The performance of Automatic Fingerprint Identification Systems (AFIS) relies on the quality of the input fingerprints, so the enhancement of noisy images is a critical step. We propose a new fingerprint enhancement algorithm that selectively applies contextual filtering starting from automatically-detected high-quality regions and then iteratively expanding to low-quality ones. The proposed algorithm does not require any prior information like local orientations or frequencies. Experimental results over both real (FVC2004 and FVC2006) and synthetic (generated by the SFinGe software) fingerprints demonstrate the effectiveness of the proposed method.
R. Cappelli, D. Maltoni , F. Turroni (2012). Fingerprint Enhancement using Contextual Iterative Filtering. s.l : IEEE [10.1109/ICB.2012.6199773].
Fingerprint Enhancement using Contextual Iterative Filtering
CAPPELLI, RAFFAELE;MALTONI, DAVIDE;TURRONI, FRANCESCO
2012
Abstract
The performance of Automatic Fingerprint Identification Systems (AFIS) relies on the quality of the input fingerprints, so the enhancement of noisy images is a critical step. We propose a new fingerprint enhancement algorithm that selectively applies contextual filtering starting from automatically-detected high-quality regions and then iteratively expanding to low-quality ones. The proposed algorithm does not require any prior information like local orientations or frequencies. Experimental results over both real (FVC2004 and FVC2006) and synthetic (generated by the SFinGe software) fingerprints demonstrate the effectiveness of the proposed method.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
