Classification of handwritten signatures based on name legibility
Javier Galbally, Julián Fiérrez, Javier Ortega-García · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2007
An automatic classification scheme of on-line handwritten signatures is presented. A Multilayer Perceptron (MLP) with a hidden layer is used as classifier, and two different signature classes are considered, namely: legible and non-legible name. Signatures are represented considering different feature subsets obtained from global information. Mahalanobis distance is used to rank the parameters and feature selection is then applied based on the top ranked features. Experimental results are given on the MCYT signature database comprising 330 signers. It is shown experimentally that automatic on-line signature classification based on the name legibility is feasible.