A performance evaluation of shape and texture based methods for vein recognition

This paper gives fair comparisons of shape and texture based methods for vein recognition. The shape of the back of hand contains information that is capable of authenticating the identity of an individual. In this paper, two kinds of shape matching method are used, which are based on Hausdorff distance and Line Edge Mapping(LEM) methods. The vein image also contains valuable texture information, and Gabor wavelet is exploited to extract the discriminative feature. In order to evaluate the system performance, a dataset of 100 persons of different ages above 16 and of different gender, each has 5 images per person is used. Experimental results show that Hausdorff LEM and Gabor based methods achieved 58%, 66% 80% individually.