Wrist Vein Recognition by Fusion of Multiple Handcrafted Methods

Abstract

A wrist vein recognition system is proposed in this paper. The system combines three texture-based feature descriptors, namely, multiple filters of Binarized Statistical Image Features (M-BSIF), 2D Gabor filter, and Histogram of Gradient orientation by Decision-Level Fusion. The method was tested on two publicly available datasets obtained from FYO and PUT databases. The proposed method outperforms the individual descriptors and achieves 95.63% and 93.92% accuracies on FYO and PUT databases, respectively.