Combining left and right wrist vein images for personal verification

Abstract

Multibiometric systems that fuse information from different sources are able to alleviate limitations of the unimodal biometric systems. In this paper, we propose a multibiometric framework to identify people using their left and right wrist vein patterns. The framework uses a fast and robust preprocessing and feature extraction method. A generic score level fusion approach is proposed to integrate the scores from left and right wrist vein patterns using Dubois and Parad triangular-norm (t-norm). Experiments on the publicly available PUT wrist vein dataset show that the proposed multibiometric framework outperforms the unimodal systems, their fusion using other t-norms techniques, and existing wrist vein recognition methods.