**5. Conclusions**

Aiming at the problem that the recognition rate of the dorsal hand vein image collected by different devices is not high, this paper proposes a research method-based bit plane and block mutual information. The optimal block is determined by the variance corresponding to the average entropy matrix, the gray-normalized image, the binary image, the gray image that only retains the contour of dorsal hand vein, and the bit planes are tested respectively under various mutual information calculation modes. By comparing other algorithms used on cross-device hand vein recognition, the method proposed in this paper has been significantly improved. However, at present, only the one-bit plane is processed separately, therefore, the fusion and optimization of multiple bit planes will be the focus of further research in the later stage.

**Author Contributions:** Y.W. provided the ideas and methods of the whole article. H.C. designed the experiment and conducted experimental analysis on the proposed algorithm. Partial preparatory work was done with the help of X.J., Y.T. was finally responsible for the review of the thesis.

**Funding:** National Natural Science Fund Committee of China (NSFC No. 61673021).

**Acknowledgments:** This work was supported by the National Natural Science Fund Committee of China (NSFC No. 61673021).

**Conflicts of Interest:** The authors declare no conflicts of interest.
