@ARTICLE{Isnanto_R._Rizal_Determination_2020,
 author={Isnanto, R. Rizal and Zahra, Ajub Ajulian and Santoso, Imam and Lubis, Muhammad Salman},
 volume={vol. 66},
 number={No 3},
 journal={International Journal of Electronics and Telecommunications},
 pages={561-569},
 howpublished={online},
 year={2020},
 publisher={Polish Academy of Sciences Committee of Electronics and Telecommunications},
 abstract={The copy-move forgery detection (CMFD) begins with the preprocessing until the image is ready to process. Then, the image features are extracted using a feature-transform-based extraction called the scale-invariant feature transform (SIFT). The last step is features matching using Generalized 2 Nearest- Neighbor (G2NN) method with threshold values variation. The problem is what is the optimal threshold value and number of keypoints so that copy-move detection has the highest accuracy. The optimal threshold value and number of keypoints had determined so that the detection has the highest accuracy. The research was carried out on images without noise and with Gaussian noise.},
 type={Article},
 title={Determination of the Optimal Threshold Value and Number of Keypoints in Scale Invariant Feature Transform-based Copy-Move Forgery Detection},
 URL={http://ochroma.man.poznan.pl/Content/117108/PDF/77_2468_Isnanto_skl_new.pdf},
 doi={10.24425/ijet.2020.134013},
 keywords={forgery, Gaussian noise, feature extraction, pattern matching, Euclidean distance},
}