Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30238
Distortion Estimation in Digital Image Watermarking using Genetic Programming

Authors: Labiba Gilani, Asifullah Khan, Anwar M. Mirza

Abstract:

This paper introduces a technique of distortion estimation in image watermarking using Genetic Programming (GP). The distortion is estimated by considering the problem of obtaining a distorted watermarked signal from the original watermarked signal as a function regression problem. This function regression problem is solved using GP, where the original watermarked signal is considered as an independent variable. GP-based distortion estimation scheme is checked for Gaussian attack and Jpeg compression attack. We have used Gaussian attacks of different strengths by changing the standard deviation. JPEG compression attack is also varied by adding various distortions. Experimental results demonstrate that the proposed technique is able to detect the watermark even in the case of strong distortions and is more robust against attacks.

Keywords: fitness function, blind watermarking, Genetic Programming (GP), Discrete Cosine Transform (DCT)

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1057077

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1354

References:


[1] I. J. Cox, M. L. Miller, and J. A. Bloom, Digital Watermarking and fundamentals, Morgan Kaufmann, San Francisco, 2002.
[2] M. Barni, and F. Bartolini, Watermarking systems engineering: Enabling digital assets security and other application, Marcel Dekker, Inc. New York, 2004.
[3] Kiryung Lee, Dong Sik Kim, Taejeong Kim, and Kyung Ae Moon, "Em estimation of scale factor for quantization-based audio watermarking," in Digital Watermarking,Second International Workshop,IWDW 2003, Seoul, Korea, Oct. 2003.
[4] A. Piva, M. Barni, F. Bartolini, V. Cappellini, DCT-based Watermark Recovering without Resorting to the Uncorrupted Original Image, Proc Int. Conf. Image Processing, vol. 1, Oct. 1997, pp. 520-523.
[5] J.C. Oostveen, A.A.C. Kalker, and M. Staring, "Adaptive quantize watermarking," in Proc. of SPIE: Security, Steganography, and Watermarking of Multimedia Contents VI, San Jose, California, USA, 2004, vol. 5306, pp. 37-39.
[6] Qiao Li, Ingemar J. Cox, Using perceptual models to improve fidelity and provide invariance to volumetric scaling for quantization index modulation watermarking, Campus Seminar Series, Departments of Computer Science and Electronic and Electrical Engineering, University College London Torrington Place, London, WC1E 7JE, England, Feb. 2005.
[7] Sviatoslav Voloshynovskiy, Frederic Deguillaume, Shelby Pereira and Thierry Pun, Optimal adaptive diversity watermarking with channel state estimation University of Geneva - CUI, 24 rue duGeneral Dufour, CH 1211, Geneva 4, Switzerland, 2002.
[8] A. Khan and Anwar M. Mirza, Genetic Perceptual Shaping: Utilizing Cover Image and Conceivable Attack Information Using Genetic Programming, accepted in International Journal of Information Fusion, Elsevier Science, 2005.
[9] Asifullah Khan, A Novel approach to decoding: Exploiting Anticipated Attack Information using Genetic Programming, International Journal of Knowledge-Based Intelligent Engineering Systems, 2006, (in press).
[10] A. Khan, Anwar M. Mirza and A. Majid, Intelligent Perceptual Shaping of a Digital Watermark: Exploiting Characteristics of Human Visual System, accepted in the International Journal of Knowledge-Based Intelligent Engineering Systems, 2005.
[11] W. Banzhaf, P. Nordin, R.E. Keller, and F.D. Francone, "Genetic Programming: An Introduction," Morgan Kaufmann Publishers, CA, 1998.
[12] S. Gustafon, "An Analysis of Diversity in Genetic Programming", PhD Thesis, University of Nottingham, UK, 2004.
[13] http://www.geneticprogramming.com.