A Dataset on Digital Image Forgery Detection
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-7633-1_30
Reference20 articles.
1. Alkawaz M, Veeran M, Bachok R (2020) Digital image forgery detection based on expectation maximization algorithm. In: 2020 16th IEEE international colloquium on signal processing & its applications (CSPA 2020), 28–29 Feb 2020, Langkawi, Malaysia
2. Battiato S, Giudice O, Guarnera F, Puglisi G (2021) First quantization estimation by a robust data exploitation strategy of DCT coefficients. IEEE Access 9:73110–73120
3. Battiato S, Giudice O, Guarnera F, Puglisi G (2022) CNN-based estimation of the first quantization matrix from double compressed JPEG images. J Vis Commun Image Represent
4. Dixit A, Bag S (2019) Utilization of HOG-SVD based features with connected component labeling for multiple copy-move image forgery detection. In: 2019 IEEE 5th international conference on identity, security, and behavior analysis (ISBA)
5. Farhan NS, Abdulmunem ME, Abid-Ali M (2019) Image plagiarism system for forgery detection in maps design. In: 2019 2nd scientific conference of computer sciences (SCCS), University of Technology—Iraq
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