Name
Abstract | ||
|---|---|---|
Though the current state of the art of image forensics permits to acquire very interesting information about image history, all the instruments developed so far focus on the analysis of single images. It is the aim of this paper to propose a new approach that moves the forensics analysis further, by considering groups of images instead of single images. The idea is to discover dependencies among a group of images representing similar or equal contents in order to construct a graph describing image relationships. Given the pronounced effect that images posted on the Web have on opinions and bias in the networked age we live in, such an analysis could be extremely useful for understanding the role of pictures in the opinion forming process. We propose a theoretical framework for the analysis of image dependencies and describe a simple system putting the theoretical principles in practice. The performance of the proposed system are evaluated on a few practical examples involving both images created and processed in a controlled way, and images downloaded from the web. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1117/12.840235 | Proceedings of SPIE |
Keywords | Field | DocType |
image dependencies,image forensics,image registration,dependency test,dependency graph | Data mining,Graph,Computer vision,Computer science,Upload,Image retrieval,Image processing,Image forensics,Artificial intelligence,Dependency graph,Image registration | Conference |
Volume | ISSN | Citations |
7541 | 0277-786X | 19 |
PageRank | References | Authors |
0.91 | 1 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alessia De Rosa | 1 | 312 | 20.66 |
| F. Uccheddu | 2 | 99 | 9.69 |
| A. Costanzo | 3 | 19 | 0.91 |
| Alessandro Piva | 4 | 2231 | 157.21 |
| M. Barni | 5 | 3091 | 246.21 |