Open AccessA Signature Verification System with Ensemble Classifier
Author(s) -
Alpana Deka
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.c5445.118419
Subject(s) - naive bayes classifier , computer science , artificial intelligence , pattern recognition (psychology) , classifier (uml) , authentication (law) , scripting language , signature (topology) , k nearest neighbors algorithm , simple (philosophy) , support vector machine , mathematics , computer security , philosophy , geometry , epistemology , operating system
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.