A Palmprint Verification System Based on Phase Congruency Features

Vitomir Struc, Nikola Pavesic

Abstract: The paper presents a fully automatic palmprint verification system which uses 2D phase congruency to extract line features from a palmprint image and subsequently performs linear discriminant analysis on the computed line features to represent them in a more compact manner. The system was trained and tested on a database of 200 people (2000 hand images) and achieved a false acceptance rate (FAR) of 0.26% and a false rejection rate (FRR) of 1.39% in the best performing verification experiment. In a comparison, where in addition to the proposed system, three popular palmprint recognition techniques were tested for their verification accuracy, the proposed system performed the best.