Deep Encoder-Decoder Neural Network for Fingerprint Image Denoising and Inpainting
Fingerprint image denoising is a very important step in fingerprint identification. to improve the denoising effect of fingerprint image,we have designs a fingerprint denoising algorithm based on deep encoder-decoder network,which encoder subnet to learn the fingerprint features of noisy images.the decoder subnet reconstructs the original fingerprint image based on the features to achieve denoising, while using the dilated convolution in the network to increase the receptor field without increasing the complexity and improve the network inference speed. In addition, feature fusion at different levels of the network is achieved through the introduction of residual learning, which further restores the detailed features of the fingerprint and improves the denoising effect. Finally, the experimental results show that the algorithm enables better recovery of edge, line and curve features in fingerprint images, with better visual effects and higher peak signal-to-noise ratio (PSNR) compared to other methods.
Code (0)
등록된 구현이 없습니다.
Tasks
DecoderDenoisingImage DenoisingMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
FPD-M-net: Fingerprint Image Denoising and Inpainting Using M-Net Based Convolutional Neural Networks
Fingerprint is a common biometric used for authentication and verification of an individual. These images are degraded when fingers are wet, dirty, dry or wounded and due to the failure of the sensors, etc. The extractio…
DenoisingImage DenoisingU-Finger: Multi-Scale Dilated Convolutional Network for Fingerprint Image Denoising and Inpainting
This paper studies the challenging problem of fingerprint image denoising and inpainting. To tackle the challenge of suppressing complicated artifacts (blur, brightness, contrast, elastic transformation, occlusion, scrat…
DenoisingImage DenoisingSSIMResWCAE: Biometric Pattern Image Denoising Using Residual Wavelet-Conditioned Autoencoder
The utilization of biometric authentication with pattern images is increasingly popular in compact Internet of Things (IoT) devices. However, the reliability of such systems can be compromised by image quality issues, pa…
DecoderDenoisingImage DenoisingDeep End-to-end Fingerprint Denoising and Inpainting
This work describes our winning solution for the Chalearn LAP In-painting Competition Track 3 - Fingerprint Denoising and In-painting. The objective of this competition is to reduce noise, remove the background pattern a…
DenoisingMulti-level Encoder-Decoder Architectures for Image Restoration
Many real-world solutions for image restoration are learning-free and based on handcrafted image priors such as self-similarity. Recently, deep-learning methods that use training data have achieved state-of-the-art resul…
DecoderDenoisingImage ReconstructionImage Restoration+1