Image forensics is an important area of research used to indicate if a particular image is original or subjected to any kind of tampering. Images are essential part of judgment in tribunals. For forensic analysis, image forgery-detection techniques used to identify the forged images. In this paper, an effective algorithm to indicate Copy Move Forgery in digital image presented. The Scale Invariant Feature Transform (SIFT) and Fuzzy C-means (FCM) for clustering are utilized in the proposed algorithm. A number of numerical experiments performed using the MICC-220 dataset. The authors created an additional dataset, which consisted of 353 color images. The proposed algorithm tested by using both datasets where the average detection time on the MICC-220 data set is reduced by 14.67% over the existing traditional SIFT-based algorithm. For the created dataset, the average detection time reduced by 15.91% over the existing traditional SIFT-based algorithm.
Alberry, Hesham A.; Hegazy, Abdelfatah A.; and Salama, Gouda I.
"A fast SIFT based method for copy move forgery detection,"
Future Computing and Informatics Journal: Vol. 3
, Article 3.
Available at: https://digitalcommons.aaru.edu.jo/fcij/vol3/iss2/3