Vein recognition, as an emerging biometric recognition approach, is becoming a very active topic in both research and practical applications. In our framework, the minutiae features is extracted from the dorsal hand vein patterns for recognition, which include end points and the distance between the two end points as measured along the boundary of the image.
In addition, the end-points-tree (EP-tree) is proposed to accelerate the matching performance and evaluate the discriminating power of these end points for person verification purposes. We employed a total of 4,280 images of dorsal hand veins from 214 individuals in order to validate the proposed recognition method. In a comparison with three existing verification algorithms, the proposed method achieves the highest accuracy in the lowest matching time.