Finger Vein Recognition Based on Double-Orientation Coding Histogram

Abstract

More and more handcraft finger vein recognition algorithms have been proposed successively in recent years, and the orientation coding-based finger vein recognition has great research significance. In the paper, we offer a double orientation coding (DOC) method for finger vein recognition to represent the direction of vein texture using two orientation values. To strengthen the discrimination ability and robustness of the direction description, we further convert the DOC into the double orientation coding histogram (DOCH). Subsequently, since the proposed DOCH method cannot represent vein information adequately, we fuse DOCH with LBP scores. Finally, we propose a weighted score fusion strategy to improve recognition performance, which integrates the DOCH score and the LBP score with the chi-square distance and SVM respectively. Experimental results on two public databases (i.e., the MMCBNU_6000 and the FV-USM databases) demonstrate the effectiveness of our method for finger vein recognition, which has achieved 0.55% and 0.16% EERs.