Neural Computing and Applications

, Volume 32, Issue 5, pp 1379–1403 | Cite as

SVM-based robust image watermarking technique in LWT domain using different sub-bands

  • Mohiul Islam
  • Amarjit Roy
  • Rabul Hussain LaskarEmail author
Original Article


In this paper, a robust image watermarking system in lifting wavelet transform domain using different sub-bands has been proposed. SVM classifier is used during watermark extraction to obtain improved robustness under diverse attack conditions. In this work, a detailed analysis of imperceptibility and robustness performance with the use of different sub-bands has been presented. The performance on different sub-band has been analyzed so as to maximize the robustness against different attacks keeping imperceptibility at adequate level. Robustness is observed against various attacks such as noising attacks, denoising attacks, image processing attacks, lossy compression attacks and geometric attacks. It is seen that high-frequency sub-band provides better invisibility, whereas variation of robustness performance on different sub-bands depend on the type of attacks. It is observed from the performance analysis that all the attacks do not have exactly same effect on the frequency content of the image. For instance, noising attack affects every frequency component of the image almost equally, whereas the embedding in high-frequency band makes the system fragile to lossy compression attack. The algorithm is tested on a large image database to observe the variation in the performance of the system. Comparative analysis suggests that the proposed sub-band provides improved performance over some benchmark methods in most of the cases.


Image watermarking Lifting wavelet transform (LWT) Support vector machine (SVM) Watermarking attacks 



The authors would like to acknowledge all the members of Speech and Image Processing Laboratory, Department of Electronics and Communication Engineering, National Institute of Technology Silchar, India, for providing support and necessary facilities for carrying out this work. The authors would like to thank the editor and the anonymous reviewers for their valuable comments and suggestions to improve the quality of this paper.

Compliance with ethical standards

Conflict of interest

The authors declare that there is no conflict of interests regarding the publication of this paper.


