Abstract:

In order to solve the shortcoming of fewer hand vein characteristics and lower recognition rates of hand vein recognition, we proposed a fusion method based on feature point distance of hand vein. Firstly, the hand vein is refined and matched the sum of quantized values of moment invariants feature; then the endpoints and the intersections of hand vein is extracted, and the improved Hausdorff distance is used to match, so the effects of zero point was removed, the degree of dissimilarity between two images was increased; finally, the two methods are weighted and fused. The experimental results show that fusion algorithm recognition rate can reach 96. 75%, and the running time is 0. 97 s.

Key words: biometrics, hand vein, feature points, moment invariants, Hausdorff distance, weighted fusion