Image forgery detection algorithm based on exponential moments and locally sensitive Hash

LI Jianjun; WU Wenliang; ZHANG Fuquan

doi:10.11805/tkyda2019309

Journals >Journal of Terahertz Science and Electronic Information Technology >Volume 18 >Issue 4 >Page 679 > Article

Journal of Terahertz Science and Electronic Information Technology
Vol. 18, Issue 4, 679 (2020)

Image forgery detection algorithm based on exponential moments and locally sensitive Hash

LI Jianjun^1、*, WU Wenliang¹, and ZHANG Fuquan²

Author Affiliations

¹[in Chinese]

²[in Chinese]

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DOI: 10.11805/tkyda2019309 Cite this Article

LI Jianjun, WU Wenliang, ZHANG Fuquan. Image forgery detection algorithm based on exponential moments and locally sensitive Hash[J]. Journal of Terahertz Science and Electronic Information Technology , 2020, 18(4): 679 Copy Citation Text

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References

[1] ZHONG Junliu,GAN Yanfen,YOUNG Janson. A new block-based method for copy move forgery detection under image geometric transforms[J]. Multimedia Tools and Applications, 2017,73(16):14887-14903.

[2] YANG Hongying,NIU Ying,JIAO Lixian. Robust copy-move forgery detection based on multi-granularity superpixels matching[J]. Multimedia Tools and Applications, 2018,77(11):13615-13641.

[3] WANG Chunpeng,WANG Xingyuan,XIA Zhiqiu. Geometrically resilient color image zero-watermarking algorithm based on quaternion exponent moments[J]. Journal of Visual Communication and Image Representation, 2016,41(7):247-259.

[6] CHRISTLEIN V,RIESS C,JORDAN J. An evaluation of popular copy-move forgery detection approaches[J]. IEEE Transactions on Information Forensics & Security, 2012,7(6):1841-1854.

[7] RAHUL Dixit,RUCHIRA Naskar,SWATI Mishra. Blur-invariant copy-move forgery detection technique with improved detection accuracy utilizing SWT-SVD[J]. IET Image Processing, 2017,11(5):301-309.

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