A sparse representation-based approach for copy-move image forgery detection in smooth regions

Jalila Abdessamad; Asma ElAdel; Mourad Zaied

doi:10.1117/12.2268766

17 March 2017 A sparse representation-based approach for copy-move image forgery detection in smooth regions

Jalila Abdessamad, Asma ElAdel, Mourad Zaied

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.

Citation Download Citation

Jalila Abdessamad, Asma ElAdel, and 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); https://doi.org/10.1117/12.2268766

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