文章基本信息

标题：OFF-LINE Signature Verification Using Neural Network Approach
本地全文：下载
作者：Sakshi Chhabra
期刊名称：International Journal of Computer Trends and Technology
电子版ISSN：2231-2803
出版年度：2013
卷号：4
期号：5-5
出版社：Seventh Sense Research Group
摘要：Signature verification is the process carried out to determine whether a given signature is genuine or forged. Handwriting comes in many different forms and there is great deal of variability even signature of people that use same language. Some signature may be quite complex while others are simple and appear as if they may be forged easily. In this paper we present an effective method to perform offline signature verification and identification. First of all the signatures are converted into .PBM format so that less information to process. Then different feature extraction methods are used to obtain optimized high performance signature verification for improving the identification rate. Two different files are used one to train the network and another to test the network. Finally neural network Radial basis function network (RBF) is used as classifier. RBF provides better verification accuracy than any other classifier.
关键词：OFF-LINE Signature Verification Using Neural Network Approach