Dorsal Hand Vein Recognition Method Based on Multi-bit Planes Optimization
With the development of technology, how to improve the accuracy of dorsal hand vein recognition has become the focus of current research. In order to solve this problem, this paper proposes a dorsal hand vein image recognition method which is based on multi-bit planes and Deep Learning network. The multi-bit planes can not only fully use the gray information of the images but also their intrinsic relationship between the bit planes of the images. In addition, the bit plane with less information is removed according to the Euclidean distance, and a new bit planes sequence is formed, and the accuracy of the recognition of the dorsal hand vein is improved. The algorithm is tested on the real dorsal hand vein database, and the recognition accuracy is more than 99%, which proves the effectiveness of the algorithm.
KeywordsDorsal hand vein recognition Multi-bit planes SqueezeNet network Euclidean distance
This work was supported by the National Natural Science Fund Committee of China (NSFC no. 61673021).
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