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On Automatic Authenticity Verification of Printed Security Documents

机译:关于印刷安全文件的自动真实性验证

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This paper presents a pioneering effort to involve machine in checking document authenticity. A particular class of security documents has been considered for the present experiment. Bank cheques, several kinds of tickets like lottery tickets, air tickets, etc., legal deeds, certificates, mark sheets, postal stamps, etc. all these documents fall under the same class as far as security is concerned. Criminals’ efforts for generating fraudulent version of such documents are on the rise. This study attempts to develop a general framework for automatic authenticity verification of such security documents. The proposed method first computationally extracts the security features from the document images and then the notion of authenticity vs. duplicity is defined in the feature space. Bank cheques are taken as a reference for conducting experiment. Support Vector Machines (SVMs) are used to verify authenticity of these cheques. Non-linear kernel functions are used to conduct this experiment. Results show that a polynomial kernel based SVM gives about 99.5% accuracy discriminating duplicate cheques from genuine ones. This strongly attests the viability of the proposed approach for machine authentication of printed security documents.
机译:本文提出了一种开创性的努力,检查文件的真实性涉及到机器。一类特别的安全文件已被认为是本实验。银行支票,数种票样彩票,机票等,法律行为,证书,标张,邮票等。所有这些文件的同一类下尽可能安全而言下降。罪犯用来产生这些文件的欺诈版本的努力都在上升。本研究试图开发这样的安全文件的自动真实性验证的总体框架。所提出的方法计算第一提取从文档图像,然后对真实性口是心非的概念的安全功能在特征空间进行定义。银行支票为例进行实验进行参考。支持向量机(SVM)被用来验证这些检查真实性。非线性内核函数被用来进行这项实验。结果表明,基于SVM多项式内核提供了约99.5%的准确度从真正的人区分重复检查。这有力地证明了该方法用于印刷的安全文件的机器验证的可行性。

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