Image Forgery Detection via Forensic Similarity Graphs

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. Source Code The source code and documentation for this algorithm are available from the web page of this article 1. Usage instructions are included in the README.txt file of the archive. The original implementation of the method is available here 2. This is an MLBriefs article, the source code has not been reviewed!