A novel framework for image forgery localization [article]

Davide Cozzolino and Diego Gragnaniello and Luisa Verdoliva
2013 arXiv   pre-print
Image forgery localization is a very active and open research field for the difficulty to handle the large variety of manipulations a malicious user can perform by means of more and more sophisticated image editing tools. Here, we propose a localization framework based on the fusion of three very different tools, based, respectively, on sensor noise, patch-matching, and machine learning. The binary masks provided by these tools are finally fused based on some suitable reliability indexes.
more » ... ing to preliminary experiments on the training set, the proposed framework provides often a very good localization accuracy and sometimes valuable clues for visual scrutiny.
arXiv:1311.6932v1 fatcat:qvi7dmwd3jhpxattlz6hbciow4