Combining fingerprint and hand-geometry verification decisions

Abstract

This paper proposes to combine the fingerprint and handgeometry verification decisions using a reduced multivariate polynomials model. Main advantage of this method over those neural network based methods is that only a single step is required for training and the training is optimal. Numerical experiments using a database containing over 100 identities show significant improvement of Receiver Operating Characteristics as compared to that of individual biometrics. Moreover, the result outperforms a few commonly used methods using the same database. © Springer-Verlag 2003.