Accurate and robust image copy-move forgery detection using adaptive keypoints and FQGPCET-GLCM feature-Reference-Cited by-同舟云学术

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Accurate and robust image copy-move forgery detection using adaptive keypoints and FQGPCET-GLCM feature

Published:2023-05-12 Issue:1 Volume:83 Page:2203-2235
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Wang Xiang-yang,Wang Xing-qi,Niu Pan-pan,Yang Hong-ying

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/s11042-023-15499-3.pdf

Reference49 articles.

1. Abdel-Basset M, Manogaran G, Fakhry AE et al (2020) 2-levels of clustering strategy to detect and locate copy-move forgery in digital images. Multimed Tools Appl 79(7):5419–5437

2. Achanta R, Shaji A, Smith K et al (2012) SLIC superpixels compared to state-of-the-art superpixel methods. IEEE Trans Pattern Anal Mach Intell 34(11):2274–2282

3. Amerini I, Ballan L, Caldelli R et al (2013) Copy-move forgery detection and localization by means of robust clustering with J-linkage. Signal Process Image Commun 28(6):659–669

4. Anbu T, Joe MM, Murugeswari G (2021) A comprehensive survey of detecting tampered images and localization of the tampered region. Multimed Tools Appl 80:2713–2751

5. Ardizzone E, Bruno A, Mazzola G (2015) Copy-move forgery detection by matching triangles of keypoints. IEEE Trans Inf Forensic Secur 10(10):2084–2094

Cited by 9 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Similarity-Based Positional Attention-Aided Deep Learning Model for Copy–Move Forgery Detection;IEEE Transactions on Artificial Intelligence;2024-09

2. A copy-move forgery detection technique using DBSCAN-based keypoint similarity matching;International Journal of Machine Learning and Cybernetics;2024-07-03

3. A Deep Learning Model to Inspect Image Forgery on SURF Keypoints of SLIC Segmented Regions;Engineering, Technology & Applied Science Research;2024-02-08

4. Advancing Copy-Move Manipulation Detection in Complex Image Scenarios Through Multiscale Detector;IEEE Access;2024

5. CNN-Keypoint Based Two-Stage Hybrid Approach for Copy-Move Forgery Detection;IEEE Access;2024

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