Dorsal Hand Vein Recognition Method Based on Multi-bit Planes Optimization

  • Haoxuan LiEmail author
  • Yiding Wang
  • Xiaochen Jiang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10996)


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.


Dorsal 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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© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.North China University of TechnologyBeijingChina

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