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A Fast and Robust Image Watermarking Scheme Using Improved Singular Value Decomposition

  • Conference paper
Intelligent Information and Database Systems (ACIIDS 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9621))

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Abstract

With the popularity of editing software and the Internet, digital content can easily be manipulated and distributed. Therefore, illegal reproduction of digital products became a real problem. Watermarking has been considered as an effective solution for copyright protection and authentication. However, watermarking schemes usually have encountered some difficulties, such as computational complexity, imperceptibility and robustness. In this paper, based on improved singular value decomposition (SVD), we proposed a new image watermarking scheme in order to reduce the computational complexity. To this end, we designed an algorithm to directly compute the largest eigenvalues and eigenvectors of the analyzed image segmented blocks. Moreover, an adaptive embedding technique was utilized to improve the robustness of the proposed scheme. Experimental results showed that the scheme is fast and good for digital image watermarking and it outperforms several widely used schemes in terms of robustness and imperceptibility.

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References

  1. Sun, R., Sun, H., Yao, T.: A SVD and quantization based semi-fragile watermarking technique for image authentication. In: Proceedings of International Conference on Signal Processing, pp. 1952–1955 (2002)

    Google Scholar 

  2. Bhatnagar, G., Raman, B.: A new robust reference watermarking scheme based on DWT-SVD. Comput. Stand. Interfaces 31(5), 1002–1013 (2009)

    Article  Google Scholar 

  3. Chang, C.C., Tsai, P., Lin, C.C.: SVD-based digital image watermarking scheme. Pattern Recogn. Lett. 26(10), 1577–1586 (2005)

    Article  Google Scholar 

  4. Chen, H., Zhu, Y.: A robust watermarking algorithm based on QR factorization and DCT using quantization index modulation technique. J. Zhejiang Univ. 13(8), 573–584 (2012)

    Article  Google Scholar 

  5. Chung, K.L., Yang, W.N., Huang, Y.H., Wu, S.T., Hsu, Y.C.: SVD-based watermarking algorithm. Appl. Math. Comput. 188(1), 54–57 (2007)

    MathSciNet  MATH  Google Scholar 

  6. Fei, C., Kwong, R., Kundur, D.: Secure semi-fragile watermarking for image authentication. In: IEEE WIFS, pp. 141–145 (2009)

    Google Scholar 

  7. Arathi, C.: A semi fragile image watermarking technique using block based SVD. Int. J. Comput. Sci. Inf. Technol. 3(2), 3644–3647 (2012)

    Google Scholar 

  8. Gokhale, U.M., Joshi, Y.V.: A semi fragile watermarking algorithm based on SVD-IWT for image authentication. Int. J. Adv. Res. Comput. Commun. Eng. 1(4) (2012). ISSN-2278-1021

    Google Scholar 

  9. Lai, C.C.: An improved SVD-based watermarking scheme using visual characteristics. Optics Commun. 284(4), 938–944 (2012)

    Article  Google Scholar 

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

    Article  Google Scholar 

  11. Bao, P., Ma, X.: Image adaptive watermarking using wavelet domain SVD. IEEE Trans. Circ. Syst. Video Technol. 15(1), 96–102 (2005)

    Article  Google Scholar 

  12. Sun, X., Liu, J., Sun, J., Zhang, Q., Ji, W.: A robust image watermarking scheme based on the relationship of SVD. In: Proceedings of International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIHMSP 2008), Harbin, pp. 731–734 (2008)

    Google Scholar 

  13. Zhu, X., Zhao, J., Xu, H.: A digital watermarking algorithm and implementation based on improved SVD. In: Proceedings of 18th International Conference on Pattern Recognition (ICPR 2006), vol. 3, Hong Kong, pp. 651–656 (2006)

    Google Scholar 

  14. At, P.V.: Determination of the largest characteristic number and the corresponding eigenvector of a nonnegative matrix. USSR Comput. Math. Math. Phys 21(4), 1–19 (1982)

    MathSciNet  Google Scholar 

  15. Golub, G.H., Loan, C.F.V.: Matrix Computations. Johns Hopkins University Press, Baltimore (1996)

    MATH  Google Scholar 

  16. Mohan, B.C., Kumar, S.S.: A robust image watermarking scheme using singular value decomposition. J. Multimedia 3(1), 7–15 (2008)

    Article  Google Scholar 

  17. Shieh, J.M., Lou, D.C., Chang, M.C.: A semi-blind digital watermarking scheme based on singular value decomposition. Comput. Stand. Interfaces 28, 428–440 (2006)

    Article  Google Scholar 

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Correspondence to Nguyen Hieu Cuong .

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Luyen, C.T., Cuong, N.H., At, P.V. (2016). A Fast and Robust Image Watermarking Scheme Using Improved Singular Value Decomposition. In: Nguyen, N.T., Trawiński, B., Fujita, H., Hong, TP. (eds) Intelligent Information and Database Systems. ACIIDS 2016. Lecture Notes in Computer Science(), vol 9621. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49381-6_75

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  • DOI: https://doi.org/10.1007/978-3-662-49381-6_75

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-49380-9

  • Online ISBN: 978-3-662-49381-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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