Using Global Features for Pre-classification in Online Signature Verification Systems

Abstract

In this paper, a pre-classification stage based on global features is incorporated to an online signature verification system for the purposes of improving its performance. The pre-classifier makes use of the discriminative power of some global features to discard (by declaring them as forgeries) those signatures for which the associated global features are far away from their respective means. Global features are considered individually and in a combined form for pre-classification. The subsequent classification stage is based on features obtained from a wavelet approximation of the time functions associated with the signing process. The experimental results show that the proposed pre-classification approach is capable of getting error rate improvements with respect to the case where no pre-classification is performed, having also the advantages of simplifying and speeding up the verification process.