A comprehensive evaluation procedure for copy-move forgery detection methods: results from a systematic review-Reference-Cited by-同舟云学术

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A comprehensive evaluation procedure for copy-move forgery detection methods: results from a systematic review

Published:2022-02-28 Issue:11 Volume:81 Page:15171-15203
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Warif Nor Bakiah Abd,Idris Mohd. Yamani Idna,Wahab Ainuddin Wahid Abdul,Ismail Nor-Syahidatul N.,Salleh Rosli

Funder

ministry of higher education, malaysia

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-022-12010-2.pdf

Reference62 articles.

1. Abdalla Y, Iqbal MT, Shehata M (2019) Convolutional neural network for copy-move forgery detection. Symmetry (Basel) 11(10):1–17. https://doi.org/10.3390/sym11101280

2. Agarwal R, Verma OP (2020) An efficient copy move forgery detection using deep learning feature extraction and matching algorithm. Multimed Tools Appl 79(11–12):7355–7376. https://doi.org/10.1007/s11042-019-08495-z

3. Al-Qershi OM, Khoo BE (Sep. 2013) Passive detection of copy-move forgery in digital images: state-of-the-art. Forensic Sci Int 231(1–3):284–295. https://doi.org/10.1016/j.forsciint.2013.05.027

4. Al-Qershi OM, Khoo BE (2018) Evaluation of copy-move forgery detection: datasets and evaluation metrics. Multimed Tools Appl 77(24):31807–31833. https://doi.org/10.1007/s11042-018-6201-4

5. Al-Qershi OM, Khoo BE (2019) Enhanced block-based copy-move forgery detection using k-means clustering. Multidimens Syst Signal Process 30(4):1671–1695. https://doi.org/10.1007/s11045-018-0624-y

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1. Comparative Analysis of Deep Learning Approaches for Detecting Copy-Move Forgery;2024 International Conference on Computational Intelligence and Computing Applications (ICCICA);2024-05-23

2. Decoding Image Integrity: A Comprehensive Analysis of YOLOv8’s Performance for Detecting Copy-Move Forgery;2024 11th International Conference on Signal Processing and Integrated Networks (SPIN);2024-03-21

3. Enhancing copy-move forgery detection through a novel CNN architecture and comprehensive dataset analysis;Multimedia Tools and Applications;2024-01-02

4. Cross-scale condition aggregation and iterative refinement for copy-move forgery detection;Applied Intelligence;2023-12-21

5. A Survey of Detection and Mitigation for Fake Images on Social Media Platforms;Applied Sciences;2023-10-05

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