Copy and Move Forgery Detection Using SIFT and Local Color Dissimilarity Maps - Université de technologie de Troyes Access content directly
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Copy and Move Forgery Detection Using SIFT and Local Color Dissimilarity Maps

Abstract

It is becoming harder and harder to believe in digital images authenticity. This is due to the increasing ease of producing forged images using retouching software more powerful than ever. On software like Photoshop, one can easily remove an element from an image with just a few clicks. Copy-move is one of the elemental forgery methods that consists in the duplication of one portion of the image. Such manipulation is very usual and dangerous in official document falsification (ID, breeder docs, bills. . . ). In this paper, we propose a novel method for the detection of Copy and Move forgery while maintaining a low false positive rate.
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Dates and versions

hal-02461503 , version 1 (30-01-2020)

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Gael Mahfoudi, Frédéric Morain-Nicolier, Florent Retraint, Marc Pic. Copy and Move Forgery Detection Using SIFT and Local Color Dissimilarity Maps. Global Conference on Signal and Information Processing (GlobalSIP), 2019, Ottawa, Canada. ⟨10.1109/GlobalSIP45357.2019.8969355⟩. ⟨hal-02461503⟩
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