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Non-blind method of detection and localization of structural tampering using robust Hash-like function and similarity metric for digital images

机译:使用鲁棒的类哈希函数和数字图像相似性度量的结构篡改检测和定位的非盲方法

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摘要

Content preserving manipulations (CPM) in a digital image has been discussed subjectively in the literature so far. A number of ways of obtaining robust hash functions have been reported which claim to be robust against any content preserving manipulations and sensitive to structural tamperings. However, in many cases, one can make out these structural tampering just by viewing and comparing the two images, the original and the tampered image. We report an algorithm using robust Hash-like function and similarity metric by which even a very small but malicious tampering affecting only a few pixels of the digial image could be localized accurately. Results are shown in which locations of single or even multiple structural tamperings are successfully identified.
机译:到目前为止,文献中已经对主观讨论了数字图像中的内容保存操作(CPM)。已经报道了获得鲁棒散列函数的多种方法,这些方法声称对任何内容保存操作都是鲁棒的并且对结构篡改敏感。但是,在许多情况下,仅通过查看和比较原始图像和被篡改的两个图像就可以识别出这些结构性篡改。我们报告了一种使用健壮的类似于Hash的函数和相似性度量的算法,通过该算法,即使仅影响数字图像的几个像素的很小但恶意的篡改也可以准确定位。结果显示了成功识别出单个或多个结构篡改的位置。

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