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Automatic Detection of Internal Copy-Move Forgeries in Images

机译：自动检测图像中的内部复制移动伪造

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This article presents an implementation and discussion of the recently proposed 'Efficient Dense-Field Copy-Move Forgery Detection' by Cozzolino et al. This method is a forgery detection based on a dense field of descriptors chosen to be invariant by rotation. Zernike moments were suggested in the original article. An efficient matching of the descriptors is then performed using PatchMatch, which is extremely efficient to find duplicate regions. Regions matched by PatchMatch are processed to find the final detections. This allows a precise and accurate detection of copy-move forgeries inside a single suspicious image. We also extend successfully the method to the use of dense SIFT descriptors and show that they are better at detecting forgeries using Poisson editing.
机译：本文介绍了Cozzolino等人最近提出的“高效密集场复制移动伪造检测”的实现和讨论。该方法是基于被选为旋转不变的描述符的密集字段的伪造检测。原始文章中建议使用Zernike矩。然后使用PatchMatch对描述符进行有效匹配，这对于查找重复区域非常有效。处理由PatchMatch匹配的区域以找到最终的检测结果。这样可以准确而准确地检测单个可疑图像内的复制移动伪造品。我们还成功地将该方法扩展为使用密集的SIFT描述符，并表明它们更擅长使用泊松编辑来检测伪造品。

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