Email this article 
Open Access
Subscription or Fee Access
RDWT based Digital Image Watermarking and Extraction using ICA
Abstract
In recent years, watermarking has become an attractive field in the areas like copyright protection, image authentication. Many literatures have reported about Discrete Wavelet Transform (DWT) watermarking techniques for data security. However, DWT based watermarking schemes are found to be less robust against image processing attacks and the shift variance of Wavelet Packet Transform (WPT) causes inaccurate extraction. In this paper, an attempt is made to develop a watermarking scheme based on RDWT and extraction using Independent Component Analysis (ICA). VariousICAlike Fast ICA, Radical ICA, Pearson ICA, Jade ICA, Maximum Likelihood ICA, Mean Field ICA and Kernel ICA are proposed and implemented for extraction. Simulation results show that the proposed scheme produces high Peak Signal to Noise Ratio (PSNR) values over other transform techniques like DWT and WPT. Also results reveal that Fast ICA produces better similarity measure and Mutual Information over otherICAmethods.
Keywords
References
M.D. Swanson, M. Kobayashi, and A.H. Tewfik, “Multimedia data embedding and watermarking technologies,” Proc. IEEE, vol. 86, 1998, pp.1064-1087.
F.M. Boland, J.J.K.O. Ruanaidh, and C.Dautzenberg, “ Watermarking digital images for copyright protection,” Proc. Of the Int. Conf. on Image Processing and its applications, 1995, pp. 321- 326.
R.G. Van Schnyndel, A.Z. Tirkel, and C.F. Osborne, “ A Digital Watermark,” Proc. Int. Conf. on Image Processing, vol.2, 1994, pp. 86-90.
I.J. Cox, J.Kilian, T.Leighton, and T.Shamoon, “ Secure spread spectrum watermarking for multimedia,” IEEE Trans. On Image Processing, vol.6, no.12,1997, pp. 1673-1687.
H.J.M. Wang, P.C. Su, and C.C.J. Kuo, “Wavelet-based digital image watermarking,” Opt. Express, vol. 3, no. 12, 1998, pp. 491-496.
Mauro Barni, Franco Bartolini and Aleespandro piva, “ Improved wavelet based watermarking through pixel-wise masking,” IEEE Trans. On Image Processing, vol.10. no.5, 2001, pp. 783-791.
D. Kundur, and D. Hatzinakos, “Digital watermarking using multiresolution wavelet decomposition,” in Proc. IEEE Int. Conf. Acoustics, Speech, Signal Processing, vol. 5, 1998, pp. 2969-2972.
Werner Dietl, Peter Meerwald, and Andreas Uhl, “ Protection of wavelet based watermarking systems using filter parametrization,” Signal Processing (83) , 2003, pp. 2095-2116.
A.Adhipathi Reddy, B.N. Chatterji, “ A new wavelet based logo watermarking scheme,” Pattern Recognition Letters (26) ,2005, pp. 1019-1027.
Alexander H.Paquet, Saif Zahir and Rabab K. Ward, “Wavelet Packets based Image retrieval” IEEE Int. Conf. Image Processing,2000, pp. 455-460.
Alexander H.Paquet, Rabab K.Ward and Ioannis Pitas, “Wavelet Packets based Image digital watermarking for image verification and authentication” Signal Processing, 2003, pp. 2117-2132.
G. Thirugnanam, and S.Arulselvi, “Maximum Likelihood ICA and Kernel ICA comparison for Wavelet based digital Image watermarking” Int. Journal of Signal and Image Processing, vol. 1 (1), 2010, pp. 7-12.
Ju Liu, Xinghag zhang and Jiande Sun, “ A new image watermarking scheme based on DWT and ICA,” IEEE Int. Conf. Neural Networks and Signal Processing, 2003, pp. 14-17.
Mayank Vasta, Richa Singh, Afzel Noore, “Feature based RDWT watermarking for multimodal biometric system,” Journal of Image and Vision Computing, vol. 27, 2009 , pp. 293- 304.
Thai Duy Hien., Zensho Nakao.,and Yen-Wei Chen, “ Robust multi-logo watermarking by RDWT and ICA,” Signal Processing, 2006, pp. 2981-2993.
A.Hyvarinen, J. Karhunen, and E. Oja, Independent component analysis, First Edition, John Wiley & Sons, Inc., New york, 2002.
Ju Liu, Xingang Zhang, Jiande Sun and Miguel Angel Lagunas, “ A Digital watermarking schemem based on ICA,” 4th Int. Symposium on ICA and BSS, 2003, pp.215-220.
F.J. Gonzalez – Serrano et.al, “ ICA applied to Digital image watermark,” Proc. ICASSP, 2001.
V. Krishnaveni, S. Jayaraman, P.M. Manojkumar, K. Shivakumar, and Ramadoss, “Comparison of independent component analysis algorithms for removal of Ocular Artifacts from Electroencephalo gram” Journal of Measurement science review, vol.5, 2005.
G. Thirugnanam, and S. Arulselvi, “Wavelet Packet based Robust Digital Image Watermarking and Extraction using Independent Component Analysis” Int. Journal of Signal and Image Processing, vol. 1 (2) , 2010, pp. 80-87.
Juha Karvanen., John Eriksson and Visa Koivunen, “Pearson system based for blind separation” for Academy of Finland, 2001, pp. 245-260.
A.D.F.R. Pedro, Hojen-Sorensen, Ole Winther and Lars Kai Hansen, “Mean Field Approaches to Independent Component Analysis”, 2002, pp. 256-269.
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.