It is necessary to improve the quality of the captured hand vein image in the vein display device and vein recognition system. In this paper, a method of hand vein image enhancement based on phase congruency is proposed according to the structure and features of human hand vein images. Firstly, multiple images containing vein edges are acquired by applying phase congruency which parameters are set differently, and two images that contain the majority of vein and less noise are selected by image entropy values, then the chosen images will be enhanced by contrast enhancement. Finally, the original image and the enhanced image will be fused in gradient domain. The experiment results show that the proposed algorithm can enhance the contrast of the hand vein images efficiently, improve the quality of image significantly, and suppress noise perfectly.
Kinds of factors such as illumination and hand gestures would reduce the accuracy of dorsal hand vein recognition. Aiming at single hand vein image with low contrast and simple structure, an algorithm combining Gabor multi-orientation features fusion with Multi-scale Histogram of Oriented Gradient (MS-HOG) is proposed in this paper. With this method, more features will be extracted to improve the recognition accuracy. Firstly, diagrams of multi-scale and multi-orientation are acquired using Gabor transformation, then the Gabor features of the same scale and multi-orientation will be fused, and the features of the correspondent fusion diagrams will be extracted with a HOG operator of a certain scale. Finally the multi-scale cascaded histograms will be obtained for hand vein recognition. The experimental results show that our method not only improve the recognition accuracy but has good robustness in dorsal hand vein recognition.