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Optimization of Scaling Factors for Image Watermarking Using Harmony Search Algorithm

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Computational Science and Its Applications – ICCSA 2018 (ICCSA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10963))

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Abstract

We propose a novel watermarking scheme for images which optimizes the watermarking strength using Harmony Search Algorithm (HSA). The optimized watermarking scheme is based on the discrete wavelet transform (DWT) and singular value decomposition (SVD). The amount of modification made in the coefficients of the LL3 sub band of the host image depends on the values obtained by the Harmony Search algorithm. For optimization of scaling factors, HSA uses an objective function which is a linear combination of imperceptibility and robustness. The PSNR and SSIM values show that the visual quality of the signed and attacked images is good. The proposed scheme is robust against common image processing operations. It is concluded that the embedding and extraction of the proposed algorithm is well optimized, robust and show an improvement over other similar reported methods.

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References

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

    Article  Google Scholar 

  2. Mishra, A., Goel, A., Singh, R., Chetty, G., Singh, L.: A novel image watermarking scheme using extreme learning machine. In: Proceedings of the IEEE World Congress on Computational Intelligence, pp. 1–6 (2012)

    Google Scholar 

  3. Motwani, M.C., Motwani, R.C., Harris Jr., F.C.: Wavelet based fuzzy perceptual mask for images. In: Proceedings of IEEE International Conference on Image Processing (ICIP 2009), Cairo, Egypt (2009)

    Google Scholar 

  4. Motwani, M.C., Harris Jr., F.C.: Fuzzy perceptual watermarking for ownership verification. In: Proceedings of the International Conference on Image Processing, Computer Vision, and Pattern Recognition, Las Vegas, Nevada (2009)

    Google Scholar 

  5. Fındık, O., Babaoğlu, I., Ülker, E.: A color image watermarking scheme based on hybrid classification method: particle swarm optimization and k-nearest neighbor algorithm. Opt. Commun. 283(24), 4916–4922 (2010)

    Article  Google Scholar 

  6. Cox, I., Kilian, J., Leighton, F.T., Shamoon, T.: Secure spread spectrum watermarking for multimedia. IEEE Trans. Image Process. 6, 1673–1687 (1997)

    Article  Google Scholar 

  7. Run, R.-S., Horng, S.-J., Lai, J.-L., Kao, T.-W., Chen, R.-J.: An improved SVD-based watermarking technique for copyright protection. Expert Syst. Appl. 39, 673–689 (2012)

    Article  Google Scholar 

  8. Kumsawat, P., Attakitmongcol, K., Srikaew, A.: A new approach for optimization in image watermarking by using genetic algorithms. IEEE Trans. Sig. Process. 53(12), 4707–4719 (2005)

    Article  MathSciNet  Google Scholar 

  9. Lai, C.-C.: A digital watermarking scheme based on singular value decomposition and tiny genetic algorithm. Digital Sig. Process. 21, 522–527 (2011)

    Article  Google Scholar 

  10. Ishtiaq, M., Sikandar, B., Jaffar, A., Khan, A.: Adaptive watermark strength selection using particle swarm optimization. ICIC Express Lett. 4(5) (2010). ISSN: 1881-803X

    Google Scholar 

  11. Loukhaoukha, K., Chouinard, J.-Y., Taieb, M.H.: Optimal image watermarking algorithm based on LWT-SVD via multi-objective ant colony optimization. J. Inf. Hiding Multimedia Sig. Process. 2(4), 303–319 (2011)

    Google Scholar 

  12. Geem, Z.W., Kim, J.H., Loganathan, G.V.: A new heuristic optimization algorithm: harmony search. Simulation 76, 60–682 (2001)

    Article  Google Scholar 

  13. Lee, K.S., Geem, Z.W.: A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice. Comput. Methods Appl. Mech. Eng. 194, 3902–3933 (2005)

    Article  Google Scholar 

  14. Yang, X.S.: Nature-Inspired Metaheuristic Algorithms. Luniver Press, Bristol (2008)

    Google Scholar 

  15. Geem, Z.W.: Optimal cost design of water distribution networks using harmony search. Eng. Optim. 38, 259–280 (2006)

    Article  Google Scholar 

  16. Cuevas, E., Ortega-Sánchez, N., Zaldivar, D., Pérez-Cisneros, M.: Circle detection by harmony search optimization. J. Intell. Rob. Syst. Theory Appl. 66(3), 359–376 (2013)

