2013/11/27 by Davide Cozzolino, Cozzolino, Davide, Diego Gragnaniello +3
Computer Science · Engineering · #Advanced Steganography and Watermarking Techniques #Computer Vision and Pattern Recognition (cs.CV) #Digital Media Forensic Detection #FOS: Computer and information sciences #Image Processing Techniques and Applications
paper · pdf · doi:10.48550/arxiv.1311.6932
openalex publication_date 2013/11/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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. According to preliminary experiments on the training set, the proposed framework provides often a very good localization accuracy and sometimes valuable clues for visual scrutiny.