SIFT-Symmetry: A robust detection method for copy-move forgery with reflection attack
| Autor: | Rosli Salleh, Mohd Yamani Idna Idris, Ainuddin Wahid Abdul Wahab, Nor Bakiah Abd Warif, Fazidah Othman |
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| Rok vydání: | 2017 |
| Předmět: |
Matching (graph theory)
0211 other engineering and technologies Scale-invariant feature transform 02 engineering and technology symbols.namesake 0202 electrical engineering electronic engineering information engineering Media Technology Computer vision Electrical and Electronic Engineering Mathematics 021110 strategic defence & security studies business.industry computer.file_format JPEG Transformation (function) Reflection (mathematics) Gaussian noise Signal Processing symbols 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Artificial intelligence Reflection attack business computer Rotation (mathematics) |
| Zdroj: | Journal of Visual Communication and Image Representation. 46:219-232 |
| ISSN: | 1047-3203 |
| DOI: | 10.1016/j.jvcir.2017.04.004 |
| Popis: | Copy-move forgery (CMF) is a popular image manipulation technique that is simple and effective in creating forged illustrations. The bulk of CMF detection methods concentrate on common geometrical transformation attacks (e.g., rotation and scale) and post-processing attacks (e.g., Joint Photographic Experts Group (JPEG) compression and Gaussian noise addition). However, geometrical transformation that involves reflection attacks has not yet been highlighted in the literature. As the threats of reflection attack are inevitable, there is an urgent need to study CMF detection methods that are robust against this type of attack. In this study, we investigated common geometrical transformation attacks and reflection-based attacks. Also, we suggested a robust CMF detection method, called SIFT-Symmetry, that innovatively combines the Scale Invariant Feature Transform (SIFT)-based CMF detection method with symmetry-based matching. We evaluated the SIFT-Symmetry with three established methods that are based on SIFT, multi-scale analysis, and patch matching using two new datasets that cover simple transformation and reflection-based attacks. The results show that the F-score of the SIFT-Symmetry method surpassed the average 80% value for all geometrical transformation cases, including simple transformation and reflection-based attacks, except for the reflection with rotation case which had an average F-score of 65.3%. The results therefore show that the SIFT-Symmetry method gives better performance compared to the other existing methods. |
| Databáze: | OpenAIRE |
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