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Copy-Move Forgery Detection Based on Keypoint Clustering and Similar Neighborhood Search Algorithm

  • Published:2020 Issue: Volume:8 Page:36863-36875
  • ISSN:2169-3536
  • Container-title:IEEE Access
  • language:
  • Short-container-title:IEEE Access

Author:

Chen HaipengORCID,Yang XiwenORCID,Lyu YingdaORCID

Funder

Jilin Province Science and Technology Development Plan Project

National Natural Science Foundation of China

Natural Science Foundation of Jilin Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Cited by 45 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. Identification of Clustering Brisk Keypoint Feature in Grocery Product Using the Elbow Method;2024 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT);2024-07-04

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

3. ORBcmfd: Oriented FAST and Rotated BRIEF Keypoints Based Image Copy-Move Forgery Detection;2024 IEEE Students Conference on Engineering and Systems (SCES);2024-06-21

4. Copy–move forgery detection in digital image forensics: A survey;Multimedia Tools and Applications;2024-02-07

5. Passive Image Forgery Detection Techniques: A Review, Challenges, and Future Directions;Wireless Personal Communications;2024-02
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