An Efficient Image Forgery Detection Using Biorthogonal Wavelet Transform and Improved Relevance Vector Machine-Reference-Cited by-同舟云学术

An Efficient Image Forgery Detection Using Biorthogonal Wavelet Transform and Improved Relevance Vector Machine

Published:2018-05-10 Issue:4 Volume:101 Page:1983-2008
ISSN:0929-6212
Container-title:Wireless Personal Communications
language:en
Short-container-title:Wireless Pers Commun

Author:

Jain Neelesh Kumar,Rathore Neeraj Kumar,Mishra Amit

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Computer Science Applications

Link

http://link.springer.com/article/10.1007/s11277-018-5802-6/fulltext.html

Reference60 articles.

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2. Redi, J. A., Taktak, W., & Dugelay, J.-L. (2011). Digital image forensics: A booklet for beginners. Multimedia Tools and Applications, 51(1), 133–162.

3. Amerini, I., Ballan, L., Caldelli, R., Del Bimbo, A., & Serra, G. (2011). A SIFT-based forensic method for copy-move attack detection and transformation recovery. IEEE Transactions on Information Forensics and Security, 6(3), 1099–1110.

4. Pan, X., & Lyu, S. (2010). Detecting image region duplication using sift features. In: Proceedings of the IEEE international conference on acoustics, speech, and signal processing (ICASSP’10) (pp.1706–1709).

5. Chauhana, D., Kasatb, D., Jainc, S., Thakared, V. (2016) Survey on keypoint based copy-move forgery detection methods on image. In Elsevier—International Conference on Computational Modeling and Security (CMS 2016) (pp. 206–212).

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