Robust Image Watermarking With Quaternion Fractional-Order Polar Harmonic-Fourier Moments Based On Wavelet Transformation: Resistance Against Rotation Attacks
Article Sidebar
Main Article Content
Abstract
This study presents a zero-watermarking algorithm that can resist rotation attacks. The algorithm uses quaternion fractional-order polar harmonic-Fourier moments (QFr-PHFMs) based on wavelet-transformation. First, the wavelet-transformation is applied to each component of the host image, which is in RGB three-channel color. The low-frequency sub-bands of each component are then extracted and represented using quaternion algebra. Multiple QFr-PHFMs are calculated, and the invariants of the QFr-PHFMs are utilized to establish the watermark system. The watermark extraction process is also simplified. The detection of the image requires a two-level wavelet transformation, followed by the calculation of multiple invariant moments of the low-frequency sub-image. The experimental results are shown and compared with similar methods. Simulations show that this method can produce high-quality visual effects and withstand noise, filtering, JPEG compression, and cropping attacks.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
All articles published in JIWE are licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) License. Readers are allowed to
- Share — copy and redistribute the material in any medium or format under the following conditions:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use;
- NonCommercial — You may not use the material for commercial purposes;
- NoDerivatives — If you remix, transform, or build upon the material, you may not distribute the modified material.
References
Z.Q. Xia, X.Y. Wang, X.X. Li, C.P. Wang, S. Unar, M.X. Wang and T.T. Zhao, “Efficient copyright protection for three CT images based on
quaternion polar harmonic Fourier moments”, Signal processing, vol. 164, no.11, pp. 368-379, 2019.
K.M. Hosny, M.M. Darwish, and M.M. Fouda, “New Color Image Zero-Watermarking Using Orthogonal Multi-Channel Fractional-Order
Legendre-Fourier Moments”, IEEE Access, vol. 9, no. 99, pp. 91209-91219, 2021.
Z. Yuan, D. Liu, X. Zhang, H. Wang and Q. Su, “DCT-based color digital image blind watermarking method with variable steps”, Multimedia
Tools and Applications, vol. 79, no. 1, pp. 163-173,2020.
X. Liu, Y. Wu, H. Zhang, J. Wu and L. Zhang, “Quaternion discrete fractional Krawtchouk transform and its application in color image
encryption and watermarking”, Signal Processing, vol. 38, no. 15, pp. 173-178,2021.
Q. Wen, T. Sun, and S. Wang, “The concept and application of zero watermark”, Acta electronica Sinica, vol. 31, no. 2, pp. 214-216,2003.
B. Ma, L.L. Chang, C.P. Wang, J. Li, L. Gang, Z.Q. Xia and X.Y. Wang, “Double Medical Images Zero-Watermarking Algorithm Based on the
Chaotic System and Ternary Accurate Polar Complex Exponential Transform”, Journal of Mathematical Imaging and Vision, vol. 63, no. 9, pp. 1160-1178, 2021.
Z.Q. Xia, X.Y. Wang, C.P. Wang, C.X. Wang, B. Ma, Q. Li, M.X. Wang and T.T. Zhao, “A robust zero-watermarking algorithm for lossless
copyright protection of medical images” , Applied Intelligence, vol. 52,no. 1, pp. 607-621,2022.
T.F. Yang, J.F. Ma, Y.B. Miao, X. Wang, B. Xiao, B. He and Q. Meng, “Quaternion weighted spherical Bessel-Fourier moment and its invariant for color image reconstruction and object recognition”, Information Sciences, vol. 505, pp. 388-405,2019.
B.J. Chen, H.Z. Shu, H. Zhang, G. Chen, C. Toumoulin, J.L. Dillenseger and L.M. Luo, “Quaternion Zernike moments and their invariants for color image analysis and object recognition”, Signal Processing, vol. 92, no. 2, pp. 308-318,2012, doi: 10.1016/j.sigpro.2011.07.018.
K.M. Hosny, M.M. Darwish and T. Aboelenen, “New fractional-order Legendre-Fourier moments for pattern recognition applications”,
Pattern Recognition, vol. 103, pp. 1-19,2020.
B. Xiao, L. Li, Y. Li, W. Li, and G Wang, “Image analysis by fractional-order orthogonal moments”, Information Sciences, vol. 382, pp. 135-149,2017.
H.Q. Zhang, Z.M. Li, and Y.J. Liu, “Fractional Orthogonal Fourier-Mellin Moments for Pattern Recognition”, Chinese Conference on Pattern Recognition, Communications in Computer and Information Science, vol. 662, pp. 766–778,2016.
X.Y. Wang, W.Y. Li and H.Y. Yang, “Quaternion polar complex exponential transform for invariant color image description”, Applied
Mathematics and Computation, vol. 256, no. C, pp. 951-967,2015.
B.J. Chen, H.Z. Shu, H. Zhang, G. Chen, C. Toumoulin, J.L. Dillenseger and L.M. Luo, “Quaternion Zernike moments and their invariants
for color image analysis and object recognition”, Signal Processing, vol. 92, pp. 308-318,2012.
Z.H. Shao, H.Z. Shu, J.S. Wu, B.J. Chen and J.L. Coatrieux, “Quaternion Bessel–Fourier moments and their invariant descriptors for object
reconstruction and recognition”, Pattern Recognition, vol. 47, no. 2, pp. 603-611,2014.
Y. Lim, K.W.Ng, P.Naveen and S.C.Haw, “Emotion Recognition by Facial Expression and Voice: Review and Analysis”,Journal of Informatics and Web Engineering, vol. 1, no. 2, pp. 45-54,2022
N.R. Jin, X.Q. Lv, Y.Gu, Y. Zhao and K. Liu, “Blind watermarking algorithm for color image in Contourlet domain based on QR
code and chaotic encryption”, Packaging engineering, vol. 38, no. 15.pp. 173-178,2017.
Y.L. Hong, G.L. Qie, and H.W. Yu, “A contrast preserving color image graying algorithm based on two-step parametric subspace model”,
Frontiers of Information Technology & Electronic Engineering, pp. 102-116,2017.
W.T. Chan, “Conditional Noise Filter for MRI Images with Revised Theory on Second-order Histograms”, International Journal on Robotics, Automation and Sciences, vol. 3, pp. 25-32,2021.