational complexity. Usually fingerprint images have noisy background and the local orientation field also changes very rapidly in the singular point area. It is difficult to locate the singular point precisely. There already exists many singular point detection algorithms, Most of them can efficiently detect the core point when the image quality is fine, but when the image quality is poor, the efficiency of the algorithm degrades rapidly. In the present work, a new method of detection and localization of core points in a fingerprint image is proposed.