A Novel Approach for Copy-move Forgery Detection using Bilateral Filtering

Öz

Digital image processing methods have a wide area of usage and their complexity is increasing, as well as the tampering methods. A widely used tampering method is copy-move forgery. In this study, a hybrid method combining the DCT and Bilateral filtering is developed. In this method, first overlapping blocks are obtained from the input image. Then, bilateral filtering and DCT of these blocks are multiplied to obtain the refined block features. The block features are scanned by a zig-zag process followed by a lexicographic sorting. Finally, a similarity detection by a predetermined threshold parameter is applied to detect the forgery. Both visual and quantitative results demonstrated that the proposed method can determine the copy-move forgery regions.

Anahtar Kelimeler

• copy-move forgery,bilateral filtering,zigzag scanning,DCT (Discrete Cosinus Transformation

Kaynakça

1. [1] A. J. Fridrich, B. D. Soukal, and A. J. Luk´aˇs, “Detection of copymove forgery in digital images,” in in Proceedings of Digital Forensic Research Workshop. Citeseer, 2003.
2. [2] N. H. Kaplan and I. Erer, “Bilateral pyramid based pansharpening of multispectral satellite images,” in 2012 IEEE International Geoscience and Remote Sensing Symposium, 2012, pp. 2376–2379.
3. [3] S. Paris, P. Kornprobst, and J. Tumblin, “Bilateral filtering: Theory and applications,” Foundations and Trends in Computer Graphics and Vision, vol. 4, no. 1, pp. 1–73, 2009.
4. [4] N. H. Kaplan and I. Erer, “Bilateral filtering-based enhanced pansharpening of multispectral satellite images,” IEEE geoscience and remote sensing letters, vol. 11, no. 11, pp. 1941–1945, 2014.
5. [5] H. A. Alberry, A. A. Hegazy, and G. I. Salama, “A fast sift based method for copy move forgery detection,” Future Computing and Informatics Journal, vol. 3, no. 2, pp. 159–165, 2018.
6. [6] A. Novoz´amsk`y and M. ˇ Sorel, “Detection of copy-move image modification using jpeg compression model,” Forensic science international, vol. 283, pp. 47–57, 2018.
7. [7] A. Parveen, Z. H. Khan, and S. N. Ahmad, “Block-based copy–move image forgery detection using dct,” Iran Journal of Computer Science, pp. 1–11, 2019.
8. [8] N. B. A. Warif, A. W. A. Wahab, M. Y. I. Idris, R. Ramli, R. Salleh, S. Shamshirband, and K.-K. R. Choo, “Copy-move forgery detection: survey, challenges and future directions,” Journal of Network and Computer Applications, vol. 75, pp. 259–278, 2016.

9. [9] R. Lionnie, R. B. Bahaweres, S. Attamimi, and M. Alaydrus, “A study on pre-processing methods for copy-move forgery detection based on sift,” in TENCON 2017-2017 IEEE Region 10 Conference. IEEE, 2017, pp. 1142–1147.
10. [10] D. Chauhan, D. Kasat, S. Jain, and V. Thakare, “Survey on keypoint based copy-move forgery detection methods on image,” Procedia Computer Science, vol. 85, pp. 206–212, 2016.
11. [11] N. D. Wandji, S. Xingming, and M. F. Kue, “Detection of copy-move forgery in digital images based on dct,” arXiv preprint arXiv:1308.5661, 2013.
12. [12] Y. Huang, W. Lu, W. Sun, and D. Long, “Improved dct-based detection of copy-move forgery in images,” Forensic science international, vol. 206, no. 1-3, pp. 178–184, 2011.
13. [13] A. C. Popescu and H. Farid, “Exposing digital forgeries by detecting duplicated image regions,” Dept. Comput. Sci., Dartmouth College, Tech. Rep. TR2004-515, pp. 1–11, 2004.
14. [14] V. Manu and B. Mehtre, “Tamper detection of social media images using quality artifacts and texture features,” Forensic science international, vol. 295, pp. 100–112, 2019.
15. [15] M. H. Alkawaz, G. Sulong, T. Saba, and A. Rehman, “Detection of copy-move image forgery based on discrete cosine transform,” Neural Computing and Applications, vol. 30, no. 1, pp. 183–192, 2018.
16. [16] VCL, “Comofod - image database for copy-move forgery detection,” http://www.vcl.fer.hr/comofod/, Access Date: February 27, 2019).
17. [17] D. Tralic, I. Zupancic, S. Grgic, and M. Grgic, “Comofodnew database for copy-move forgery detection,” in Proceedings ELMAR-2013. IEEE, 2013, pp. 49–54.
18. [18] A. Boz and H. S¸ . Bilge, “Copy-move image forgery detection based on lbp and dct,” in 2016 24th Signal Processing and Communication Application Conference (SIU). IEEE, 2016, pp. 561–564.