Cross-Domain Consistent Fingerprint Denoising

Performance of the state-of-the-art fingerprint denoising model on poor-quality fingerprints degrades due to
cross-domain shift
observed between training and testing domains. To address this limitation, we present a
cross-domain consistent
fingerprint denoising model, which ensures that the output of two fingerprint images with the same ridge structure, however, varying contrast and ridge-valley clarity should be similar. Results indicate that the proposed CDC-GAN outperforms state-of-the-art fingerprint denoising algorithms on challenging publicly available poor-quality fingerprint databases.