An advanced multi-modal method for human authentication featuring biometrics data and tokenised random numbers

In this work, we propose a multi-modalmethod that combines the scores of selected fingerprint matchers with the scores obtained by a Face Authenticator where the facial features are combined with pseudo-randomnumbers. We propose a novel method to combine the scores of fingerprint matchers based on random subspace Ensemble and we test the method on the systems submitted to FVC2004. Moreover, we show that methods based on tokenised pseudo-randomnumbers and user specific biometric features are highly dependent upon a parameter, the hashing threshold; we demonstrate that using an ensemble of classifiers it is possible to solve this problem leading to a considerable performance improvement. Finally, we study the fusion among the scores obtained by a Face Authenticator (where the face features are combined with pseudo-randomnumbers) and the scores of the systems submitted to FVC2004.