Spurious fingerprint minutiae detection based on multiscale directional information

Abstract

Amongst available biometrics, personal identification based on fingerprints is still considered for one of the most reliable identification method. Most AFIS available today uses distinctive fingerprint features called minutiae for fingerprint comparison. Conventional feature extraction algorithm can produce a large number of spurious minutiae if fingerprint pattern contains large regions of broken ridges. This can drastically reduce the recognition rate in automatic fingerprint identification systems. In this paper multiscale directional information obtained from orientation image is used to detect and filter those spurious minutiae, resulting in multiple decrease of their number.