Skip to main content

Advertisement

SpringerLink
Log in

Wavelet-Hadamard based blind image watermarking using genetic algorithm and decision tree

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

Abstract

Recently the active use of Internet and multimedia technologies has increased the violation of copyright. Digital watermarking has a crucial role in the field of multimedia copyright protection. In this paper, an optimized image watermarking technique based on Discrete Wavelet Transform (DWT) and Hadamard transform is proposed. Genetic Algorithm (GA) is an optimizing technique used to satisfy the tradeoff between robustness and imperceptibility. Blind property is conducted using the estimation capability of Decision Tree (DT). First the host image is transformed using second level DWT, then Hadamard transform is applied on selected DWT sub-bands. Adaptive multiple strength values are computed using GA. The watermark is successfully extracted using the trained DT which estimates the original coefficients needed for the extraction process without the need for the original host image. The proposed technique is evaluated against several types of attacks: compression, median filtering, salt and pepper noise, histogram equalization, blurring, scaling, painting, and cropping. Experimental results show that the proposed watermarking technique is robust against these attacks while keeping good imperceptibility. The proposed technique outperforms the compared techniques according to robustness, imperceptibility, and capacity.

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

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

Similar content being viewed by others

References

  1. Aslantas V (2008) A singular-value decomposition-based image watermarking using genetic algorithm. AEU-International Journal of Electronics and Communications 62(5):386–394

    Article  Google Scholar 

  2. Bamatraf A, Ibrahim R, Salleh M, Mohd N (2011). A new digital watermarking algorithm using combination of least significant bit (LSB) and inverse bit. arXiv preprint arXiv:11116727

  3. Bassel A, Nordin MJ, Abdulkareem MB (2017) An improved robust image watermarking scheme based on the singular value decomposition and genetic algorithm. In: International Visual Informatics Conference. Springer, pp 702–713

  4. Gen M, Cheng R (2000) Genetic algorithms and engineering optimization, vol 7. John Wiley & Sons

  5. Han J, Pei J, Kamber M (2011) Data mining: concepts and techniques. Elsevier

  6. Holland JH (1975). Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. University of Michigan Press Ann Arbor,

  7. Huang H-C, Chen Y-H (2013). Application of genetic-based wavelet packet watermarking for copyright protection. In: Recent advances in information hiding and applications. Springer, pp 139–153

  8. Kalarikkal Pullayikodi S, Tarhuni N, Ahmed A, Shiginah FB (2017) Computationally efficient robust color image watermarking using fast Walsh hadamard transform. Journal of Imaging 3(4):46

    Article  Google Scholar 

  9. Kazemivash B, Moghaddam ME (2017) A robust digital image watermarking technique using lifting wavelet transform and firefly algorithm. Multimed Tools Appl 76(20):20499–20524

    Article  Google Scholar 

  10. Kazemivash B, Moghaddam ME (2018) A predictive model-based image watermarking scheme using regression tree and firefly algorithm. Soft Comput 22(12):4083–4098

    Article  Google Scholar 

  11. Kim C, Shin D, Leng L, Yang C-N (2018) Separable reversible data hiding in encrypted halftone image. Displays 55:71–79

    Article  Google Scholar 

  12. Kim C, Shin D, Leng L, Yang C-N (2018) Lossless data hiding for absolute moment block truncation coding using histogram modification. J Real-Time Image Proc 14(1):101–114

    Article  Google Scholar 

  13. Kumaran T, Thangavel P (2008) Genetic algorithm based watermarking in double-density dual-tree DWT. In: Wavelet Analysis and Pattern Recognition. In: 2008. ICWAPR’08. International conference on. IEEE, pp 585–590

  14. Kundur D, Hatzinakos D (2004) Toward robust logo watermarking using multiresolution image fusion principles. IEEE Transactions on Multimedia 6(1):185–198

    Article  Google Scholar 

  15. Leng L, Li M, Kim C, Bi X (2017) Dual-source discrimination power analysis for multi-instance contactless palmprint recognition. Multimed Tools Appl 76(1):333–354

    Article  Google Scholar 

  16. Liu H, Xiao D, Zhang R, Zhang Y, Bai S (2016) Robust and hierarchical watermarking of encrypted images based on compressive sensing. Signal Process Image Commun 45:41–51

    Article  Google Scholar 

  17. Mallat SG (1989) A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans Pattern Anal Mach Intell 11(7):674–693

    Article  Google Scholar 

  18. Mehta R, Rajpal N, Vishwakarma VP (2018) Robust image watermarking scheme in lifting wavelet domain using GA-LSVR hybridization. Int J Mach Learn Cybern 9(1):145–161

    Article  Google Scholar 

  19. Mohananthini N, Yamuna G (2016) Comparison of multiple watermarking techniques using genetic algorithms. Journal of Electrical Systems and Information Technology 3(1):68–80. https://doi.org/10.1016/j.jesit.2015.11.009

    Article  Google Scholar 

  20. Nikolaidis A, Pitas I (2001) Region-based image watermarking. IEEE Trans Image Process 10(11):1726–1740

    Article  Google Scholar 

  21. Pai Y-T, Lee L-T, Ruan S-J (2011) DS-CDMA-based watermarking: a low-power, high-security algorithm for embedded systems. International Journal of Innovative Computing Information and Control 7(10):5893–5908

