📅 28 February 2022
DOI: 10.35671/telematika.v15i1.1322
Gaussian Pyramid Decomposition in Copy-Move Image Forgery Detection with SIFT and Zernike Moment Algorithms
Telematika
Universitas Amikom Purwokerto
📄 Abstract
One of the easiest manipulation methods is a copy-move forgery, which adds or hides objects in the images with copies of certain parts at the same pictures. The combination of SIFT and Zernike Moments is one of many methods that helping to detect textured and smooth regions. However, this combination is slowest than SIFT individually. On the other hand, Gaussian Pyramid Decomposition helps to reduce computation time. Because of this finding, we examine the impact of Gaussian Pyramid Decomposition in copy-move detection with SIFT and Zernike Moments combinations. We conducted detection test in plain copy-move, copy-move with rotation transformation, copy-move with JPEG compression, multiple copy-move, copy-move with reflection attack, and copy-move with image inpainting. We also examine the detections result with different values of gaussian pyramid limit and different area separation ratios. In detection with plain copy-move images, it generates low level of accuracy, precision and recall of 58.46%, 18.21% and 69.39%, respectively. The results are getting worse in for copy-move detection with reflection attack and copy-move with image inpainting. This weakness happened because this method has not been able to detect the position of the part of the image that is considered symmetrical and check whether the forged part uses samples from other parts of the image.
🔖 Keywords
#Copy-Move Forgery;Scale Invariant Feature Transform;Gaussian Pyramid Decomposition;Zernike Moments
ℹ️ Informasi Publikasi
Tanggal Publikasi
28 February 2022
Volume / Nomor / Tahun
Volume 15, Nomor 1, Tahun 2022
📝 HOW TO CITE
Rahma, Firstyani Imannisa; Universitas Amikom Yogyakarta; Utami, Ema; Universitas Amikom Yogyakarta; Al-Fatta, Hanif; Universitas Amikom Yogyakarta; , "Gaussian Pyramid Decomposition in Copy-Move Image Forgery Detection with SIFT and Zernike Moment Algorithms," Telematika, vol. 15, no. 1, Feb. 2022.
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