Cross-Domain Consistent Fingerprint Denoising

Abstract

Performance of the state-of-the-art fingerprint denoising model on poor-quality fingerprints degrades due to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">cross-domain shift</i> observed between training and testing domains. To address this limitation, we present a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">cross-domain consistent</i> 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.