Aiming at the problem that the finger vein image collected by infrared CCD camera is fuzzy, resulting in high error detection rate of finger vein recognition, this paper proposed super resolution reconstruction of digital vein image based on frequency division and residual of multi receptive field density. This method constructed the image high and low frequency information processing sub network, and integrated the RRFDB structure into the high frequency sub network. The residual dense block design with RFB as the core improved the receptive field, reduced the computational complexity, and better retained the linear texture features of the original digital vein image. The experimental results show that this method can effectively improve the image quality of finger vein. Compared with SRCNN, VDSR, DRRN and other super-resolution reconstruction methods on FV-USM and MMCBNU-6000, this method has good effect on finger vein feature extraction, high reconstructed image quality, and PSNR and SSIM are better than other methods.

[2021-12-13] Accepted Paper /doc/2021.08.0441/v1

[2022-06-05] Printed Article /doc/2021.08.0441/v2