Phylogenetic analysis of near-duplicate images using processing age metrics
Recent researches on image forensics have led to the design of algorithms to study the phylogenetic relationship between near-duplicate (ND) images. The proposed solutions aim at reconstructing the image phylogeny tree (IPT), and they have immediate applications in security, law and copyright enforcement, and news tracking services. Anyway, the effectiveness of such strategies strictly depends on the accuracy in characterizing image similarities. In this paper, we show that it is possible to take into account additional information to better reconstruct the IPT. More specifically, we propose a set of features that blindly model the processing age of an image, i.e., how much an image has been edited in its lifetime. By exploiting these features, it is possible to improve the performance of IPT reconstruction by increasing the accuracy and reducing the computational complexity.