Skip to main content
SpringerLink
Log in

Logo extraction using dynamic stochastic resonance

  • Original Paper
  • Published:
Signal, Image and Video Processing Aims and scope Submit manuscript

Abstract

This paper presents a novel technique for watermark (logo) extraction from the distorted watermarked images. The proposed technique is based on the combined discrete wavelet transform (DWT), discrete cosine transform (DCT), and dynamic stochastic resonance (DSR). In this technique, DCT transform is applied to the DWT coefficients of the watermarked image. Later on, variance is calculated from the DCT coefficients, and it is used to tune the DCT coefficient with the help of dynamic double-well system parameters that causes resonance to DCT coefficients. The experimental results have been compared with the existing techniques and were found superior in terms of peak-value-of-signal-to-noise-ratio (PSNR) and correlation coefficient.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Mohammad A.A., Haj A.A., Shaltaf S.: An improved SVD-based watermarking scheme for protecting rightful ownership. Signal Process. 88(9), 2158–2180 (2008)

    Article  MATH  Google Scholar 

  2. Ouhsain M., Hamza A.B.: Image watermarking scheme using nonnegative matrix factorization and wavelet transform. Expert Syst. Appl. 36(1), 2123–2129 (2009)

    Article  Google Scholar 

  3. Chandra B., Srinivas S.: A robust image watermarking scheme using singular value decomposition. J. Multimed. 3(1), 7–15 (2008)

    Google Scholar 

  4. Bhatnagar G., Raman B.: A new robust reference watermarking scheme based on DWT-SVD. Stand. Interfaces 31, 1001–1013 (2009)

    Google Scholar 

  5. Wang X.Y., Yang H.Y., Cui C.Y.: An SVM-based robust digital image watermarking against desynchronization attacks. Signal Process. Arch. 88(9), 2193–2205 (2008)

    Article  MATH  Google Scholar 

  6. Chang C.C., Lin C.C., Tseng C.S., Tai W.L.: Reversible hiding DCT based compressed images. Inf. Sci. 177(13), 2768–2786 (2007)

    Article  Google Scholar 

  7. Alturki F.T., Almutairi A.F, Mersereauu R.M.: Analysis of blind data hiding using discrete cosine transform phase modulation. Signal Process. Image Commun. 22(4), 347–362 (2007)

    Article  Google Scholar 

  8. Barni M., Bartolini F., Piva A.: Improved wavelet based watermarking through pixel wise masking. IEEE Trans. Image Process 10(5), 783–791 (2001)

    Article  MATH  Google Scholar 

  9. Hien T.D.: Robust multi-logo watermarking by RDWT and ICA. Signal Process. 86(10), 2981–2993 (2006)

    Article  MATH  Google Scholar 

  10. Kang X., Zeng W., Huang J.: A multi-band wavelet watermarking scheme. Int. J. Netw. Secur. 6(2), 121–126 (2008)

    Google Scholar 

  11. Reddy A.A., Chatterji B.N.: A new wavelet based logo-watermarking scheme. Pattern Recognit. Lett. 26, 1019–1027 (2005)

    Article  Google Scholar 

  12. Agreste S., Andaloro G.: A new approach to pre-processing digital image for wavelet-based transform. J. Comput. Appl. Math. 221(2), 274–283 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  13. Chang C., Lin C., Hu Y.: An SVD oriented watermark embedding scheme with high qualities for the restored images. Int. J. Innov. Comput. Inf. Control 3(3), 609–620 (2007)

    Google Scholar 

  14. Aslantas V.: An optimal robust digital image watermarking based on SVD using differential evolution algorithm. Opt. Commun. 282(5), 769–777 (2009)

    Article  Google Scholar 

  15. Rezazadeh S., Yazdi M.: Nonoblivious image watermarking system based on singular value decomposition and texture segmentation. Proc. World Acad. Sci. Eng. Tech 13, 255–259 (2009)

