Commenced in January 2007
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Sequential Straightforward Clustering for Local Image Block Matching

Authors: Mohammad Akbarpour Sekeh, Mohd. Aizaini Maarof, Mohd. Foad Rohani, Malihe Motiei

Abstract:

Duplicated region detection is a technical method to expose copy-paste forgeries on digital images. Copy-paste is one of the common types of forgeries to clone portion of an image in order to conceal or duplicate special object. In this type of forgery detection, extracting robust block feature and also high time complexity of matching step are two main open problems. This paper concentrates on computational time and proposes a local block matching algorithm based on block clustering to enhance time complexity. Time complexity of the proposed algorithm is formulated and effects of two parameter, block size and number of cluster, on efficiency of this algorithm are considered. The experimental results and mathematical analysis demonstrate this algorithm is more costeffective than lexicographically algorithms in time complexity issue when the image is complex.

Keywords: Copy-paste forgery detection, Duplicated region, Timecomplexity, Local block matching, Sequential block clustering.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1076252

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References:


[1] J. Fridrich, "Detection of copy-move forgery in digital images," in Proceedings of Digital Forensic Research Workshop, 2003, pp. -.
[2] Popescu and H. Farid, "Exposing digital forgeries by detecting duplicated image regions," Tech. Rep., 2004.
[3] W. Luo, "Robust detection of region-duplication forgery in digital image," in IEEE Computer Society Washington, DC, USA, vol. Proceedings of the 18th International Conference on Pattern Recognition - Volume 04, 2006, pp. 746 - 749-.
[4] Lukas, Fridrich, and Goljan, "Detecting digital image forgeries using sensor pattern noise," in Security, Steganography, and Watermarking of Multimedia Contents VIII, vol. 6072, San Jose, CA, 2006, pp. -.
[5] B. Mahdian, "Using noise inconsistencies for blind image forensics," vol. 27, pp. 1497-1503-, 2009.
[6] M. K. Johnson and H. Farid, "Exposing digital forgeries in complex lighting environments," vol. 2, pp. 450-461-, 2007.
[7] Popescu and H. Farid, "Exposing digital forgeries in color filter array interpolated images," vol. 53, pp. 3948-3959-, 2005.
[8] A. Popescu and H. Farid, "Exposing digital forgeries by detecting traces of re-sampling," Tech. Rep., 2003.
[9] S. Bayram, "An efficient and robust method for detecting copy-move forgery," in IEEE International Conference on Acoustics, Speech and Signal Processing, vol. Washington, DC, USA, 2009, pp. -.
[10] B. Mahdian and S. Saic, "Detection of copy-move forgery using a method based on blur moment invariants," vol. 171, pp. 180-189-, 2007.
[11] Z. Zhang, "A survey on passive-blind image forgery by doctor method detection," in Proceedings of the Seventh International Conference on Machine Learning and Cybernetics. Kunming: IEEE, 2008, pp. -.
[12] B. Mahdian, "A bibliography on blind methods for identifying image forgery," vol. Signal Processing: Image Communication, pp. 389399-, 2010.
[13] H. J. Lin, C. W. Wang, and Y. T. Kao, "Fast copy-move forgery detection," vol. 5, pp. 188-197-, 2009.
[14] T. Sergois and Koutroumbas, Pattern Recognition - book - Third Edition. San diego: Elsevier, 2006.
[15] Stirling, "Stirling approximation for n!" pp. -.