Phylogeny of JPEG images by ancestor estimation using missing markers on image pairs

Abstract : Nowadays it is extremely easy to tamper with images and share them thanks to social media. Identifying the transformation history is imperative to be able to trust these images. We address this problem by using image phylogeny trees, where the root is the image that has been less tampered with and as every generation is obtained from the transformation of its parents, the leaves are the most transformed images. Our method for image phylogeny trees reconstruction is based on a binary decision between two images using JPEG compression artifacts. Experimental results show that when there is no missing image data, the reconstruction is very accurate.