Context-Aware Forgery Localization in Social-Media Images: A Feature-Based Approach Evaluation

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...

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Bibliographic Details
Main Authors: Maigrot, Cedric, Kijak, Ewa, Claveau, Vincent
Format: Conference Proceeding
Language:English
Subjects:
Context-aware digital forensics
Estimation
Forgery
Forgery localization
Image forensics
Image tampering
Kernel
Measurement
Social network services
Splicing
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Description
Summary: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.
ISSN:2381-8549
DOI:10.1109/ICIP.2018.8451726