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- W2110150246 abstract "Image manipulation has become commonplace with growing easy access to powerful computing abilities. One of the most common types of image forgeries is the copy-paste forgery, wherein a region from an image is replaced with another region from the same image (with possible transformations). A brute-force approach to finding identical regions suffers from many problems, including inability to detect transformed regions. In this paper, we propose a novel technique based on transform-invariant features. These are obtained by adapting the MPEG-7 image signature tools to specifically deal with copy-paste forgeries. Results are provided to justify the application of these tools in copy-paste forgery detection." @default.
- W2110150246 created "2016-06-24" @default.
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- W2110150246 date "2011-06-01" @default.
- W2110150246 modified "2023-09-22" @default.
- W2110150246 title "Detecting copy-paste forgeries using transform-invariant features" @default.
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- W2110150246 doi "https://doi.org/10.1109/isce.2011.5973783" @default.
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