International E-publication: Publish Projects, Dissertation, Theses, Books, Souvenir, Conference Proceeding with ISBN.  International E-Bulletin: Information/News regarding: Academics and Research

Image Duplication Forgery Detection using Two Robust Features

Author Affiliations

  • 1 Department of Computer engineering, Shahrood Branch, Islamic Azad University, Shahrood, IRAN

Res. J. Recent Sci., Volume 1, Issue (12), Pages 1-6, December,2 (2012)

Abstract

Nowadays duplication forgery is the most applicable method to make tampered images. This method copies a region of an image and pasted into another part(s) of that image. There are several methods to detect forged images. Most of them can only detect those regions which are exactly pasted into another part, but in practice the copied region is scaled or rotated before pasting to achieve the best matching with surrounding. In this paper we propose a method to detect duplicated regions in an image using SIFT features and then using Zernik moments. By using SIFT features we can detect duplicated regions even if they scaled or rotated, but these features cannot find flat duplicated regions. Zernik moments can solve this problem; they can find flat copied regions but failed to find scaled copied regions. So at first we will apply SIFT feature extraction method and find SIFT key points, but there is no SIFT key points in flat regions, then we will apply zernik moments on such regions, So duplicated region in all over the image even in flat regions will detected while the process time is efficient.

References

  1. Sharma Kalpa, Health IT in Indian Healthcare System: A New Initiative, Res. J. Recent Sci., 1(6), 83-86 (2012)
  2. Shahaboddin Shamshirband and Ali Za'fari., Evaluation of the Performance of Intelligent Spray Networks Based On Fuzzy Logic, Res. J. Recent Sci., 1(8), 77-81 (2012)
  3. Bora Abhijit, Science Communication through Mass Media, Res. J. Recent Sci., 1(1), 10-15 (2012)
  4. M. Stamp and P. Stavroulakis, Handbook of Information and Communication Security (2010)
  5. S. Jin Ryu, M. Jeong Lee, and H. Kyu Lee, Detection of copy-rotate- move forgery using Zernik moments (2010)
  6. Bayram S., Sencar H.T. and Memon N., An efficient and robust method for detecting copy-move forgery, Proc. of ICASSP, (2009)
  7. Solorio B., Nandi S. and A.K., Passive method for detecting duplicated regions affected by reection, rotation and scaling, EUSIPCO, (2009)
  8. Pan X. and Lyu S., Detection image region duplication using SIFT features (2008)
  9. Bernal J., Vilarino F. and Sanchez J., Feature detectors and descriptor: where we are now, september (2010)
  10. Lowe D., Distinctive image features from scale-invariant keypoints, IJCV, 60(2), 91–110 (2004)
  11. Beis J. and Lowe D., Shape indexing using approximate nearestneighbour search in high-dimensional spaces, CVPR, (1997)
  12. Suzuki S. and Abe K., Topological structural analysis of digital binary images by border following, CVGIP, 30(1), 32–46 (1985)
  13. Popescu A.C. and Farid H., Exposing digital forgeries by detecting duplicated image regions, Technical Report TR2004-515, Department of Computer Science, Dartmouth College, (2004)
  20. Irene Amerini, Lamberto Ballan, Student Member, IEEE, Roberto Caldelli, Member, IEEE, Alberto Del Bimbo, Member, IEEE, and Giuseppe Serra., A SIFT-based forensic method for copy-move attack detection and transformation recovery, IEEE(2011)