An Image Data Hiding Scheme Based on Vector Quantization and Graph Coloring

  • Shuai Yue
  • Zhi-Hui Wang
  • Chin-Chen Chang
Part of the Intelligent Systems Reference Library book series (ISRL, volume 40)


Vector quantization, i.e., VQ, is an important image compression method. In the past, many data hiding schemes have been proposed based on VQ. However, none of them is graph coloring based, although graph coloring has been used in many applications. In this work, we propose a VQ-based data hiding scheme using graph coloring. The proposed scheme colored every codeword in the codebook in different colors, each of which represents some bits of secret messages. Then the scheme hidden data into the compression code through replacing one codeword in a color with another codeword in another color. The performance of the proposed scheme was evaluated on the basis of embedding capacity and imperceptibility, which proved the scheme’s validity.


Particle Swarm Optimization Particle Swarm Optimization Algorithm Cover Image Vector Quantization Secret Message 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Duric, Z., Jacobs, M., Jajodia, S.: Information hiding: Steganography and steganalysis. Handbook of Statistics 24, 171–187 (2005)CrossRefGoogle Scholar
  2. 2.
    Tefas, A., Nikolaidis, N., Pitas, I.: Image watermarking: Techniques and applications. The Essential Guide to Image Processing 22, 597–648 (2009)CrossRefGoogle Scholar
  3. 3.
    Lin, Y.C., Wang, C.C.: Digital images watermarking by vector quantization. Optical Engineering 3, 76–78 (1999)Google Scholar
  4. 4.
    Wu, H.C., Wu, N.I., Tsai, C.S., Hwang, M.S.: Image steganographic scheme based on pixel-value differencing and lsb replacement methods. Vision, Image and Signal Processing 152, 611–615 (2005)CrossRefGoogle Scholar
  5. 5.
    Li, Y., Li, C.T.: Steganographic scheme for vq compressed images using progressive exponential clustering. In: Proc. IEEE Int’l. Conf. Video and Signal Based Surveillance, p. 85 (2006)Google Scholar
  6. 6.
    Cosman, P.C., Oehler, K.L., Riskin, E.A., Gray, R.M.: Using vector quantization for image processing. Proceedings of the IEEE 81, 1326–1341 (1993)CrossRefGoogle Scholar
  7. 7.
    Yanez, J., Ramirez, J.: The robust coloring problem. European Journal of Operational Research 148, 546–558 (2003)MathSciNetzbMATHCrossRefGoogle Scholar
  8. 8.
    Guruswami, V., Khanna, S.: On the hardness of 4-coloring a 3-collorable graph. In: Proc. 15th Annual IEEE Conf. Computational Complexity, pp. 188–197 (2000)Google Scholar
  9. 9.
    Cui, G., Qi, L., Liu, S., Wang, Y., Zhang, X., Cao, X.: Modified PSO algorithm for solving planar graph coloring problem. Progress in Natural Science 18, 353–357 (2008)CrossRefGoogle Scholar
  10. 10.
    Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proc. IEEE Int’l Conf. Neural Networks, vol. 4, pp. 1942–1948 (1995)Google Scholar
  11. 11.

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of SoftwareDalian University of TechnologyDaLianChina
  2. 2.Department of Information Engineering and Computer ScienceFeng Chia UniversityTaichungTaiwan

Personalised recommendations