17 March 2017 A sparse representation-based approach for copy-move image forgery detection in smooth regions
Author Affiliations +
Proceedings Volume 10341, Ninth International Conference on Machine Vision (ICMV 2016); 1034129 (2017) https://doi.org/10.1117/12.2268766
Event: Ninth International Conference on Machine Vision, 2016, Nice, France
Abstract
Copy-move image forgery is the act of cloning a restricted region in the image and pasting it once or multiple times within that same image. This procedure intends to cover a certain feature, probably a person or an object, in the processed image or emphasize it through duplication. Consequences of this malicious operation can be unexpectedly harmful. Hence, the present paper proposes a new approach that automatically detects Copy-move Forgery (CMF). In particular, this work broaches a widely common open issue in CMF research literature that is detecting CMF within smooth areas. Indeed, the proposed approach represents the image blocks as a sparse linear combination of pre-learned bases (a mixture of texture and color-wise small patches) which allows a robust description of smooth patches. The reported experimental results demonstrate the effectiveness of the proposed approach in identifying the forged regions in CM attacks.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jalila Abdessamad, Asma ElAdel, Mourad Zaied, "A sparse representation-based approach for copy-move image forgery detection in smooth regions", Proc. SPIE 10341, Ninth International Conference on Machine Vision (ICMV 2016), 1034129 (17 March 2017); doi: 10.1117/12.2268766; https://doi.org/10.1117/12.2268766
PROCEEDINGS
5 PAGES


SHARE
Back to Top