Robust Multi-Spectral Palm-Print Recognition

Abstract

In recent years, biometric has emerged as the most trustworthy and reliable technique for verifying or identifying humans. The distinctive and consistent qualities of palm prints have led to a rise in their use as a biometric attribute for user access and authentication. A palm-print template is proposed that stores the relative geometric information of the minutiae points. It is impossible to determine the orientation of the palm-print from the template since it lacks information on the orientation of the minutiae and their position. For template matching, an internal angle based on Delaunay triangulation is used, which then produces matching scores for various spectral bands. The multispectral data is finally integrated using a score-level fusion approach that minimizes the overlapping effects. The technique was evaluated on the widely used PolyU multispectral palm-print database, which provides more accurate results than a mono-spectral band. The total Correct Recognition Rate (CRR) is 96.28%, while the Equal Error Rate (EER) is 0.16%.