Fuzzy methaheuristic model for copy-move forgery detection on images
Abstract
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 $$p-$$median clustering applied to the problem and compared with existing research in this field give better results.
Keywords:
Clustering / Forensic images / Methaheuristic / MetricsSource:
Multimedia Tools and Applications, 2023Funding / projects:
- Characterisation of Kinetics and Influence of Emerging Pollutants of Waste Flow in Graphic Industry (RS-MESTD-Technological Development (TD or TR)-34014)
- Mathematical modeling of nonlinearity, uncertainty and decision (RS-MESTD-Basic Research (BR or ON)-174009)
- Ministry of Science, Technological Development and Innovation of the Republic of Serbia, institutional funding - 200156 (University of Novi Sad, Faculty of Technical Science) (RS-MESTD-inst-2020-200156)
- Development of new information and communication technologies, based on advanced mathematical methods, with applications in medicine, telecommunications, power systems, protection of national heritage and education (RS-MESTD-Integrated and Interdisciplinary Research (IIR or III)-44006)
- Ministry of Science, Technological Development and Innovation of the Republic of Serbia, institutional funding - 200116 (University of Belgrade, Faculty of Agriculture) (RS-MESTD-inst-2020-200116)
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Institution/Community
Poljoprivredni fakultetTY - JOUR AU - Milosavljević, Nataša S. AU - Ralević, Nebojša M. PY - 2023 UR - https://doi.org/10.1007/s11042-023-17053-7 UR - http://aspace.agrif.bg.ac.rs/handle/123456789/6478 AB - 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 $$p-$$median clustering applied to the problem and compared with existing research in this field give better results. T2 - Multimedia Tools and Applications T2 - Multimedia Tools and ApplicationsMultimed Tools Appl T1 - Fuzzy methaheuristic model for copy-move forgery detection on images DO - 10.1007/s11042-023-17053-7 ER -
@article{ author = "Milosavljević, Nataša S. and Ralević, Nebojša M.", year = "2023", abstract = "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 $$p-$$median clustering applied to the problem and compared with existing research in this field give better results.", journal = "Multimedia Tools and Applications, Multimedia Tools and ApplicationsMultimed Tools Appl", title = "Fuzzy methaheuristic model for copy-move forgery detection on images", doi = "10.1007/s11042-023-17053-7" }
Milosavljević, N. S.,& Ralević, N. M.. (2023). Fuzzy methaheuristic model for copy-move forgery detection on images. in Multimedia Tools and Applications. https://doi.org/10.1007/s11042-023-17053-7
Milosavljević NS, Ralević NM. Fuzzy methaheuristic model for copy-move forgery detection on images. in Multimedia Tools and Applications. 2023;. doi:10.1007/s11042-023-17053-7 .
Milosavljević, Nataša S., Ralević, Nebojša M., "Fuzzy methaheuristic model for copy-move forgery detection on images" in Multimedia Tools and Applications (2023), https://doi.org/10.1007/s11042-023-17053-7 . .