Machine Authentication of Security Documents

Utpal Garain, Biswajit Halder
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引用次数: 7

Abstract

This paper presents a pioneering effort towards machine authentication of security documents like bank cheques, legal deeds, certificates, etc. that fall under the same class as far as security is concerned. The proposed method first computationally extracts the security features from the document images and then the notion of ‘genuine’ vs. ‘duplicate’ is defined in the feature space. Bank cheques are taken as a reference for conducting the present experiment. Support Vector Machines (SVMs) and Neural Networks (NN) are involved to verify authenticity of these cheques. Results on a test dataset of 200 samples show that the proposed approach achieves about 98% accuracy for discriminating duplicate cheques from genuine ones. This strongly attests the viability of involving machine in authenticating security documents.
安全文件的机器认证
本文介绍了对安全文件(如银行支票、法律契约、证书等)进行机器认证的开创性努力,这些文件就安全性而言属于同一类别。该方法首先从文档图像中计算提取安全特征,然后在特征空间中定义“真品”与“复制品”的概念。本实验以银行支票为参考。使用支持向量机(svm)和神经网络(NN)来验证这些支票的真实性。在200个样本的测试数据集上的结果表明,所提出的方法在区分假支票和真支票方面达到了98%的准确率。这有力地证明了让机器参与安全文档身份验证的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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