CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

An Effective Image Watermarking System for High Embedding Capacity

Published on April 2012 by Chandan Singh, Sukhjeet K. Ranade
journal_cover_thumbnail

International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT 2012)
Foundation of Computer Science USA
IRAFIT - Number 4
April 2012
Authors: Chandan Singh, Sukhjeet K. Ranade
3b19311e-e751-4089-b6ec-9ee8a42a9420

Chandan Singh, Sukhjeet K. Ranade . An Effective Image Watermarking System for High Embedding Capacity. International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT 2012). IRAFIT, 4 (April 2012), 22-28.

@article{
author = { Chandan Singh, Sukhjeet K. Ranade },
title = { An Effective Image Watermarking System for High Embedding Capacity },
journal = { International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT 2012) },
issue_date = { April 2012 },
volume = { IRAFIT },
number = { 4 },
month = { April },
year = { 2012 },
issn = 0975-8887,
pages = { 22-28 },
numpages = 7,
url = { /proceedings/irafit/number4/5874-1030/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT 2012)
%A Chandan Singh
%A Sukhjeet K. Ranade
%T An Effective Image Watermarking System for High Embedding Capacity
%J International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT 2012)
%@ 0975-8887
%V IRAFIT
%N 4
%P 22-28
%D 2012
%I International Journal of Computer Applications
Abstract

In this paper, we present a computationally fast and robust image watermarking system with high embedding capacity. The watermark signal is embedded by quantizing the magnitudes of higher order Zernike moments (ZMs). The use of fast and numerically stable method for ZMs computation is proposed to overcome the high computational complexity and numerical instability at the high order of moments. An 8-way symmetry/ anti-symmetry property and recurrence relations for calculation of trigonometric functions are employed to further improve the time and space complexity. Experimental results show that the proposed method provides an excellent tradeoff between embedding capacity, watermark robustness, and visual imperceptibility.

References
  1. Cox, I.J., Kilian, J., Leighton, F.T., and Shamoon, T. 1997. Secure Spread Spectrum Watermarking for Multimedia. IEEE Transactions on Image Processing 6(12):1673-1687.
  2. O' Ruanaidh, J.J.K. and Pun, T. 1998. Rotation, Scale and Translation Invariant Spread Spectrum Digital Image Watermarking. Signal Processing. 66(8):pp. 303-317.
  3. Petitcolas, F.A.P., Anderson, R.J., and Kuhn, M.G. 1999. Information Hiding| A Survey. In proceedings of the IEEE Special issue on Protection of Multimedia content. 87(7):1062-1078
  4. Lan, T.-H. and Tewfik A.H. 2006. A Novel High-Capacity Data-Embedding System. IEEE Transactions on Image Processing, 15(8):2431-2440.
  5. Kumar, P.M. and Shunmuganathan, K.L. 2010. A reversible high embedding data hiding technique for hiding secret data in images. International Journal of Comp. Sci. and Inf. Security 7(3): 109-115
  6. Potdar, V. M., Han, S. and Chang, E. 2005. A Survey of Digital Image Watermarking Techniques. In proceedings of 3rd IEEE International Conference on Industrial Informatics. INDIN: 709-716.
  7. Farzam, M. and Shirani, S. 2001. A Robust Multimedia Watermarking Technique using Zernike Transform. IEEE 4th Workshop on Multimedia Signal Processing. 529-534
  8. Kim, H.S., and Lee, H.-K. 2003. Invariant Image Watermark using Zernike Moments. IEEE Transactions on Circuits and Systems for Video Tech. 13(8): 766-775.
  9. Xin, Y., Liao, S. and Pawlak, M. 2007 Circularly Orthogonal Moments for Geometrically Robust Image Watermarking, Pattern Recognition 40: 3740-3752.
  10. Singhal, N., Lee, Y.-Y., Kim, C.-S. and Lee, S.-U. 2009. Robust Image Watermarking using Local Zernike Moments. Journal of Vision Communication and Image Representation 20:408-419.
  11. Wang, X.-Y., Hou, L.-M. and Yang, H.-Y. 2009. A Feature-Based Image Watermarking Scheme Robust to Local Geometrical Distortions. Journal of Optics A: Pure and Applied Optics. DOI:10.1088/1464-4258/11/6/065401
  12. Wang, X.-Y., Xu, Z.-H., and Yang, H.-Y. 2009. A Robust Image Watermarking Algorithm using SVR Detection. Expert Systems with Applications. 36:9056-9064.
  13. Yap, P.-T. and Paramesran, R. 2005. An Image Watermarking Scheme Based on Orthogonal Moments. In proceedings of TENCON. IEEE Region 10 Conference.
  14. Venkataramana, A. and Raj, P. A. 2007. Image Watermarking using Krawtchouk Moments. In proceedings of the IEEE International Conference on Computing: Theory and Applications.
  15. Deng, C. Gao, X., Li, X. and Tao, D. 2009. A local Tchebichef moments-based robust image watermarking. Signal Processing 89:1531-1539.
  16. Singh, C. 2006. Improved quality of Reconstructed Images using floating point arithmetic for moment calculation. Pattern Recognition. 39:2047-2064.
  17. Kintner, E.C. 1976. A Recursive Relation for Calculating the Zernike polynomials. Opt. Acta 23 (6):489-500.
  18. Prata, A. and Rusch, W.V.T. 1989. Algorithm for computation of Zernike polynomials expansion coefficients. Appl. Opt. 28:749-754.
  19. Chong, C.-W., Paramesran, R. and Mukundan, R. 2003. A comparative analysis of algorithms for fast computation of Zernike moments. Pattern Recognition. 36:731-742
  20. Singh, C. and Walia, E. 2010. Fast and Numerically Stable Methods for the Computation of Zernike moments. Pattern Recognition. 43: 2497-2506.
  21. Singh, C. and Walia, E. 2011. Algorithms for Fast Computation of Zernike moments and their Numerical Stability. Image and Vision Computing. 29:251-259
  22. Petitcolas, F.A.P., Steinebach, M., Raynal, F., Dittmann, J., Fontaine, C. and Fates, N. 2001. A public automated web-based evaluation service for watermarking schemes: StirMark Benchmark. In proc. of SPIE. 4314: 575- 584
Index Terms

Computer Science
Information Sciences

Keywords

Zernike Moments Embedding Capacity Robustness Visual Imperceptibility Numerical Instability