A multi-matcher system based on knuckle-based features

Authors:
Loris Nanni;Alessandra Lumini
Affiliations:
Università di Bologna, DEIS, IEIIT-CNR, Viale Risorgimento 2, 40136, Bologna, Italy;Università di Bologna, DEIS, IEIIT-CNR, Viale Risorgimento 2, 40136, Bologna, Italy
Venue:
Neural Computing and Applications
Year:
2009

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Abstract

We describe a new multi-matcher biometric approach, using knuckle-based features extracted from the middle finger and from the ring finger, with fusion applied at the matching-score level. The features extraction is performed by Radon transform and by Haar wavelet, then these features are transformed by non-linear Fisher transform. Finally, the matching process is based on Parzen window classifiers. Moreover, we study a method based on tokenised pseudo-random numbers and user specific knuckle features. The experimental results show the effectiveness of the system in terms of equal error rate (EER) (near zero equal error rate).