Multimedia Tools and Applications

, Volume 76, Issue 6, pp 8695–8710 | Cite as

Robust image watermarking technique using triangular regions and Zernike moments for quantization based embedding

Article

Abstract

Watermarking is a tool to embed information in the image to provide authentication, copyrights protection, copy control, etc. Some watermarking techniques are robust to intentional /unintentional attacks on the watermarked image. In this study, we propose a robust watermarking approach that can resist geometrical attacks. The proposed technique exploits both the robust image feature points and local Zernike moments for embedding the information. Delaunay tessellation is employed to divide image into distinct triangular segments based on robust features. These features are identified using Harris detector. Zernike moments are calculated for each selected triangular segment, and then the watermark is embedded in the magnitude of Zernike moments using dither modulation. It can be observed from the experimental results that by using proposed approach, the watermark can be detected even in the presence of geometrical distortion, i.e. rotation, cropping, and scaling, and JPEG compression attack.

Keywords

Robust watermarking Zernike moments Feature points Geometric attacks 

References

  1. 1.
    Bas P, Chassery J-M, Macq B (2002) Geometrically invariant watermarking using feature points. IEEE Trans Image Process 11:1014–28. doi:10.1109/TIP.2002.801587 CrossRefGoogle Scholar
  2. 2.
    Chamlawi R, Khan A, Usman I (2010) Authentication and recovery of images using multiple watermarks. Comput Electr Eng 36:578–584CrossRefMATHGoogle Scholar
  3. 3.
    Cox IJ, Miller ML, Bloom JA et al (2008) Digital watermarking and steganography, 2nd ed. Morgan KaufmannGoogle Scholar
  4. 4.
    Das C, Panigrahi S, Sharma VK, Mahapatra KK (2014) A novel blind robust image watermarking in DCT domain usinginter-block coefficient correlation. Int J Electron Commun 68:244–253CrossRefGoogle Scholar
  5. 5.
    Kodak Lossless True Color Image Suite. http://r0k.us/graphics/kodak/
  6. 6.
    Lee H-Y, Lee C, Lee H-K (2007) Geometrically invariant watermarking: synchronization through circular Hough transform. Multimed Tools Appl 34:337–353. doi:10.1007/s11042-007-0112-0 CrossRefGoogle Scholar
  7. 7.
    Lee DT, Schachter BJ (1980) Two algorithms for constructing a Delaunay triangulation. Int J Comput Inf Sci 9:219–242MathSciNetCrossRefMATHGoogle Scholar
  8. 8.
    Lian S, Chen X, Wang J (2010) Content distribution and copyright authentication based on combined indexing and watermarking. Multimed Tools Appl 57:49–66. doi:10.1007/s11042-010-0521-3 CrossRefGoogle Scholar
  9. 9.
    Lin S, Costello D (2004) Error control coding. Prentice HallGoogle Scholar
  10. 10.
    Lu W, Sun W, Lu H (2011) Novel robust image watermarking based on subsampling and DWT. Multimed Tools Appl 60:31–46. doi:10.1007/s11042-011-0794-1 CrossRefGoogle Scholar
  11. 11.
    Luo H, Sun X, Yang H, Xia Z (2011) A robust image watermarking based on image restoration using SIFT. Radio Eng 20:525–532Google Scholar
  12. 12.
    Mair E, Hager GD, Burschka D et al (2010) Adaptive and generic corner detection based on the accelerated segment test. Comput Vis – ECCV 6312:183–196Google Scholar
  13. 13.
    Schmidt A, Kraft M, Kasinski A (2010) An evaluation of image feature detectors and descriptors for robot navigation. In: Comput. Vis. Graph. Springer, BerlinCrossRefGoogle Scholar
  14. 14.
    Seo JS, Yoo CD (2006) Image watermarking based on invariant regions of scale-space representation. IEEE Trans Signal Process 54:218–238Google Scholar
  15. 15.
    Singhal N, Lee Y, Kim C, Lee S (2009) Robust image watermarking using local Zernike moments. J Vis Commun Image Represent 20:408–419. doi:10.1016/j.jvcir.2009.04.002 CrossRefGoogle Scholar
  16. 16.
    Tang C-W, Hang H-M (2003) A feature-based robust digital image watermarking scheme. IEEE Trans Signal Process 51:950–959MathSciNetCrossRefGoogle Scholar
  17. 17.
    Tao H, Chongmin L, Zain JM, Abdalla AN (2014) Robust image watermarking theories and techniques: a review. J Appl Res Technol 12:122–138CrossRefGoogle Scholar
  18. 18.
    Usman I, Khan A (2010) BCH coding and intelligent watermark embedding: employing both frequency and strength selection. Appl Soft Comput 10:332–343CrossRefGoogle Scholar
  19. 19.
    Wang X-Y, Yang Y-P, Yang H-Y (2010) Invariant image watermarking using multi-scale Harris detector and wavelet moments. Comput Electr Eng 36:31–44CrossRefMATHGoogle Scholar
  20. 20.
    Xin Y, Liao S, Pawlak M (2004) A multibit geometrically robust image watermark based on Zernike moments. In: IEEE Int. Conf. Pattern Recognit. pp 218–238Google Scholar
  21. 21.
    Zhou J, Pang M (2010) Digital watermark for printed materials. In: IEEE Int. Conf. Netw. Infrastruct. Digit. Content. pp 758–762Google Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Pattern Recognition Lab, Department of Computer and Information Sciences, PIEASIslamabadPakistan

Personalised recommendations