Survey on image copy-move forgery detection
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-16455-x.pdf
Reference174 articles.
1. Abd Warif N, Wahid A, Idris M, Ramli R, Salleh R, Band S, Choo KKR (2016) Copy-move forgery detection: Survey, challenges and future directions. J Netw Comput Appl 75. https://doi.org/10.1016/j.jnca.2016.09.008
2. Abd Warif N, Wahid A, Idris M, Salleh R, Othman F (2017) Sift-symmetry: A robust detection method for copy-move forgery with reflection attack. J Vis Commun Image Represent 46. https://doi.org/10.1016/j.jvcir.2017.04.004
3. Agarwal V, Mane V (2016) Reflective sift for improving the detection of copy-move image forgery. In: 2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN), pp 84–88. https://doi.org/10.1109/ICRCICN.2016.7813636
4. Alhussein M (2016) Image tampering detection based on local texture descriptor and extreme learning machine. In: 2016 UKSim-AMSS 18th International Conference on Computer Modelling and Simulation (UKSim), pp 196–199. https://doi.org/10.1109/UKSim.2016.39
5. Alkawaz MH, Sulong G, Saba T, Rehman A (2016) Detection of copy-move image forgery based on discrete cosine transform. Neural Comput Applic 30:183–192
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