Palm Vein Recognition Based on Multi-algorithm and Score-Level Fusion

Abstract

In order to improve the recognition rate of palm vein recognition algorithm, a recognition algorithm based on SIFT and ORB features extraction and score-level fusion is presented in this paper. Score-level fusion is an information fusion technique, which has six common combination rules. Two dynamic weight combination rules are proposed as a supplement here. The main steps of the proposed algorithm are: First, extract Region of interest (ROI) from the registered palm vein image and the to-be-matched palm vein image and process them with sharpen enhancement, and then extract SIFT features and ORB features and obtain matching scores respectively, finally utilize score-level fusion to compute the final score for decision. The experiments on the CASIA Palm Vein Image Database show that the algorithm attains the best recognition rate by utilizing the min-rule, and the equal error rate (EER) is 0.36%.