Undoubtedly, we are living in era of digital information and technology. In this revolutionized world of digital information, we are exposed to a remarkable array of visual imagery. With sophisticated image editing tools and software?s, it is very easy to manipulate and temper the digital images, thereby questioning the trustworthiness of it. This paper presents a method based on a statistical technique, Independent Component Analysis (ICA), also known as a Blind Source Separation (BSS), to detect the copy-move kind of forgery in digital images. Results of this method prove that ICA can be effectively used for image forgery detection in digital image as a tool to digital image forensics.

1. 1C. T. Hsieh and Y. K. Wu, “Geometric Invariant Semi-fragile Image Watermarking Using Real Symmetric Matrix,” WSEAS Transaction on Signal Processing, Vol. 2, Issue 5, May 2006, pp.612-618.
2. A. C. Popescu and H. Farid, “Exposing Digital Forgeries by Detecting Traces of Resampling,” IEEE Transactions on Signal Processing, Vol. 53, 2005, pp. 758-767.
3. E. S. Gopi, N. Lakshmanan, T. Gokul, S. KumaraGanesh, and P. R. Shah, “DigitalImage Forgery Detection using Artificial Neural Network and Auto Regressive Coefficients,” Electrical and Computer Engineering, 2006, pp.194-197.
4. M. K. Johnson and H. Farid, “Exposing Digital Forgeries Through Chromatic Aberration,” in Proceedings of the 8th workshop on Multimedia and security, 2006, pp. 48-55.- 257
5. J. Lukas, J. Fridich, and M. Goljan, “Detecting Digital Image Forgeries Using Sensor Patter Noise,” in Proceedings of the SPIE Conference on Security Steganography, and Watermarking of Multimedia Contents, Vol. 6072, January 2006, pp. 362-372.
6. M. K. Johnson and H. Farid, “Exposing Digital Forgeries by Detecting Inconsistencies in Lighting,” in Proceedings of ACM Multimedia and Security Workshop, New York, 2005, pp.1-9.
7. J. Fridrich, D. Soukal, and J. Lukas, “Detection of Copy-Move Forgery in Digital Images,” in Proceedings of Digital Forensic Research Workshop, August 2003
8. A. C. Popescu and H. Farid, “Exposing Digital Forgeries by Detecting Duplicated Image Regions,” Technical Report, TR2004-515, Department of Computer Science, Dartmouth College, 2004.
9. G. Li, Q. Wu, D. Tu, and S. Sun, “A Sorted Neighborhood Approach for Detecting Duplicated Regions in Image Forgeries based on DWT and SVD,” in Proceedings of IEEE International Conference on Multimedia and Expo, Beijing China, July 2-5, 2007, pp. 1750-1753.
10. Michael Zimba, Sun Xingming , “DWT-PCA (EVD) Based Copy-move Image Forgery Detection”, International Journal of Digital Content Technology and its Applications. Volume 5, Number 1, January 2011
11. P. Comon, “Independent Component Analysis-A new concept?” Signal Processing, vol. 36, pp. 287-314, 1994.
12. J.F.Cardoso, “Blind Signal Separation: Statistical Principles”, Proc. of IEEE, vol. 9, no. 10, pp. 2009-2025, 1998.
13. AapoHyvärinen et al., “Independent Component Analysis: Algorithms and Applications”, Neural Networks, 13(4-5):411-430, 2000.
14. AapoHyvärinen et al., “Independent Component Analysis: Algorithms and Applications”, Neural Networks, 13(4-5):411-430, 2000.
15. A. Hyvarinen, “Fast and robust fixed-point algorithms for independent component analysis”. IEEE Trans. Neural Netw.,vol.10,no.3,pp.624-634,May 1999.
16. Koldovský, Z., Tichavský, P., and Oja, E.: Efficient Variant of Algorithm FastICA for Independent Component Analysis Attaining the Cram´er-Rao Lower Bound, IEEE Tr. Neural Networks, 17 (2006) 1265–1277.

Digital forensics Image processing BSS ICA Image tempering