Improved Algorithms for Robust Histogram Shape-Based Image Watermarking

  • Bingwen Feng
  • Jian WengEmail author
  • Wei Lu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10431)


In histogram shape-based watermarking schemes, watermark bits are embedded by altering the shape of a histogram extracted from the host image. Exited embedding algorithms use a group of histogram bins to embed only one watermark bit, which results in a rather low watermark capacity. In this paper, we improve the embedding algorithm in two new ways. The first proposed algorithm performs multi-round embedding to carry more watermark bits. In each round of embedding, a specified histogram is extracted so that the embedding operation does not affect watermark bits embedded in previous rounds. The second proposed algorithm uses a group of histogram bins to embed more than one watermark bits, where the coefficient transferring is optimized to minimize the embedding distortion. These algorithms can effectively enlarge the capacity. Furthermore, a histogram preadjustment method, together with a refined coefficient transferring method, is introduced. As a result, reasonable performances on robustness and watermarked image quality are available. The proposed algorithms provide various tradeoff among capacity, robustness, and perceptibility, which supports a wide range of applications.


Blind watermarking Robustness Multilevel histogram Multiple histogram adjustment 



This work was supported by National Science Foundation of China (Grant Nos. 61472165 and 61373158), Guangdong Provincial Engineering Technology Research Center on Network Security Detection and Defence (Grant No. 2014B090904067), Guangdong Provincial Special Funds for Applied Technology Research and development and Transformation of Important Scientific and Technological Achieve (Grant No. 2016B010124009), the Zhuhai Top Discipline–Information Security, Guangzhou Key Laboratory of Data Security and Privacy Preserving, Guangdong Key Laboratory of Data Security and Privacy Preserving.


  1. 1.
    Ni, J., Zhang, R., Huang, J., Wang, C., Li, Q.: A rotation-invariant secure image watermarking algorithm incorporating steerable pyramid transform. In: Shi, Y.Q., Jeon, B. (eds.) IWDW 2006. LNCS, vol. 4283, pp. 446–460. Springer, Heidelberg (2006). doi: 10.1007/11922841_36 CrossRefGoogle Scholar
  2. 2.
    Dugelay, J.L., Roche, S., Rey, C., Doërr, G.: Still-image watermarking robust to local geometric distortions. IEEE Trans. Image Process. 15(9), 2831–2842 (2006)CrossRefGoogle Scholar
  3. 3.
    Su, P.C., Chang, Y.C., Wu, C.Y.: Geometrically resilient digital image watermarking by using interest point extraction and extended pilot signals. IEEE Trans. Inf. Forensics Secur. 8(12), 1897–1908 (2013)CrossRefGoogle Scholar
  4. 4.
    Gao, X., Deng, C., Li, X., Tao, D.: Geometric distortion insensitive image watermarking in affine covariant regions. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 40(3), 278–286 (2010)CrossRefGoogle Scholar
  5. 5.
    Deng, C., Gao, X., Li, X., Tao, D.: Local histogram based geometric invariant image watermarking. Sig. Process. 90(12), 3256–3264 (2010)CrossRefzbMATHGoogle Scholar
  6. 6.
    Licks, V., Jordan, R.: Geometric attacks on image watermarking systems. IEEE Multimed. 3, 68–78 (2005)CrossRefGoogle Scholar
  7. 7.
    Ruanaidh, J.J.O., Pun, T.: Rotation, scale and translation invariant spread spectrum digital image watermarking. Sig. Process. 66(3), 303–317 (1998)CrossRefzbMATHGoogle Scholar
  8. 8.
    Zhang, H., Shu, H., Coatrieux, G., Zhu, J., Wu, Q.J., Zhang, Y., Zhu, H., Luo, L.: Affine legendre moment invariants for image watermarking robust to geometric distortions. IEEE Trans. Image Process. 20(8), 2189–2199 (2011)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Kang, X., Huang, J., Zeng, W.: Efficient general print-scanning resilient data hiding based on uniform log-polar mapping. IEEE Trans. Inf. Forensics Secur. 5(1), 1–12 (2010)CrossRefGoogle Scholar
  10. 10.
    Li, L., Li, S., Abraham, A., Pan, J.S.: Geometrically invariant image watermarking using polar harmonic transforms. Inf. Sci. 199, 1–19 (2012)MathSciNetCrossRefzbMATHGoogle Scholar
  11. 11.
    Xiang, S., Kim, H.J., Huang, J.: Invariant image watermarking based on statistical features in the low-frequency domain. IEEE Trans. Circuits Syst. Video Technol. 18(6), 777–790 (2008)CrossRefGoogle Scholar
  12. 12.
    He, X., Zhu, T., Yang, G.: A geometrical attack resistant image watermarking algorithm based on histogram modification. Multidimension. Syst. Sig. Process. 26(1), 291–306 (2015)MathSciNetCrossRefGoogle Scholar
  13. 13.
    Zong, T., Xiang, Y., Natgunanathan, I., Guo, S., Zhou, W., Beliakov, G.: Robust histogram shape-based method for image watermarking. IEEE Trans. Circuits Syst. Video Technol. 25(5), 717–729 (2015)CrossRefGoogle Scholar
  14. 14.
    Bas, P., Furon, T.: BOWS-2 (2007).
  15. 15.
    Pereira, S., Voloshynovskiy, S., Madueno, M., Marchand-Maillet, S., Pun, T.: Second generation benchmarking and application oriented evaluation. In: Moskowitz, I.S. (ed.) IH 2001. LNCS, vol. 2137, pp. 340–353. Springer, Heidelberg (2001). doi: 10.1007/3-540-45496-9_25 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.College of Information Science and TechnologyJinan UniversityGuangzhouChina
  2. 2.School of Data and Computer Science, Guangdong Key Laboratory of Information Security TechnologySun Yat-sen UniversityGuangzhouChina

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