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首页> 外文期刊>International Journal of Innovative Research in Science, Engineering and Technology >Exposing Digital Forgery Detection by Illumination Using SVM classifier
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Exposing Digital Forgery Detection by Illumination Using SVM classifier

机译:使用SVM分类器通过照明公开数字伪造检测

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Photographs often act as evidence for criminals cases in courts. It also plays a vital role in media such as newspapers, television, etc. But however, image forgery becomes easier nowadays as image editing software becomes available. Here we analyze the often utilized manipulation technique called splicing or image composition. Physics-based and statistical-based illuminate estimation technique is incorporated so that texture- and edge-based features are extracted to identify image forgery. Machine-learning approach is also employed; hence requires minimal human interaction.
机译:照片通常是法庭上犯罪分子案件的证据。它在报纸,电视等媒体中也起着至关重要的作用。但是,如今,随着图像编辑软件的推出,图像伪造变得更加容易。在这里,我们分析了经常使用的称为拼接或图像合成的操纵技术。结合了基于物理和基于统计的照明估计技术,以便提取基于纹理和边缘的特征以识别图像伪造。还采用了机器学习方法。因此需要最少的人际互动。

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