Name
Abstract | ||
|---|---|---|
In this paper, a forensic tool able to discriminate between original and forged regions in an image captured by a digital camera is presented. We make the assumption that the image is acquired using a Color Filter Array, and that tampering removes the artifacts due to the demosaicking algorithm. The proposed method is based on a new feature measuring the presence of demosaicking artifacts at a local level, and on a new statistical model allowing to derive the tampering probability of each 2 $\\,\\times\\,$2 image block without requiring to know a priori the position of the forged region. Experimental results on different cameras equipped with different demosaicking algorithms demonstrate both the validity of the theoretical model and the effectiveness of our scheme. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/TIFS.2012.2202227 | IEEE Transactions on Information Forensics and Security |
Keywords | Field | DocType |
statistical analysis,image segmentation,computer forensics | Computer vision,Computer forensics,Pattern recognition,Computer science,A priori and a posteriori,Demosaicing,Image segmentation,Digital camera,Statistical model,Artificial intelligence,Color filter array,Color image | Journal |
Volume | Issue | ISSN |
7 | 5 | 1556-6013 |
Citations | PageRank | References |
77 | 2.02 | 20 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pasquale Ferrara | 1 | 105 | 5.15 |
| Tiziano Bianchi | 2 | 1003 | 62.55 |
| Alessia De Rosa | 3 | 312 | 20.66 |
| Alessandro Piva | 4 | 2231 | 157.21 |