    Google Scholar 

  22. Patil P, Bormane D (2013). DWT based invisible watermarking technique for digital images. International Journal of Engineering and Advanced Technology (IJEAT) ISSN 2249

  23. Samee MK, Götze J (2013) CDMA based reversible and blind watermarking scheme for images. International Journal of Future Computer and Communication 2(2):138

    Article  Google Scholar 

  24. Sarker MIH, Khan MI (2013) An efficient image watermarking scheme using BFS technique based on hadamard transform. SmartCR 3(5):298–308

    Article  Google Scholar 

  25. Shaamala A, Abdullah SM, Manaf AA (2011) Study of the effect DCT and DWT domains on the imperceptibility and robustness of genetic watermarking. International Journal of Computer Science Issues (IJCSI) 8(5):220

    Google Scholar 

  26. Tsai H-H, Jhuang Y-J, Lai Y-S (2012) An SVD-based image watermarking in wavelet domain using SVR and PSO. Appl Soft Comput 12(8):2442–2453

    Article  Google Scholar 

  27. Tsai H-H, Liu C-C (2011) Wavelet-based image watermarking with visibility range estimation based on HVS and neural networks. Pattern Recogn 44(4):751–763

    Article  MathSciNet  Google Scholar 

  28. Tsui TK, Zhang X-P, Androutsos D (2008) Color image watermarking using multidimensional Fourier transforms. IEEE Transactions on Information Forensics and security 3(1):16–28

    Article  Google Scholar 

  29. USC-SIPI image database website. n.d. http://sipi.usc.edu/database/database.php.

  30. Vahedi E, Lucas C, Zoroofi RA, Shiva M (2007). A bio-inspired content adaptive approach for multiresolution-based image watermarking. In: Natural Computation, 2007. ICNC. Third international conference on, 2007. IEEE, pp 58–62

  31. Vahedi E, Lucas C, Zoroofi RA, Shiva M (2007). A new approach for image watermarking by using particle swarm optimization. In: Signal Processing and Communications, 2007. ICSPC 2007. IEEE international conference on, IEEE, pp 1383–1386

  32. Vahedi E, Zoroofi RA, Shiva M (2007). On optimal color coordinate selection for wavelet-based color image watermarking. In: Intelligent and Advanced Systems, 2007. ICIAS 2007. International conference on, IEEE, pp 635–640

  33. Verma VS, Jha RK, Ojha A (2015) Digital watermark extraction using support vector machine with principal component analysis based feature reduction. J Vis Commun Image Represent 31:75–85

    Article  Google Scholar 

  34. Viswanatham VM, Reddy GS, Jagadeesh P (2012). A hybrid digital watermarking algorithm for color images based on DWT and DCT. Anale Seria Informatică 10 (2)

  35. Wang X, Shi Q, Wang S, Yang H (2016) A blind robust digital watermarking using invariant exponent moments. AEU-International Journal of Electronics and Communications 70(4):416–426

    Article  Google Scholar 

  36. Wang J, Yaojin L, Wang Y (2014). Blind watermarking scheme based on support vector machine and singular value decomposition. Computer science:212–215

  37. Wu H-T, Huang J (2012) Reversible image watermarking on prediction errors by efficient histogram modification. Signal Process 92(12):3000–3009

    Article  Google Scholar 

  38. Yadav AK, Mehta R, Kumar R, Vishwakarma VP (2016) Lagrangian twin support vector regression and genetic algorithm based robust grayscale image watermarking. Multimed Tools Appl 75(15):9371–9394

    Article  Google Scholar 

  39. Yassin NI, Salem NM, El Adawy MI (2014) QIM blind video watermarking scheme based on wavelet transform and principal component analysis. Alexandria Engineering Journal 53(4):833–842

    Article  Google Scholar 

  40. Yu J, Zhang B, Kuang Z, Lin D, Fan J (2017) iPrivacy: image privacy protection by identifying sensitive objects via deep multi-task learning. IEEE Transactions on Information Forensics and Security 12(5):1005–1016

    Article  Google Scholar 

  41. Zhang J, Gu Z, Jang J, Wu H, Stoecklin MP, Huang H, Molloy I (2018), Protecting intellectual property of deep neural networks with watermarking. In: Proceedings of the 2018 on Asia Conference on Computer and Communications Security, ACM, pp 159–172

  42. Zhou X, Cao C, Ma J, Wang L (2018). Adaptive digital watermarking scheme based on support vector machines and optimized genetic algorithm mathematical problems in engineering 2018

Download references

Author information

Authors and Affiliations

  1. Systems & Information Department, Engineering Division, National Research Centre, Dokki, Cairo, 12311, Egypt

    Enas M. F. El Houby & Nisreen I. R. Yassin

Authors
  1. Enas M. F. El Houby
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nisreen I. R. Yassin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nisreen I. R. Yassin.

Ethics declarations

Conflict of interests

All authors declare that they have no conflict of interest.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

El Houby, E.M.F., Yassin, N.I.R. Wavelet-Hadamard based blind image watermarking using genetic algorithm and decision tree. Multimed Tools Appl 79, 28453–28474 (2020). https://doi.org/10.1007/s11042-020-09333-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-020-09333-3

Keywords

Search

Navigation