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A video watermark algorithm based on tensor decomposition

1 School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China
2 Feng Chia University, Department of Information Engineering and Computer Science, Taiwan

Special Issues: Security and Privacy Protection for Multimedia Information Processing and communication

Since most of the previous video watermark algorithms regard a video as a series of consecutive images, the embedding and extraction of watermark are performed on these images, and the correlation and redundancy among frames of a video are not considered. Such algorithms are weak in protecting against frame attacks. In order to improve the robustness, we take into consideration the correlation and redundancy among the frames of a video to propose a blind video watermark algorithm based on tensor decomposition. First, a grayscale video is represented as a 3-order tensor, and the core tensor is obtained by tensor decomposition. Second, the watermark embedding position is selected based on the stability of the maximum value in the core tensor because the core tensor represents the main energy of a video. Then, the watermark is embedded by quantifying the maximum value in the core tensor. Finally, the watermark is uniformly distributed across frames of a video by inverse tensor decomposition. The experiments show that our algorithm based on tensor decomposition has better imperceptibility and robustness against common video attacks.
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Keywords Video watermark; tensor; tensor decomposition; tucker decomposition; parity quantization

Citation: Shanqing Zhang, Xiaoyun Guo, Xianghua Xu, Li Li, Chin-Chen Chang. A video watermark algorithm based on tensor decomposition. Mathematical Biosciences and Engineering, 2019, 16(5): 3435-3449. doi: 10.3934/mbe.2019172


  • 1. A. H. Tewfik, Digital Watermarking, IEEE Signal Processing Magazine, 17 (2000), 17–18.
  • 2. T. Kalker, G. Depovere and J. Haitsma, Video watermarking system for broadcast monitoring, Secur. Watermark. Multim. Contents, 3657 (1999), 103–112.
  • 3. F. Hartung and B. Girod, Watermarking of uncompressed and compressed video, Elsevier North-Holland, 66 (1998), 283–301.
  • 4. I. G. Karybali and K. Berberidis, Efficient spatial image watermarking via new perceptual masking and blind detection schemes, IEEE Transact. Inform. Foren. Secur., 1 (2006), 256–274.
  • 5. M. J. Lee, K. S. Kim and H. K. Lee, Digital cinema watermarking for estimating the position of the pirate, IEEE Transact. Multim., 12 (2010), 605–621.
  • 6. J. Han and X. Zhao, An adaptive grayscale watermarking method in spatial domain, J. Inform. Comput. Sci., 12 (2015), 4759–4769.
  • 7. S. Wang, D. Zheng and J. Zhao, Adaptive watermarking and tree structure based image quality estimation, IEEE Transact. Multim., 16 (2014), 311–325.
  • 8. Z. Zhou, S. Chen and G. Wang, A robust digital image watermarking algorithm based on dct domain for copyright protection, Int. Symp. Smart Graph., 9317 (2012), 132–142.
  • 9. I. J. Cox and M. L. Miller, A Review of watermarking and the importance of perceptual modeling, Human Vision Electron. Imag. Confer., 3016 (1997), 92–99.
  • 10. D.V. S. Chandra, Digital image watermarking using singular value decomposition, Symposium on Circuits & Systems, USA, 2002.
  • 11. S. Wang, J. Yang and M. Sun, Sparse tensor discriminant color space for face verification, IEEE Transact. Neural Networks Learn. Systems, 23 (2012), 876–888.
  • 12. B. Ma, L. Huang and J. Shen, Discriminative tracking using tensor pooling, IEEE Transact. Cybernet., 46 (2017), 2411–2422.
  • 13. J. Li, X. Mao and X. Wu, Human action recognition based on tensor shape descriptor, IET Computer Vision, 10 (2016), 905–911.
  • 14. A. H. Phan, P. Tichavsky and A. Cichocki, CANDECOMP/PARAFAC decomposition of high-order tensors through tensor reshaping, IEEE Transact. Signal Process., 61 (2013), 4847–4860.
  • 15. A. S. Jermyn, Efficient tree decomposition of high-rank tensors, J. Comput. Phys., 377 (2018), 142–154.
  • 16. N. Sidiropoulos, L. L. De and X. Fu, Tensor Decomposition for Signal Processing and Machine Learning, IEEE Transact. Signal Process., 65 (2017), 3551–3582.
  • 17. E. E. Abdallah, A. B. Hamza and P. Bhattacharya, MPEG Video Watermarking Using Tensor Singular Value Decomposition, Image Analysis & Recognition, Canada, 2007.
  • 18. H. Xu, G. Jiang and M. Yu, A Color Image Watermarking Based on Tensor Analysis, IEEE Access, 6 (2018), 51500–51514.
  • 19. P. Li and W. K. Leung, Decoding low density parity check codes with finite quantization bits, Commu. Lett. IEEE, 4 (2000), 62–64.
  • 20. K. K. Sharma and A. Upadhyay, A novel image fusion technique for gray scale images using tensor unfolding in transform domains, Recent Advances & Innovations in Engineering, India, 2014.
  • 21. R. Costantini, L. Sbaiz and S. Susstrunk, Higher Order SVD Analysis for Dynamic Texture Synthesis, IEEE Transact. Image Process., 17 (2008), 42–52.
  • 22. Y. Wu, H. Tan and Y. Li, A fused CP factorization method for incomplete tensors, IEEE Transact. Neural Networks Learn. Systems, 30 (2018), 751–764.
  • 23. G. Zhou, A. Cichocki and Q. Zhao, Efficient Nonnegative Tucker Decompositions: Algorithms and Uniqueness, IEEE Transact. Image Process., 24 (2015), 4990–5003.
  • 24. A. Rajwade, A. Rangarajan and A. Banerjee, Image Denoising Using the Higher Order Singular Value Decomposition, IEEE Transact. Pattern Anal. Mac. Intell., 35 (2013), 849–862.
  • 25. K. Wang, G. Zhou and G. Fu, An Approach to Fast Eye Location and Face Plane Rotation Correction, J. Computer-Aided Design Comput. Graph., 25 (2013), 865–879.
  • 26. P. F. Checcacci and P. Spalla, Analysis and correction of errors in a polarimeter for Faraday rotation measurements, IEEE Transact. Antennas Propagat., 24 (1976), 253–255.


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