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Article Dans Une Revue IEEE Sensors Letters Année : 2022

Cross-Domain Consistent Fingerprint Denoising

Résumé

Performance of state-of-the-art fingerprint denoising model on poor quality fingerprints degrades due to crossdomain 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.
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Dates et versions

hal-03966789 , version 1 (31-01-2023)

Identifiants

Citer

Indu Joshi, Tashvik Dhamija, Rohit Kumar, Antitza Dantcheva, Sumantra Dutta Roy, et al.. Cross-Domain Consistent Fingerprint Denoising. IEEE Sensors Letters, 2022, 6 (8), ⟨10.1109/LSENS.2022.3193924⟩. ⟨hal-03966789⟩
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