Name
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. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/IPTA.2016.7820992 | 2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA) |
Keywords | Field | DocType |
Image phylogeny,JPEG compression,Social networks,Image phylogeny tree,near-duplicates | Computer vision,Pattern recognition,Computer science,Ancestor,Transform coding,Image coding,Binary decision diagram,JPEG,Artificial intelligence,Jpeg compression | Conference |
ISSN | ISBN | Citations |
2154-512X | 978-1-4673-8911-2 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Noe Le Philippe | 1 | 1 | 0.72 |
| William Puech | 2 | 535 | 76.74 |
| Christophe Fiorio | 3 | 197 | 23.27 |