Dorsal hand vein recognition based on Gabor multi-orientation fusion and multi-scale HOG features
Tuo Han, Zhiyong Wang, Xiaoping Yang · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2016
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.