[IPOL discuss] [IPOL announce] new article: Image Forgery Detection via Forensic Similarity Graphs

[announcements about the IPOL journal]

A new article is available in IPOL: http://www.ipol.im/pub/art/2022/432/

Marina Gardella, and Pablo Musé,
Image Forgery Detection via Forensic Similarity Graphs,
Image Processing On Line, 12 (2022), pp. 490–500.
https://doi.org/10.5201/ipol.2022.432

Abstract
In the article 'Exposing Fake Images with Forensic Similarity Graphs', 
O. Mayer and M. C. Stamm introduce a novel image forgery detection 
method. The proposed method is built on a graph-based representation of 
images, where image patches are represented as the vertices of the 
graph, and the edge weights are assigned in order to reflect the 
forensic similarity between the connected patches. In this 
representation, forged regions form highly connected subgraphs. 
Therefore, forgery detection and localization can be cast as a cluster 
analysis problem on the similarity graph. The authors present two graph 
clustering methods to detect and localize image forgeries. In this 
paper, we present briefly the method and offer an online executable 
version allowing everyone to test it on their own suspicious images.




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