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Fingerprint image denoising is a very important step in fingerprintidentification. to improve the denoising effect of fingerprint image,we havedesigns a fingerprint denoising algorithm based on deep encoder-decodernetwork,which encoder subnet to learn the fingerprint features of noisyimages.the decoder subnet reconstructs the original fingerprint image based onthe features to achieve denoising, while using the dilated convolution in thenetwork to increase the receptor field without increasing the complexity andimprove the network inference speed. In addition, feature fusion at differentlevels of the network is achieved through the introduction of residuallearning, which further restores the detailed features of the fingerprint andimproves the denoising effect. Finally, the experimental results show that thealgorithm enables better recovery of edge, line and curve features infingerprint images, with better visual effects and higher peak signal-to-noiseratio (PSNR) compared to other methods.

Deep Encoder-Decoder Neural Network for Fingerprint Image Denoising and Inpainting