Palm-Dorsal Vein Recognition Method Based on Histogram of Local Gabor Phase XOR Pattern with Second Identification

Abstract

This paper proposes a palm-dorsal vein recognition method with local Gabor phase features, which includes a second identification for more accuracy. First, we extract quadrant-bit codes from the 2D Gabor transformation of a vein image. Then using the Histogram of the Local Gabor Phase XOR Pattern (HLGPXP) obtains the vein texture features, which combines the global information and the local information. Finally, the chi-square distance is adopted for recognition. Using the texture features based on the local Gabor codes above, the Second Identification (SI) segments the vein images and regards the non-overlap degree between images as a matching criterion. The experimental results show the Error Equation Rate (EER) of our method (HLGPXP-SI) decreases by 11.7 %, 4.8 % respectively than Modified Local Binary Pattern (MLBP) [1], Local Gabor Binary Pattern (LGBP) [2] on Database A (204 high-quality palm-dorsal vein images from 68 hands), and on Database B (400 low-quality palm-dorsal vein images from 100 hands), it decreases by 18.94 %, 15.51 % respectively than Selected Gabor Phase and Amplitude Features (SGPAF) [3], Direct Gabor Phase Coding (DGPC) [4].