Share Email Print

Proceedings Paper

A sparse representation-based approach for copy-move image forgery detection in smooth regions
Author(s): Jalila Abdessamad; Asma ElAdel; Mourad Zaied
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper 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.

Paper Details

Date Published: 17 March 2017
PDF: 5 pages
Proc. SPIE 10341, Ninth International Conference on Machine Vision (ICMV 2016), 1034129 (17 March 2017); doi: 10.1117/12.2268766
Show Author Affiliations
Jalila Abdessamad, Ecole Nationale d'Ingénieurs de Sfax (Tunisia)
Asma ElAdel, Ecole Nationale d'Ingénieurs de Sfax (Tunisia)
Mourad Zaied, Ecole Nationale d'Ingénieurs de Sfax (Tunisia)

Published in SPIE Proceedings Vol. 10341:
Ninth International Conference on Machine Vision (ICMV 2016)
Antanas Verikas; Petia Radeva; Dmitry P. Nikolaev; Wei Zhang; Jianhong Zhou, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?