Abstract
Recent studies of digital video watermarking have demonstrated the superiority of the core tensor as a robust feature against various attacks. However, embedding watermarks into the core tensor often introduces perceptible distortions to the host videos. In order to improve the imperceptibility while preserving the robustness, we propose a novel video watermarking algorithm based on a time factor matrix. By applying the Tucker decomposition, we transform the host video into the core tensor and three factor matrices representing the row, column and time axis directions of the video frames, respectively. We found that the first column of the time factor matrix contains the time correlation among frames of the video tensor, which is stable and does not change drastically after geometric deformation or cropping. Hence, our algorithm embeds the watermark by modifying the first column of the time factor matrix. The experimental results show that our algorithm is robust not only to attacks such as cropping, scaling, and rotation, but also to video-specific attacks such as frame deletion and video compression, which outperforms other tensor-based video watermarking algorithms.
Similar content being viewed by others
References
Abdulla A, Anwer (2015) Exploiting similarities between secret and cover images for improved embedding efficiency and security in digital steganography[D]. Doctoral thesis, University of Buckingham
Abdulla AA, Sellahewa H, Jassim SA (2014) Stego quality enhancement by message size reduction and fibonacci bit-plane mapping[C]. International conference on research in security standardisation. Springer, pp 151–166
Allwinnaldo, Budiman G et al (2019) Qimbased audio watermarking using polarbased singular value in dct domain[C]. 2019 4th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE), vol 2019, pp 216221
Ayubi P, Jafari Barani M, Yousefi Valandar M et al (2020) A new chaotic complex map for robust video watermarking[J]. Artif Intell Rev:144
Cao Z, Wang L (2019) A secure video watermarking technique based on hyperchaotic Lorentz system[J].Multimed Tools Appl 78(18)
Chen H, Wei L, He Y et al (2017) An adaptive weighted HOSVD denoising method[C]. International conference on information science & control engineering, pp 145–149
Gaj S, Sur A, Bora PK (2015) A robust watermarking scheme against re-compression attack for H.265/HEVC[C]. 2015 Fifth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG). IEEE
He Y, Liang W, Liang JL et al (2014) Tensor decomposition-based color image watermarking[C]. Fifth International Conference on Graphic & Image Processing. International Society for Optics and Photonics, pp 9069–9076
Hemalatha P (2018) Gregarious star factorization of the tensor product of graphs[J]. Discrete Math Algorithms Appl:1850055
Horé A, Ziou D (2010) Image quality metrics: PSNR vs. SSIM [C]. International conference on pattern recognition, pp 2366–2369
Juergen S (2005) Digital watermarking for digital media[J]. Information Science Publishing
Le NT, Wang JW, Wang CC et al (2019) Novel framework based on HOSVD for Ski Goggles defect detection and classification[J]. Sensors 19(24):133–158
Li L, Xia W, Lin W et al (2017) No-reference and robust image sharpness evaluation based on multiscale spatial and spectral features [J]. IEEE Trans Multimedia 19(5):1030–1040
Li DS, Che XY, Luo W et al (2019) Digital watermarking scheme for colour remote sensing image based on quaternion wavelet transform and tensor decomposition[J]. Math Methods Appl Sci 42(14):4664–4678
Mansouri A, Mahmoudi-Aznaveh A (2019) Toward a secure video watermarking in compressed domain[J]. J Inform Secur Appl 48:102370
Sun W, Chen Y, Huang L et al (2018) Tensor completion via generalized tensor tubal rank minimization using general unfolding[J]. IEEE Signal Process Lett:1
Xu H, Jiang G, Yu M et al (2018) Color image watermarking based on tensor analysis[J]. IEEE Access 6:99–111
Zhang H, Ai B (2019) Multi-Antenna channel interpolation via tucker decomposed extreme learning machine[J]. IEEE Trans Veh Technol 68(7):7160–7163
Zhang F, Luo T, Jiang G et al (2019) A novel robust color image watermarking method using RGB correlations[J]. Multimed Tools Appl 78(14):20133–20155
Zhang SQ, Guo XY, Xu XH et al (2019) A video watermark algorithm based on tensor decomposition[J]. Math Biosci Eng 16(5):3435–3449
Acknowledgements
This research was funded by the Public Welfare Technology and Industry Project of Zhejiang Provincial Science Technology Department (Grant No. LGG19F020016, No. LGF21F020014). and the National Natural Science Foundation of China (Grant No. 61802101).and “Pioneer” and “Leading Goose” R&D Program of Zhejiang(No. 2022C03132).
Author information
Authors and Affiliations
Corresponding authors
Ethics declarations
Conflict of interest
The author declare no conflicts of interest.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Zhang, S., Li, H., Li, L. et al. A video watermarking algorithm based on time factor matrix. Multimed Tools Appl 82, 7509–7527 (2023). https://doi.org/10.1007/s11042-022-13609-1
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-022-13609-1