  1. 1.
    Cox IJ, Miller ML, Bloom JA, Honsinger C (2002) Digital watermarking, vol 1558607145. Morgan Kaufmann, San FranciscoGoogle Scholar
  2. 2.
    Potdar VM, Han S, Chang E (2005) A survey of digital image watermarking techniques. In: 2005 3rd IEEE international conference on industrial informatics. INDIN’05. IEEE, pp 709–716Google Scholar
  3. 3.
    Zhang F, Zhang X, Shang D (2012) Digital watermarking algorithm based on Kalman filtering and image fusion. Neural Comput Appl 21(6):1149–1157Google Scholar
  4. 4.
    Chaudhary A, Vasavada J, Raheja JL, Kumar S, Sharma M (2012) A hash based approach for secure keyless steganography in lossless RGB images. In: The 22nd international conference on computer graphics and vision, Russia, MoscowGoogle Scholar
  5. 5.
    Batool SI, Shah T, Khan M (2014) A color image watermarking scheme based on affine transformation and S4 permutation. Neural Comput Appl 25(7–8):2037–2045Google Scholar
  6. 6.
    Khan M, Shah T (2015) A copyright protection using watermarking scheme based on nonlinear permutation and its quality metrics. Neural Comput Appl 26(4):845–855Google Scholar
  7. 7.
    Hsieh MS, Tseng DC, Huang YH (2001) Hiding digital watermarks using multiresolution wavelet transform. IEEE Trans Ind Electron 48(5):875–882Google Scholar
  8. 8.
    Chen YH, Huang HC (2015) Coevolutionary genetic watermarking for owner identification. Neural Comput Appl 26(2):291–298Google Scholar
  9. 9.
    Loukhaoukha K, Chouinard JY (2009) Hybrid watermarking algorithm based on SVD and lifting wavelet transform for ownership verification. In: 11th Canadian workshop on information theory. CWIT 2009. IEEE, pp. 177–182Google Scholar
  10. 10.
    Verma VS, Jha RK (2015) Improved watermarking technique based on significant difference of lifting wavelet coefficients. SIViP 9(6):1443–1450Google Scholar
  11. 11.
    Hsu LY, Hu HT (2015) Blind image watermarking via exploitation of inter-block prediction and visibility threshold in DCT domain. J Vis Commun Image Represent 32:130–143Google Scholar
  12. 12.
    Lin SD, Shie SC, Guo JY (2010) Improving the robustness of DCT-based image watermarking against JPEG compression. Comput Stand Interfaces 32(1):54–60Google Scholar
  13. 13.
    Tsui TK, Zhang XP, Androutsos D (2008) Color image watermarking using multidimensional Fourier transforms. IEEE Trans Inf Forensics Secur 3(1):16–28Google Scholar
  14. 14.
    Poljicak A, Mandic L, Agic D (2011) Discrete Fourier transform–based watermarking method with an optimal implementation radius. J Electron Imaging 20(3):033008-033008Google Scholar
  15. 15.
    Chakraborty S, Chatterjee S, Dey N, Ashour AS (2017) Comparative approach between singular value decomposition and randomized singular value decomposition-based watermarking. In: Dey N, Santhi V (eds) Intelligent techniques in signal processing for multimedia security. Springer, Berlin, pp 133–149Google Scholar
  16. 16.
    Lai CC (2011) A digital watermarking scheme based on singular value decomposition and tiny genetic algorithm. Digit Signal Proc 21(4):522–527Google Scholar
  17. 17.
    Soliman MM, Hassanien AE, Onsi HM (2016) An adaptive watermarking approach based on weighted quantum particle swarm optimization. Neural Comput Appl 27(2):469–481Google Scholar
  18. 18.
    Lai CC, Tsai CC (2010) Digital image watermarking using discrete wavelet transform and singular value decomposition. IEEE Trans Instrum Meas 59(11):3060–3063Google Scholar
  19. 19.
    Makbol NM, Khoo BE (2013) Robust blind image watermarking scheme based on redundant discrete wavelet transform and singular value decomposition. AEU Int J Electron Commun 67(2):102–112Google Scholar
  20. 20.
    Dey N, Biswas D, Roy AB, Das A, Chaudhuri SS (2012) DWT-DCT-SVD based blind watermarking technique of gray image in electrooculogram signal. In: 2012 12th international conference on intelligent systems design and applications (ISDA). IEEE, pp 680–685Google Scholar
  21. 21.
    Mohammad AA, Alhaj A, Shaltaf S (2008) An improved SVD-based watermarking scheme for protecting rightful ownership. Signal Process 88(9):2158–2180zbMATHGoogle Scholar
  22. 22.
    Su Q, Niu Y, Zhao Y, Pang S, Liu X (2013) A dual color images watermarking scheme based on the optimized compensation of singular value decomposition. AEU Int J Electron Commun 67(8):652–664Google Scholar
  23. 23.
    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 31:75–85Google Scholar
  24. 24.
