Fuzzy methaheuristic model for copy-move forgery detection on images
Many methods have been proposed to detect the originality of an image. One of the most commonly used method, the Copy - move forgery detection (CMFD), is considered here. The contribution of this paper is the application of the new fuzzy distances in clustering using metaheuristics. The family of th...
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Veröffentlicht in: | Multimedia tools and applications 2024-04, Vol.83 (13), p.38737-38752 |
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Sprache: | eng |
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Zusammenfassung: | Many methods have been proposed to detect the originality of an image. One of the most commonly used method, the Copy - move forgery detection (CMFD), is considered here. The contribution of this paper is the application of the new fuzzy distances in clustering using metaheuristics. The family of the used fuzzy distances satisfies the axioms of the fuzzy metric. CMFD method, which includes Variable Neighborhood Search (VNS) and Bee Colony Optimization (BCO) metaheuristics, has been tested and compared with similar methods. The proposed method with the proposed new metric used in this research gave better results than the existing methods. The proposed fuzzy metrics in this paper as well as the problem of
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median clustering applied to the problem and compared with existing research in this field give better results. |
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ISSN: | 1573-7721 1380-7501 1573-7721 |
DOI: | 10.1007/s11042-023-17053-7 |