Published November 28, 2012 | Version 10220
Journal article Open

Efficient Copy-Move Forgery Detection for Digital Images

Description

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.

Files

10220.pdf

Files (215.1 kB)

Name Size Download all
md5:5125cd85b21120d8e1e45be00e6e63d9
215.1 kB Preview Download

Additional details

References

  • J. Fridrich, "Methods for tamper detection in digital images," Proceeding of ACM Conference on Multimedia and Security, p. 1923, 1999.
  • C. L. Jing, "Image copy-move forgery detecting based on local invariant feature," Journal of Multimedia, vol. 7, 2012.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.