Dorsal hand vein recognition based on directional filter bank

With the increasing needs of security systems, vein recognition is reliable as one of the important solutions for biometrics-based identification systems. The obvious and stable line-feature-based approach can be used to clearly describe dorsal hand vein patterns for personal identification. In this paper, a directional filter bank involving different orientations is designed to extract vein patterns and the minimum directional code is employed to encode line-based vein features into binary code. In addition, there are many non-vein areas in the vein image, which are not meaningful for vein recognition. To improve accuracy, the non-vein areas are detected by evaluating the variance of the minimum directional filtering response image and are considered as non-orientation code. In total, 4,280 dorsal hand vein images from 214 persons are used to validate the proposed dorsal hand vein recognition approach. A high accuracy (\(>\)99 %) and low equal error rate (0.54 %) were obtained using the proposed approach, which shows that the approach is feasible and effective for dorsal hand vein recognition.