Feature Image Watermarking Based on Bicubic Interpolation of Wavelet Coefficients Using CRT

Authors

  • Prajanto Wahyu Adi Universitas Dian Nuswantoro
  • Yani Parti Astuti Universitas Dian Nuswantoro
  • Egia Rosi Subhiyakto Universitas Dian Nuswantoro

DOI:

https://doi.org/10.21512/commit.v11i2.3870

Keywords:

Watermarking, CRT, Bicubic Interpolation, Wavelet

Abstract

The main objective of watermarking method is to improve the robustness and imperceptibility. This paper introduces an improved CRT watermarking method using absolute value of interpolated wavelet coefficients aiming to improve the imperceptibility and robustness. The standard CRT method embeds the watermark bits on the blocks of pixels evenly. Hence, it can significantly reduce the quality of watermarked images when the watermark lies on the homogeneous area. Otherwise, the proposed method is embedding the watermark bits on the heterogeneous area by sorting the absolute magnitude of wavelet coefficients descending. The wavelet
coefficients are selected from high frequency wavelet sub band HH. This scheme is able to determine the appropriate embedding location in certain range of value. The watermark bits are then embedding on the selected
pixel value using CRT scheme. The result shows that the average imperceptibility value the CRT is 0.9980 while the proposed method has average value of 0.9993. On robustness against compression, the proposed method achieves better result compared to the CRT with the average NC values of 0.7916 higher than the CRT value of 0.7530. These prove that the proposed method has better performance in term of imperceptibility and robustness against compression than the CRT method.

Dimensions

Plum Analytics

Author Biographies

Prajanto Wahyu Adi, Universitas Dian Nuswantoro

Lecturer at Department Informatics

Faculty of Computer Science

Universitas Dian Nuswantoro

Yani Parti Astuti, Universitas Dian Nuswantoro

Lecturer at Department Informatics

Faculty of Computer Science

Universitas Dian Nuswantoro

Egia Rosi Subhiyakto, Universitas Dian Nuswantoro

Lecturer at Department Informatics

Faculty of Computer Science

Universitas Dian Nuswantoro

References

V. S. Verma, R. K. Jha, and A. Ojha, “Significant region based robust watermarking scheme in lifting wavelet transform domain,” Expert Systems with Applications, vol. 42, no. 21, pp. 8184–8197,

N. M. Makbol and B. E. Khoo, “A new robust and secure digital image watermarking scheme based on the integer wavelet transform and singular value decomposition,” Digital Signal Processing,

vol. 33, pp. 134–147, 2014.

C. R. S. Rao and M. V. Prasad, Digital Watermarking Techniques in Curvelet and Ridgelet Domain. Switzerland: Springer, 2016.

J. C. Patra, A. Karthik, and C. Bornand, “A novel crt-based watermarking technique for authentication of multimedia contents,” Digital Signal Processing, vol. 20, no. 2, pp. 442–453, 2010.

J. C. Patra, J. E. Phua, and C. Bornand, “A novel dct domain crt-based watermarking scheme for image authentication surviving jpeg compression,” Digital Signal Processing, vol. 20, no. 6, pp. 1597–1611, 2010.

C. Li, Z. Zhang, Y. Wang, B. Ma, and D. Huang, “Dither modulation of significant amplitude difference for wavelet based robust watermarking,” Neurocomputing, vol. 166, pp. 404–415, 2015.

P. W. Adi and F. Z. Rahmanti, “Robust integer haar wavelet based watermarking using singular value decomposition,” Jurnal Ilmu Komputer dan Informasi, vol. 9, no. 1, pp. 26–34, 2016.

W. Stallings and M. P. Tahiliani, Cryptography and network security: principles and practice. New Jersey: Pearson, 2014, vol. 6.

P. Zhi Yong, H. Z. Tan, and C. Di Hu, “An improved low-cost adaptive bicubic interpolation arithmetic and vlsi implementation,” Acta Automatica Sinica, vol. 39, no. 4, pp. 407–417, 2013.

Z. Pan, W. Chen, Z. Jiang, L. Tang, Y. Liu, and Z. Liu, “Performance of global look-up table strategy in digital image correlation with cubic b–spline interpolation and bicubic interpolation,” Theoretical and Applied Mechanics Letters,

vol. 6, no. 3, pp. 126–130, 2016.

J. Leng, G. Xu, and Y. Zhang, “Medical image interpolation based on multi-resolution registration,” Computers & Mathematics with Applications, vol. 66, no. 1, pp. 1–18, 2013.

G. K. Birajdar and V. H. Mankar, “Blind method for rescaling detection and rescale factor estimation in digital images using periodic properties of interpolation,” AEUE – International Journal of

Electronics and Communications, vol. 68, no. 7, pp. 644–652, 2014.

J. W. Han, J. H. Kim, S. Sull, and S. J. Ko, “New edge–adaptive image interpolation using anisotropic gaussian filters,” Digital Signal Processing, vol. 23, no. 1, pp. 110–117, 2013.

Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, “Image quality assessment: From error visibility to structural similarity,” IEEE transactions on image processing, vol. 13, no. 4, pp. 600–612, 2004.

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Published

2017-10-31
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