    Bhatnagar G (2012) A new facet in robust digital watermarking framework. AEU Int J Electron Commun 66(4):275–285Google Scholar
  25. 25.
    Guo J, Zheng P, Huang J (2015) Secure watermarking scheme against watermark attacks in the encrypted domain. J Vis Commun Image Represent 30:125–135Google Scholar
  26. 26.
    Ramanjaneyulu K, Rajarajeswari K (2012) Wavelet-based oblivious image watermarking scheme using genetic algorithm. IET Image Process 6(4):364–373MathSciNetGoogle Scholar
  27. 27.
    Song C, Sudirman S, Merabti M (2012) A robust region-adaptive dual image watermarking technique. J Vis Commun Image Represent 23(3):549–568Google Scholar
  28. 28.
    Ali M, Ahn CW, Siarry P (2014) Differential evolution algorithm for the selection of optimal scaling factors in image watermarking. Eng Appl Artif Intell 31:15–26Google Scholar
  29. 29.
    Ouhsain M, Hamza AB (2009) Image watermarking scheme using nonnegative matrix factorization and wavelet transform. Expert Syst Appl 36(2):2123–2129Google Scholar
  30. 30.
    Bhatnagar G, Wu QJ (2013) Biometrics inspired watermarking based on a fractional dual tree complex wavelet transform. Future Gener Comput Syst 29(1):182–195Google Scholar
  31. 31.
    Bhatnagar G, Wu QJ, Raman B (2012) A new robust adjustable logo watermarking scheme. Comput Secur 31(1):40–58Google Scholar
  32. 32.
    Rastegar S, Namazi F, Yaghmaie K, Aliabadian A (2011) Hybrid watermarking algorithm based on singular value decomposition and radon transform. AEU Int J Electron Commun 65(7):658–663Google Scholar
  33. 33.
    Roy A, Singha J, Devi SS, Laskar RH (2016) Impulse noise removal using SVM classification based fuzzy filter from gray scale images. Signal Process 128:262–273Google Scholar
  34. 34.
    Sun L, Xu J, Liu S, Zhang S, Li Y, Shen CA (2016) A robust image watermarking scheme using Arnold transform and BP neural network. Neural Comput Appl. CrossRefGoogle Scholar
  35. 35.
    Roy A, Laskar RH (2016) Multiclass SVM based adaptive filter for removal of high density impulse noise from color images. Appl Soft Comput 46:816–826Google Scholar
  36. 36.
    Tsai HH, Sun DW (2007) Color image watermark extraction based on support vector machines. Inf Sci 177(2):550–569Google Scholar
  37. 37.
    Peng H, Wang J, Wang W (2010) Image watermarking method in multiwavelet domain based on support vector machines. J Syst Softw 83(8):1470–1477Google Scholar
  38. 38.
    Wang XY, Miao EN, Yang HY (2012) A new SVM-based image watermarking using Gaussian-Hermite moments. Appl Soft Comput 12(2):887–903Google Scholar
  39. 39.
  40. 40.
    Singha J, Laskar RH (2017) Hand gesture recognition using two-level speed normalization, feature selection and classifier fusion. Multimed Syst 23(4):499–514Google Scholar
  41. 41.
    Verma VS, Jha RK, Ojha A (2015) Significant region based robust watermarking scheme in lifting wavelet transform domain. Expert Syst Appl 42(21):8184–8197Google Scholar
  42. 42.
    Wang XY, Liu YN, Xu H, Wang AL, Yang HY (2016) Blind optimum detector for robust image watermarking in nonsubsampled shearlet Domain. Inf Sci 372:634–654Google Scholar
  43. 43.
    Hamghalam M, Mirzakuchaki S, Akhaee MA (2014) Geometric modelling of the wavelet coefficients for image watermarking using optimum detector. IET Image Process 8(3):162–172Google Scholar
  44. 44.
    Kasana G, Kasana SS (2017) Reference based semi blind image watermarking scheme in wavelet domain. Opt Int J Light Electron Opt 142:191–204Google Scholar
  45. 45.
    Islam M, Laskar RH (2018) Geometric distortion correction based robust watermarking scheme in LWT-SVD domain with digital watermark extraction using SVM. Multimed Tools Appl 77(11):14407–14434. CrossRefGoogle Scholar
  46. 46.
    Singh D, Singh SK (2016) DWT-SVD and DCT based robust and blind watermarking scheme for copyright protection. Multimed Tools Appl 76(11):13001–13024Google Scholar
  47. 47.
    Mehta R, Rajpal N, Vishwakarma VP (2016) LWT-QR decomposition based robust and efficient image watermarking scheme using Lagrangian SVR. Multimed Tools Appl 75(7):4129–4150Google Scholar
  48. 48.
    Yang HY, Wang XY, Wang CP (2013) A robust digital watermarking algorithm in undecimated discrete wavelet transform domain. Comput Electr Eng 39(3):893–906Google Scholar

Copyright information

© The Natural Computing Applications Forum 2018

Authors and Affiliations

  • Mohiul Islam
    • 1
  • Amarjit Roy
    • 1
  • Rabul Hussain Laskar
    • 1
    Email author
  1. 1.Department of ECENIT SilcharSilcharIndia

Personalised recommendations