A Signature Verification System with Ensemble Classifier

Abstract

Handwritten signature is considered as one of the established authentication process to study the behavioral nature of a person. This paper focuses on verification of offline handwritten signatures (for English scripts) as either genuine or forgery. Here the considered samples are genuine, skilled and simple forgeries. The verification is carried out by ensembling the three base classifiers Naive Bayes (NB), K-Nearest Neighbor (KNN) and Kmeans classifiers. The accuracies for skilled and simple forgeries are obtained as 86 % and 92 % respectively.