Copy Move Forgery Detection in Contrast Variant Environment using Binary DCT Vectors

Full Text (PDF, 778KB), PP.38-44

Views: 0 Downloads: 0

Author(s)

Sunil Kumar 1,* J. V. Desai 1 Shaktidev Mukherjee 2

1. Mody University of Science and Technology, Lakshmangarh, 332311, India

2. Moradabad Institute of Technology, Moradabad, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2015.06.05

Received: 4 Feb. 2015 / Revised: 5 Mar. 2015 / Accepted: 10 Apr. 2015 / Published: 8 May 2015

Index Terms

Copy move forgery, intensity invariant forgery detection, binary DCT coefficients, contrast invariant forgery detection, illumination invariant, blind forgery detection

Abstract

Copy move forgery detection is a very popular research area and a lot of methods have been suggested by researchers. However, every method has its own merits and weaknesses and hence, new techniques are being continuously devised and analyzed. There are many post processing operations used by the manipulators to obstruct the forgery detection techniques. One such operation is changing the contrast of the whole image or copy moved regions, which many existing methods fail to address. A novel method using binary discrete cosine transform vectors is proposed to detect copy move forgery in the presence of contrast changes. The image is divided into overlapping blocks and DCT coefficients are calculated for these blocks. Feature vectors are created from these blocks using signs of the DCT coefficients. Coefficient of correlation is used to match resulting binary vectors. The experiments show that the proposed method is able to detect copy move forgery in presence of contrast changes. The proposed method is also invariant to other post processing operations like Gaussian noise, JPEG compression and little rotation and scaling. 

Cite This Paper

Sunil Kumar, J. V. Desai, Shaktidev Mukherjee,"Copy Move Forgery Detection in Contrast Variant Environment using Binary DCT Vectors", IJIGSP, vol.7, no.6, pp.38-44, 2015. DOI: 10.5815/ijigsp.2015.06.05

Reference

[1]"Image Authentication and Forensics | Fourandsix Technologies - Photo Tampering throughout History." [Online]. Available: http://www.fourandsix.com/photo-tampering-history/. [Accessed: 21-Oct-2014].

[2]G. K. Birajdar and V. H. Mankar, "Digital image forgery detection using passive techniques: A survey," Digit. Investig., vol. 10, no. 3, pp. 226–245, Oct. 2013.

[3]M. Sridevi, C. Mala, and S. Sanyam, "Comparative Study of Image Forgery and Copy-Move Techniques," in Advances in Computer Science, Engineering & Applications SE - 71, vol. 166, D. C. Wyld, J. Zizka, and D. Nagamalai, Eds. Springer Berlin Heidelberg, 2012, pp. 715–723.

[4]S. Kumar, S. Das, and S. Mukherjee, "Copy-Move Forgery Detection in Digital Images: Progress and Challenges.," Int. J. Comput. Sci. Eng., vol. 3, no. 2, pp. 652–663, 2011.

[5]V. M. Potdar, S. Han, and E. Chang, "A survey of digital image watermarking techniques," in INDIN '05. 2005 3rd IEEE International Conference on Industrial Informatics, 2005., 2005, pp. 709–716.

[6]A. Fridrich, B. Soukal, and A. Lukáš, "Detection of copy-move forgery in digital images," Proc. Digit. Forensic Res. Work., 2003.

[7]A. C. Popescu and H. Farid, "Exposing Digital Forgeries by Detecting Duplicated Image Regions," Dept. Comput. Sci., Dartmouth Coll. Tech. Rep. TR2004-515, pp. 1–11, 2004.

[8]K. Sunil, D. Jagan, and M. Shaktidev, "DCT-PCA Based Method for Copy-Move Forgery Detection," Adv. Intell. Syst. Comput., vol. 249, pp. 577–583, 2014.

