Determination of the Optimal Threshold Value and Number of Keypoints in Scale Invariant Feature Transform-based Copy-Move Forgery Detection

• Autorzy: Isnanto R. Rizal , Zahra Ajub Ajulian , Santoso Imam , Lubis Muhammad Salman

Identyfikatory

DOI

10.24425/ijet.2020.134013

• Języki publikacji: EN

Abstrakty

EN

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 n has the highest accuracy. The research was carried out on images without noise and with Gaussian noise.

Słowa kluczowe

EN

forgery; Gaussian noise; feature extraction; pattern matching; Euclidean distance

• Wydawca: Polish Academy of Sciences, Committee of Electronics and Telecommunication
• Czasopismo: International Journal of Electronics and Telecommunications
• Rocznik: 2020
• Tom: Vol. 66, No. 3
• Strony: 561--569
• Opis fizyczny: Bibliogr. 37 poz., fot., rys., tab.

Twórcy

autor

Isnanto R. Rizal

• Computer Engineering Department of Diponegoro University, Semarang, Indonesia

autor

Zahra Ajub Ajulian

• Electrical Engineering Department of Diponegoro University, Semarang, Indonesia

autor

Santoso Imam

• Electrical Engineering Department of Diponegoro University, Semarang, Indonesia

autor

Lubis Muhammad Salman

• Electrical Engineering Department of Diponegoro University, Semarang, Indonesia

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).