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