Dorsal hand vein recognition across different devices

Abstract

With the fast development of the information, the application of distributed recognition system becomes more widespread. But the difference of hardware condition of terminal acquisition and all kinds of environments in distributed recognition system made biometric feature images different, which were gathered by different hardware. Include contrast, lightness, shifting, angle of rotation, size and so on. These differences will inevitably reduce accuracy of recognition and will not satisfy the development needs of the times. This paper synthetically analyses the important factors of heterogeneous dorsal hand vein images which are resulted by different devices. After normalizing grayscale images, this paper uses a segmentation method based on gradient difference to segment the texture of veins and uses SIFT to extract and match features. Discrimination in this paper can improve to 90.17 %, which is higher than other algorithms. This method can effectively solve the problem about dorsal hand vein recognition across different devices.