On Image Analysis by the Methods of Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Invariant Image Recognition by Zernike Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Detection of Region-Duplication Forgery in Digital Image
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
Introduction to Information Retrieval
Introduction to Information Retrieval
Detection of Copy-Move Forgery in Digital Images Using SIFT Algorithm
PACIIA '08 Proceedings of the 2008 IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application - Volume 02
An efficient and robust method for detecting copy-move forgery
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Invariant image watermark using Zernike moments
IEEE Transactions on Circuits and Systems for Video Technology
Duplication forgery detection using improved DAISY descriptor
Expert Systems with Applications: An International Journal
Hiding a second appearance in a physical relief surface
IH'12 Proceedings of the 14th international conference on Information Hiding
Countering universal image tampering detection with histogram restoration
IWDW'12 Proceedings of the 11th international conference on Digital Forensics and Watermaking
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As forgeries have become popular, the importance of forgery detection is much increased. Copy-move forgery, one of the most commonly used methods, copies a part of the image and pastes it into another part of the the image. In this paper, we propose a detection method of copy-move forgery that localizes duplicated regions using Zernike moments. Since the magnitude of Zernike moments is algebraically invariant against rotation, the proposed method can detect a forged region even though it is rotated. Our scheme is also resilient to the intentional distortions such as additive white Gaussian noise, JPEG compression, and blurring. Experimental results demonstrate that the proposed scheme is appropriate to identify the forged region by copy-rotate-move forgery.