Image-based approaches based on one-class classifiers are presented. The information is extracted with a feature-based representation and recognized by using an ensemble of one-class classifiers. The features extracted by “FingerCode” are used to capture the ridge strength. The experiments show that our system outperforms the standard “FingerCode” recognition method.
Nanni, L., Lumini, A. (2006). Random Bands: A novel ensemble for fingerprint matching. NEUROCOMPUTING, 69, 1702-1705 [10.1016/j.neucom.2006.01.011].
Random Bands: A novel ensemble for fingerprint matching
NANNI, LORIS;LUMINI, ALESSANDRA
2006
Abstract
Image-based approaches based on one-class classifiers are presented. The information is extracted with a feature-based representation and recognized by using an ensemble of one-class classifiers. The features extracted by “FingerCode” are used to capture the ridge strength. The experiments show that our system outperforms the standard “FingerCode” recognition method.File in questo prodotto:
Eventuali allegati, non sono esposti
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
