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Context-aware forgery localization in social-media images: a feature-based approach evaluation

Cédric Maigrot 1 Ewa Kijak 1 Vincent Claveau 1 
1 LinkMedia - Creating and exploiting explicit links between multimedia fragments
Inria Rennes – Bretagne Atlantique , IRISA-D6 - MEDIA ET INTERACTIONS
Abstract : In this paper, we study context-aware methods to localize tamperings in images from social media. The problem is defined as a comparison between image pairs: an near-duplicate image retrieved from the network and a tampered version. We propose a method based on local features matching, followed by a kernel density estimation, that we compare to recent similar approaches. The proposed approaches are evaluated on two dedicated datasets containing a variety of representative tamperings in images from social media, with difficult examples. Context-aware methods are proven to be better than blind image forensics approach. However, the evaluation allows to analyze the strengths and weaknesses of the contextual-based methods on realistic datasets.
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Submitted on : Wednesday, July 18, 2018 - 6:09:14 PM
Last modification on : Friday, August 5, 2022 - 2:54:52 PM
Long-term archiving on: : Friday, October 19, 2018 - 9:00:32 PM


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Cédric Maigrot, Ewa Kijak, Vincent Claveau. Context-aware forgery localization in social-media images: a feature-based approach evaluation. ICIP 2018 - IEEE International Conference of Image Processing, Oct 2018, Athènes, Greece. pp.545-549, ⟨10.1109/ICIP.2018.8451726⟩. ⟨hal-01843611⟩



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