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Document Forgery Detection with SVM Classifier and Image Quality Measures

机译:使用SVM分类器的文档伪造检测和图像质量衡量

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摘要

This paper presents a detection scheme for a fraudulent document made by printers. The fraud document is indistinguishable by the naked eye from a genuine document because of the technological advances in printing methods. Even though we cannot find any visual evidence of forgery, the fraud document includes inherent device features. We propose a method to uncover these features. 17 image quality measures are applied to discriminate between genuine and fake documents. The results of each measure are used as training and testing parameters of SVM classifier to determine fake documents. Preliminary experimental results are presented based on the fraud gift voucher made by several color printers.
机译:本文提出了一种针对打印机制造的欺诈性文件的检测方案。由于打印方法的技术进步,欺诈文件与真实文件无法用肉眼分辨。即使我们找不到伪造的任何视觉证据,欺诈文件也包含固有的设备功能。我们提出了一种发现这些特征的方法。我们采用了17种图像质量措施来区分真伪文件。每种度量的结果都用作SVM分类器的训练和测试参数,以确定伪造文档。根据几台彩色打印机制作的欺诈性礼品券,给出了初步的实验结果。

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