[9]Y. Huang, W. Lu, W. Sun, and D. Long, "Improved DCT-based detection of copy-move forgery in images.," Forensic Sci. Int., vol. 206, no. 1–3, pp. 178–84, Mar. 2011.

[10]W. Luo and J. Huang, "Robust Detection of Region-Duplication Forgery in Digital Image," 18th Int. Conf. Pattern Recognit., pp. 746–749, 2006.

[11]M. Ghorbani, M. Firouzmand, and A. Faraahi, "DWT-DCT (QCD) based copy-move image forgery detection," Syst. Signals Image Process. (IWSSIP), 2011 18th Int. Conf., pp. 1–4, 2011.

[12]G. L. G. Li, Q. W. Q. Wu, D. T. D. Tu, and S. S. S. Sun, "A Sorted Neighborhood Approach for Detecting Duplicated Regions in Image Forgeries Based on DWT and SVD," Multimed. Expo, 2007 IEEE Int. Conf., pp. 2007–2010, 2007.

[13]Y. Cao, T. Gao, L. Fan, and Q. Yang, "A robust detection algorithm for copy-move forgery in digital images," Forensic Sci. Int., vol. 214, no. 1–3, pp. 33–43, 2012.

[14]M. Alsawadi, G. Muhammad, M. Hussain, and G. Bebis, "Copy-Move Image Forgery Detection Using Local Binary Pattern and Neighborhood Clustering," Model. Symp. (EMS), 2013 Eur., pp. 249–254, 2013.

[15]R. Davarzani, K. Yaghmaie, S. Mozaffari, and M. Tapak, "Copy-move forgery detection using multiresolution local binary patterns," Forensic Sci. Int., vol. 231, no. 1–3, pp. 61–72, 2013.

[16]S. Bayram, H. Taha Sencar, and N. Memon, "An efficient and robust method for detecting copy-move forgery," in 2009 IEEE International Conference on Acoustics, Speech and Signal Processing, 2009, pp. 1053–1056.

[17]G. Lynch, F. Y. Shih, and H.-Y. M. Liao, "An efficient expanding block algorithm for image copy-move forgery detection," Inf. Sci. (Ny)., vol. 239, pp. 253–265, Aug. 2013.

[18]X. Pan and S. Lyu, "Detecting image region duplication using SIFT features," IEEE Int. Conf. onAcoustics Speech Signal Process., pp. 1706–1790, 2010.

[19]H. Huang, W. Guo, and Y. Zhang, "Detection of Copy-Move Forgery in Digital Images Using SIFT Algorithm," 2008 IEEE Pacific-Asia Work. Comput. Intell. Ind. Appl., pp. 272–276, Dec. 2008.

[20]I. Amerini, L. Ballan, R. Caldelli, A. Del Bimbo, G. Serra, and A. Del Bimbo, "Geometric tampering estimation by means of a sift-based forensic analysis," in ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 2010, pp. 1702–1705.

[21]S. Baboo, C. Applications, and C. Forgery, "Detection of Region Duplication Forgery in Digital Images Using SURF," IJCSI Int. J. Comput. Sci. Issues, vol. 8, no. 4, pp. 199–205, 2011.

[22]M. Jaberi, G. Bebis, M. Hussain, G. Muhammad, C. Science, and S. Arabia, "Accurate and robust localization of duplicated region in copy-move image forgery," Mach. Vis. Appl., vol. 25, no. 2, pp. 451–475, 2014.

[23]D. Tralic, I. Zupancic, S. Grgic, and M. Grgic, "CoMoFoD-2014; New database for copy-move forgery detection," ELMAR, 2013 55th Int. Symp., September, pp. 49–54, 2013.

[24]V. Christlein, C. C. Riess, J. Jordan, and E. Angelopoulou, "An Evaluation of Popular Copy-Move Forgery Detection Approaches," Inf. Forensics Secur. IEEE Trans., vol. 7, no. 6, pp. 1841–1854, Aug. 2012.