Feature selection in automatic signature verification

Automatic handwritten signature verification (ASV) is potentially the most powerful and publicly acceptable means of personal authentication available, and has a long history with applications to be found in cheque authorisation, document image analysis, and access control. In the past such effort has been expended in attempting to find an universal set of features suitable for verifying all classes of signatures. However, part of an ongoing research program at the University of Kent has established an approach to the verification process based on selecting a unique set of features for each individual signer to minimise error rate performance. The motivation for automatically selecting features is not only fuelled by minimising error rates, and this paper sets out to describe and analyse the parallel implementation of this new approach to ASV and describes improvements achieved in throughput performance