DETECTION OF INTENTIONALLY CAUSED CHANGES IN AN IMAGE USING Fiji, ImageJ and SPSS SOFTWARE
DOI:
https://doi.org/10.24867/26JV01ScekicKeywords:
Clustering, K-means, K-nearest neighbors, Fiji, ImegeJ, SPSSAbstract
The aim of this research is to detect deliberately caused changes caused by copying/pasting the contents of the image by combining several methods, using the K-means and K-nearest neighbors algorithms. The problem of image forensics is currently an actual problem that is being dealt with by eminent scientists from the scientific field of applied mathematics, especially electrical engineers. Finding an adequate model that would get the information as accurately and quickly as possible, and we are talking about the parts of the image that have been changed, is a real challenge. This paper presents the proposal of one of the algorithms, as well as their results. Models were created using SPSS and FIji ImageJ software.
References
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[2] Emre G, Guzin u, Mustafa U (2019), Detection of free-form copy-move forgery on digital images. Security and Communication Networks.
[3] Christlein V, Riess C, Jordan J, Riess C, Angelopoulou E (2012) An evaluation of popular copy-move forgery detection approaches. arXiv:1208.3665
[4] Warif NBA, Wahab AWA, Idris MYI, Ramli R, Salleh R, Shamshirband S, Choo KKR (2016) Copymove forgery detection: Survey, challenges and future directions. J Network and Computer Applications 75:259–278
[5] Soni B, Das PK, Thounaojam DM (2018) Cmfd: a detailed review of block based and key feature based techniques in image copy-move forgery detection. IET Image Processing 12(2):167–178. https://doi.org/10.1049/iet-ipr.2017.0441
[2] Emre G, Guzin u, Mustafa U (2019), Detection of free-form copy-move forgery on digital images. Security and Communication Networks.
[3] Christlein V, Riess C, Jordan J, Riess C, Angelopoulou E (2012) An evaluation of popular copy-move forgery detection approaches. arXiv:1208.3665
[4] Warif NBA, Wahab AWA, Idris MYI, Ramli R, Salleh R, Shamshirband S, Choo KKR (2016) Copymove forgery detection: Survey, challenges and future directions. J Network and Computer Applications 75:259–278
[5] Soni B, Das PK, Thounaojam DM (2018) Cmfd: a detailed review of block based and key feature based techniques in image copy-move forgery detection. IET Image Processing 12(2):167–178. https://doi.org/10.1049/iet-ipr.2017.0441
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Published
2024-04-04
Issue
Section
Mathematics in Engineering
