Partial palm vein based biometric authentication

Abstract

Palm vein biometrics is a potential authentication technique. In addition to the inherent liveness property, the palm vein pattern exhibits high authentication accuracy and anti-spoofing capability due to the dense vein pattern and broad coverage area. However, the large palm size increases the acquisition device’s cost and size and significantly hinders device miniaturization, resulting in the limited applicability of palm vein biometrics. A solution to this problem is to restrict the area of the palm vein pattern required for authentication. Towards this, in this paper, we explore the potential of partial palm vein patterns for authentication. Through experimentation with varied-sized partial palm vein images, we show that (14)th of palm vein pattern is adequate for individual authentication. Based on this observation, we propose an authentication framework using partial palm vein patterns. The system takes (14)th palm vein pattern as input in both the enrollment and authentication phase, and partial to full image matching is performed. We propose a rule-based image acquisition and stitching method for accurately converting partial images into full images during enrollment. The proposed partial palm vein authentication framework using elastic matching achieved an Equal Error Rate (EER) of 0.0202%, 0.1919%, and 0.2282% on the CASIA, VERA, and PUT datasets, respectively. Experiments using deep feature matching also gave comparable results to elastic matching.