    Article  Google Scholar 

  17. Mahdavi, M., Fesanghary, M., Damangir, E.: An improved harmony search algorithm for solving optimization problems. Appl. Math. Comput. 188, 1567–1579 (2007)

    MathSciNet  MATH  Google Scholar 

  18. Omran, M.G.H., Mahdavi, M.: Global-best harmony search. Appl. Math. Comput. 198, 643–656 (2008)

    MathSciNet  MATH  Google Scholar 

  19. Lee, K.S., Geem, Z.W.: A new meta-heuristic algorithm for continuous engineering optimization, harmony search theory and practice. Comput. Methods Appl. Mech. Eng. 194, 3902–3933 (2005)

    Article  Google Scholar 

  20. Lee, K.S., Geem, Z.W., Lee, S.H., Bae, K.-W.: The harmony search heuristic algorithm for discrete structural optimization. Eng. Optim. 37, 663–684 (2005)

    Article  MathSciNet  Google Scholar 

  21. Kim, J.H., Geem, Z.W., Kim, E.S.: Parameter estimation of the nonlinear Muskingum model using harmony search. J. Am. Water Resour. Assoc. 37, 1131–1138 (2001)

    Article  Google Scholar 

  22. Lee, K.S., Geem, Z.W.: A new structural optimization method based on the harmony search algorithm. Comput. Struct. 82, 781–798 (2004)

    Article  Google Scholar 

  23. Ayvaz, T.M.: Simultaneous determination of aquifer parameters and zone structures with fuzzy c-means clustering and meta-heuristic harmony search algorithm. Adv. Water Resour. 30, 2326–2338 (2007)

    Article  Google Scholar 

  24. Geem, Z.W., Lee, K.S., Park, Y.J.: Application of harmony search to vehicle routing. Am. J. Appl. Sci. 2, 1552–1557 (2005)

    Article  Google Scholar 

  25. Mishra, A., Agarwal, C., Sharma, A., Bedi, P.: Optimized gray-scale image watermarking using DWT-SVD and firefly algorithm. Expert Syst. Appl. 41, 7858–7867 (2014)

    Article  Google Scholar 

  26. Mishra, A., Agarwal, C.: Toward optimal watermarking of grayscale images using the multiple scaling factor–based cuckoo search technique. In: Bio-Inspired Computation and Applications in Image Processing, pp. 131–155. Elsevier (2016). https://doi.org/10.1016/B978-0-12-804536-7.00007-7

    Chapter  Google Scholar 

  27. Mishra, A., Rajpal, A., Bala, R.: Bi-directional extreme learning machine for semi-blind watermarking of compressed images. J. Inf. Secur. Appl. 38, 71–84 (2018)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Electronics, Deendayal Upadhyay College, University of Delhi, Delhi, India

    Anurag Mishra

  2. Department of Computer Science, University of Delhi, Delhi, India

    Charu Agarwal

  3. Faculty of ESTEM, University of Canberra, Canberra, Australia

    Girija Chetty

Authors
  1. Anurag Mishra
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  2. Charu Agarwal
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  3. Girija Chetty
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Corresponding author

Correspondence to Anurag Mishra .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. Saint Petersburg State University, Saint Petersburg, Russia

    Elena Stankova

  5. Polytechnic University of Bari, Bari, Italy

    Carmelo M. Torre

  6. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  7. Monash University, Clayton, Victoria, Australia

    David Taniar

  8. Kyushu Sangyo University, Fukuoka shi, Fukuoka, Japan

    Bernady O. Apduhan

  9. Politecnico di Bari, Bari, Italy

    Eufemia Tarantino

  10. Myongji University, Yongin, Korea (Republic of)

    Yeonseung Ryu

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Mishra, A., Agarwal, C., Chetty, G. (2018). Optimization of Scaling Factors for Image Watermarking Using Harmony Search Algorithm. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2018. ICCSA 2018. Lecture Notes in Computer Science(), vol 10963. Springer, Cham. https://doi.org/10.1007/978-3-319-95171-3_33

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  • DOI: https://doi.org/10.1007/978-3-319-95171-3_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-95170-6

  • Online ISBN: 978-3-319-95171-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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