    Google Scholar 

  16. Chandra, D.S.: Digital image watermarking using singular value decomposition. In: Proceedings of the 45th Midwest Symposium on Circuits and Systems, vol. 3, pp. 264–267 (2002)

  17. Haj A.A.: Combined DWT-DCT digital image watermarking. J. Comput. Sci. 3(9), 740–746 (2007)

    Article  Google Scholar 

  18. Liu R., Tan T.: An SVD-based watermarking scheme for protecting rightful ownership. IEEE Trans. Multimed. 4(1), 121–128 (2002)

    Article  Google Scholar 

  19. Kim, J.R., Shik Moon, Y.: A robust wavelet-based digital watermark using level-adaptive thresholding. In: Proceedings of IEEE. ICIP99, Kobe, Japan (1999)

  20. Haj, A.A.: A habrid digital image watermarking algorithm. 4th International Conference on Innovation in Information Technology, pp. 690–694 (Nov 2007)

  21. Tsai, M.J., Hung, H.Y.: DCT and DWT-based image watermarking using subsampling. In: Proceedings of the 24th International Conference on Distributed Computing Systems Workshops, vol. 7, pp. 184–189 (2004)

  22. Braudaway, G.W.: Protecting publicly-available images with an invisible image watermark. In: Proceedings of IEEE International Conference on Image Process, vol. 1, pp. 524–527 (Oct 1997)

  23. Wu, G., Qiu, Z.: A novel watermarking scheme based on stochastic resonance. IEEE 8th Int. Conf. Signal Process., 2, 1–4 (2006)

    Google Scholar 

  24. Sun S., Lei B.: On an aperiodic stochastic resonance signal processor and its application in digital watermarking. Signal Process. 88, 2085–2094 (2008)

    Article  MATH  Google Scholar 

  25. Jha, R.K., Biswas, P.K., Mishra, D.: Improving watermark detection performance using suprathreshold stochastic resonance. In: Proceedings of IEEE TENCON 2010, Japan, vol. 1, pp. 691–696 (2010)

  26. Chouhan, R., Jha, R.K., Chaturvedi A., Yamasaki T., Aizawa, K.: Robust watermark extraction using SVD-based dynamic stochastic resonance. In: Proceedings of IEEE ICIP, Brussels, Belgium (11–14 Sept 2011)

  27. Rao K., Yip P.: Discrete Cosine Transform: Algorithms, Advantages, Applications. Academic Press, USA (1990)

    MATH  Google Scholar 

  28. Wu C., Hsieh W.: Digital watermarking using zerotree of DCT. IEEE Trans. Consumer Electron. 46(1), 87–94 (2000)

    Article  Google Scholar 

  29. Gammaitoni L., Hanggi P., Jung P., Marchesoni F.: Stochastic resonance. Rev. Mod. Phys. 70, 223–287 (1998)

    Article  Google Scholar 

  30. Moss F., Pierson D., O’Gorman D.: Stochastic resonance: tutorial and update. Int. J. Bifurcation Chaos 4(6), 1383–1397 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  31. Risken H.: The Fokkar Plank Equation. Springer, Berlin (1984)

    Book  Google Scholar 

  32. Ye, Q., Huang, H., He, X., Zhang, C.: A SR-based radon transform to extract weak lines from noise images. In: Proceedings of IEEE ICIP, vol. 5, pp. 1849–1852 (2003)

Download references

Author information

Authors and Affiliations

  1. PDPM Indian Institute of Information Technology, Design and Manufacturing, Jabalpur, 482005, India

    Rajib Kumar Jha & S. Shrivastava

  2. Indian Institute of Technology Kharagpur, Kharagpur, 721302, India

    P. K. Biswas

Authors
  1. Rajib Kumar Jha
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. P. K. Biswas
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. S. Shrivastava
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rajib Kumar Jha.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Jha, R.K., Biswas, P.K. & Shrivastava, S. Logo extraction using dynamic stochastic resonance. SIViP 7, 119–128 (2013). https://doi.org/10.1007/s11760-011-0236-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11760-011-0236-6

Keywords

Search

Navigation