Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30172
A Feature-based Invariant Watermarking Scheme Using Zernike Moments

Authors: Say Wei Foo, Qi Dong

Abstract:

In this paper, a novel feature-based image watermarking scheme is proposed. Zernike moments which have invariance properties are adopted in the scheme. In the proposed scheme, feature points are first extracted from host image and several circular patches centered on these points are generated. The patches are used as carriers of watermark information because they can be regenerated to locate watermark embedding positions even when watermarked images are severely distorted. Zernike transform is then applied to the patches to calculate local Zernike moments. Dither modulation is adopted to quantize the magnitudes of the Zernike moments followed by false alarm analysis. Experimental results show that quality degradation of watermarked image is visually transparent. The proposed scheme is very robust against image processing operations and geometric attacks.

Keywords: Image watermarking, Zernike moments, Featurepoint, Invariance, Robustness.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1061980

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1487

References:


[1] J. J. Ruanaidh, W. J. Dowling, and F. M. Boland, Watermarking digital images for copyright protection, in Proc. Inst. Elect. Eng., (1999), vol. 143, no. 4, pp. 250-256.
[2] M. Barni, I.J. Cox, T. Kalker, Digital watermarking, Fourth International Workshop on Digital Watermarking, Siena, Italy, 2005.
[3] M. Swanson, B. Zhu, and A. Tewfik, Transparent Robust Image Watermarking, Proc. IEEE Int. Conf. on Image Processing, (1998), vol. III, pp. 211-214.
[4] J.F. Liu, D. Huang, and J.W. Huang, Survey on watermarking against geometric attacks, J. Electron. Technol. (2004), 26 (9) 1495-1503.
[5] W. Bender, D. Gruhl, N. Morimoto, Techniques for data hiding, IBM System Journal 25 (1999) 313-335.
[6] I.J. Cox, L.M. Matthew, A.B. Jeffrey, et al., Digital Watermarking and Steganography, Morgan Kaufmann Publishers (Elsevier)Burlington, MA, 2007.
[7] C. Hsu and J. Wu, Hidden signatures in images, in Proc. IEEE Int. Conf. Image Processing, (1998), Vol. 3, pp. 223-226.
[8] X.Y. Wang, L.M. Hou, and J. Wu, A Feature-based robust digital image watermarking against geometric attacks, Image & Computer Vision, ScienceDirect, (2008), vol. 122, no. 10, pp. 350-356.
[9] Y. Xin, S. Liao, M.A. Pawlak Multibit, Geometrically robust image watermark based on zernike moments, in: Proceedings of the 17th International Conference on Pattern Recognition (ICPR-2004), (2005), pp. 861-864.
[10] Y. Xin, S. Liao, M. Pawlak, A multibit geometrically robust image watermark based on Zernike moments, IEEE Int. Conf. Pattern Recognit., (2004), vol. 4, pp. 861-864.
[11] H.S. Kim, H.K. Lee, Invariant image watermark using Zernike moments, IEEE Trans. Circuits Syst. Video Technol. 13 (2003), (8) 766- 775.
[12] L. Chang and L. Z. Yang, Desynchronization attacks on digital watermarks and their countermeasures, J. Image Graphics 10 (2005) 403-409.
[13] V. Licks, R. Jordan, Geometric attacks on image watermarking system, IEEE Trans on Multimedia 1 (2005) 68-78.
[14] A. S. Lewis and G. Knowles, Image Compression Using the 2-D Wavelet Transform, IEEE Transactions on Image Processing, (1998), vol. 1, no. 2, pp. 244-250.
[15] B. Mathon, F Cayre and P. Bas, Practical performance analysis of secure modulations for WOA spread-spectrum based image watermarking, ACM Multimedia and Security Workshop 2007, Dallas , Texas, USA.
[16] N. Bi, Q. Sun, D. Huang, Z. Yang, J.W. Huang, Robust image watermarking based on multiband wavelets and empirical mode decomposition, IEEE Transactions on Image Processing, (2007), Volume 16, Issue 8.
[17] P. Dong, and N. P. Galatsanos, Affine transformation resistant watermarking based on image normalization, Proc. IEEE Int. Conf. on Image Processing, (2008), vol. I, Oct, pp. 451-4.
[18] C.H. Lai and J.L. Wu, Robust image watermarking against local geometric attacks using multiscale block matching method, IEEE Int. Conf. on Image Processing, (2000), vol. III, pp. 318-322.
[19] P. Bas, J.M. Chassery, and B. Macq, Geometrically invariant watermarking using feature points, IEEE Trans Image Processing. 2002, 11(9):1014-28.
[20] B.S. Kim, J.G. Choi and K.H. Park, Image normalization using invariant centroid for RST invariant digital image watermarking, Lecture Notes in Computer Science, Springer Berlin, (2003), Volume 2613/2003.
[21] F. Gu, Z.M Lu, J.S. Pan, Multipurpose image watermarking in DCT domain using subsampling, IEEE International Symposium on Circuits and Systems, (2005), Vol. 5, Page(s):4417 - 4420.
[22] Z.M. Lu, D.G. Xu, S.H. Sun, Multipurpose image watermarking algorithm based on multistage vector quantization, IEEE Transactions on Image Processing, (2005), Volume 14, Issue 6, Page(s):822 - 831.
[23] Z. M. Lu and S. H. Sun, Digital image watermarking technique based on vector quantization, Electron. Lett., (2000), vol. 36, no. 4, pp. 303-305.
[24] A. Watson, G. Yang, J. Solomon, J. Villasenor, Visibility of wavelet quantization noise, IEEE Transactions on Image Processing, (1998), vol. 6, no.8, pp. 1164-1175.