Skip to main content

Advertisement

Springer Nature Link
Log in

An algorithm for robust image watermarking based on the DCT and Zernike moments

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

An image watermarking scheme in the 2D DCT domain is proposed by exploring the advantages of using Zernike moments. Zernike transform has been used in image processing applications such as image recognition, authentication, protection, etc. Here, we propose to use the Zernike moments of the DCT transform to provide an efficient watermarking method. Particularly, the novelty of the proposed approach relies on the method for selection of features that will enable both preserving the image quality and robustness to attacks. Also, a criterion for selection of image blocks suitable for watermarking is given. It is based on the ℓ 1-norm of Zernike moments. The efficiency of the proposed watermarking algorithm is proved on several examples considering different types of attacks (compression, noise, filtering, geometrical attacks).

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  1. Barni M, Bartolini F (2004) Watermarking systems engineering. Marcel Dekker, Inc., New York

    Google Scholar 

  2. Chen Q, Yang X, Zhao J (2005) Robust image watermarking with Zernike moments. In: Canadian conference on electrical and computer engineering. Saskatoon, SASK, pp 1340—1343

  3. Flusser J, Suk T, Zitová B (2009) Moments and moment invariants in pattern recognition. Wiley

  4. Foo SW, Dong Q (2009) A normalization-based robust watermarking scheme using Zernike moments. World Acad Sci Eng Technol 3(11):1968–1973

    Google Scholar 

  5. Hernandez JR, Amado M, Perez Gonzalez F (2000) DCT-domain watermarking techniques for still images: detector performance analysis and a new structure. IEEE Trans Image Process 9(1):55–68

    Article  Google Scholar 

  6. Hwang S-K, Kim W-Y (2006) A novel approach to the fast computation of Zernike moments. Pattern Recogn 39(11):2065–2076

    Article  MATH  Google Scholar 

  7. Kim HS, Lee H-K (2003) Invariant image watermark using Zernike moments. IEEE Trans Circuits Syst Video Technol 13(8):766–775

    Article  Google Scholar 

  8. Kotoulas L, Andreadis I (2007) Accurate calculation of image moments. IEEE Trans Image Process 16(8):2028–2037

    Article  MathSciNet  Google Scholar 

  9. Liu J, She K, Wu H (2010) Blind Image Watermarking using Dual Embedding Scheme in the Wavelet Transform Domain. J Comput Inf Syst 6(6):1887–1896

    Google Scholar 

  10. Muharemagić E, Furht B (2006) Survey of watermarking techniques and applications. In: Furht B, Kirovski D (eds) Multimedia watermarking techniques and applications. Auerbach Publication, pp 91–130

  11. Nikolaidis A, Pitas I (2003) Asymptotically optimal detection for additive watermarking in the DCT and DWT domains. IEEE Trans Image Process 12(5):563–571

    Article  Google Scholar 

  12. Orovic I, Orlandic M, Stankovic S (2014) An image watermarking based on the PDF modeling and quantization effects in the wavelet domain. Multimedia Tools Appl 70(3):1503–1519

    Article  Google Scholar 

  13. Papakostas GA, Boutalis YS, Papaodysseus CN, Fragoulis DK (2006) Numerical error analysis in Zernike moments computation. Image Vis Comput 24(9):960–969

    Article  MATH  Google Scholar 

  14. Qin C, Zhang X (2015) Effective reversible data hiding in encrypted image with privacy protection for image content. J Vis Commun Image Represent 31:154–164

    Article  Google Scholar 

  15. Qin C, Chang C-C, Chiu Y-P (2014) A novel joint data-hiding and compression scheme based on SMVQ and image inpainting. IEEE Trans Image Process 23(3):969–978

    Article  MathSciNet  Google Scholar 

  16. Qin C, Chang C-C, Hsu T-J (2015) Reversible data hiding scheme based on exploiting modification direction with two steganographic images. Multimedia Tools Appl 74(15):5861–5872

    Article  Google Scholar 

  17. Singhal N, Lee YY, Kim CS, Lee SU (2009) Robust image watermarking using local Zernike moments. J Vis Commun Image Represent 20(6):408–419

    Article  Google Scholar 

  18. Stankovic S, Orovic I, Zaric N, Ioana C (2010) Two dimensional time-frequency analysis based eigenvalue decomposition applied to image watermarking. Multimedia Tools Appl 49(3):529–543

    Article  Google Scholar 

  19. Stankovic S, Orovic I, Chabert M, Mobasseri B (2013) Image watermarking based on the space/spatial-frequency analysis and hermite functions expansion. J Electron Imaging 22(1):013014

    Article  Google Scholar 

  20. Stanković S, Orović I, Sejdić E (2015) Multimedia signals and systems: basic and advance algorithms for signal processing. Springer-Verlag, New York

    Google Scholar 

  21. Tahmasbi A, Fatemeh S, Shahriar SB (2011) Classification of benign and malignant masses based on Zernike moments. Comput Biol Med 41(8):726–735

    Article  Google Scholar 

  22. Tsolis DK, Sioutas S, Papatheodorou TS (2010) A multimedia application for watermarking digital images based on a content based image retrieval technique. Multimed Tools Appl 47(3):581–597

    Article  Google Scholar 

  23. Vincent M, Chabert M, Lacaze B (2005) A spread spectrum watermarking scheme based on periodic clock changes for digital images. In: Proceedings of information hiding, vol 3727, pp 91–105

  24. Zhang X, Qian Z, Ren Y, Feng G (2011) Watermarking with flexible self-recovery quality based on compressive sensing and compositive reconstruction. IEEE Trans Inf Forensics Secur 6(4):1223–1232

    Article  Google Scholar 

Download references

Acknowledgments

This work is supported by the Montenegrin Ministry of Science, project grant funded by the World Bank loan: CS-ICT “New ICT Compressive sensing based trends applied to: multimedia, biomedicine and communications”.

Author information

Authors and Affiliations

  1. Faculty of Electrical Engineering, University of Montenegro, Dz. Vasingtona bb, Podgorica, 81000, Montenegro

    Budimir Lutovac, Miloš Daković, Srdjan Stanković & Irena Orović

Authors
  1. Budimir Lutovac
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Miloš Daković
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Srdjan Stanković
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Irena Orović
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Budimir Lutovac.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lutovac, B., Daković, M., Stanković, S. et al. An algorithm for robust image watermarking based on the DCT and Zernike moments. Multimed Tools Appl 76, 23333–23352 (2017). https://doi.org/10.1007/s11042-016-4127-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-016-4127-2

Keywords