Focal point detection based on half concentric lens model for singular point extraction in fingerprint

Abstract

A focal point is a kind of singular points, closely related to a core point, which can be derived from curvature of fingerprint ridges and valleys. It is expected that the focal point is more reliable than the core point in case of low quality fingerprint. This paper proposes a new efficient focal point localization method based on a half concentric lens model. The half concentric lens window, with directional adaptive, accelerates convergence of a focal point localization process rapidly. Moreover, concentric lens similarity factor is introduced in order to measure orientation and stability of an extracted focal point. From experimental results, the proposed scheme is out-performed most of singular point detection schemes in literature in term of location accuracy and consistency. For computational complexity, algorithm requires average 75 millisecond execution-time from original fingerprint to a unique focal point. © Springer-Verlag Berlin Heidelberg 2009.