Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30521
Efficient Copy-Move Forgery Detection for Digital Images

Authors: Somayeh Sadeghi, Hamid A. Jalab, Sajjad Dadkhah

Abstract:

Due to availability of powerful image processing software and improvement of human computer knowledge, it becomes easy to tamper images. Manipulation of digital images in different fields like court of law and medical imaging create a serious problem nowadays. Copy-move forgery is one of the most common types of forgery which copies some part of the image and pastes it to another part of the same image to cover an important scene. In this paper, a copy-move forgery detection method proposed based on Fourier transform to detect forgeries. Firstly, image is divided to same size blocks and Fourier transform is performed on each block. Similarity in the Fourier transform between different blocks provides an indication of the copy-move operation. The experimental results prove that the proposed method works on reasonable time and works well for gray scale and colour images. Computational complexity reduced by using Fourier transform in this method.

Keywords: Digital Forensics, image forgery, Copy-Move forgery

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1074821

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2382

References:


[1] J. Fridrich, "Methods for tamper detection in digital images," Proceeding of ACM Conference on Multimedia and Security, p. 1923, 1999.
[2] C. L. Jing, "Image copy-move forgery detecting based on local invariant feature," Journal of Multimedia, vol. 7, 2012.
[3] Q. S. W. Chen and W. Su, "Image splicing detection using 2-d phase congruency and statistical moments of characteristic function," E. J. Delp and P. W. Wong, editors, Proceedings of SPIE: Security and Watermarking of Multimedia Content IX, vol. 6505, p. 65050, 2007.
[4] D. T. G. Li, Q. Wu and S.Sun, "A sorted neighborhood approach for detecting duplicated regions in image forgeries based on dwt and svd," Proceedings of IEEE International Conference on Multimedia and Expo, pp. 1750-1753, 2007.
[5] a. J. L. J. Fridrich, D.Soukal, "Detection of copy-move forgery in digital images," Proceeding of Digital Forensic Research Workshop, pp. 55-61, 2003.
[6] S. S. B. Mahdian, "Detection of copymove forgery using a method based on blur moment invariants," Proceedings of fifth International conference on Forensic Science International, p. 180189, 2007.
[7] M. G. M. Najah, H. Muhammad and B. George, "Copy-move forgery detection using dyadic wavelet transform," Eighth International Conference Computer Graphics, Imaging and Visualization, pp. 103-108, 2011.
[8] G. Q. H. Jie, Z. Huaxiong and H. Hai, "An improved lexicographical sort algorithm of copy-move forgery detection," Second International Conference on Networking and Distributed Computing, pp. 23-27, 2011.
[9] S. W. X. Kang, "Identifying tampered regions using singular value decomposition in digital image forensics," International Conference on Computer Science and Software Engineering, 2008.
[10] X. P. Z. H. Z. Zhang, Y. Ren and S. Zhang, "A survey on passive-blind image forgery by doctor method detection," Proceedings of the Seventh International Conference on Machine Learning and Cybernetics, 2008.