A video watermark algorithm based on tensor decomposition

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Author(s)
Zhang, Shanqing
Guo, Xiaoyun
Xu, Xianghua
Li, Li
Chang, Chin-Chen
Griffith University Author(s)
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2019
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Abstract

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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Mathematical Biosciences and Engineering

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16

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5

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©2019 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Applied mathematics

Biomedical engineering

Chemical engineering

Science & Technology

Life Sciences & Biomedicine

Mathematical & Computational Biology

Video watermark

tensor

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Zhang, S; Guo, X; Xu, X; Li, L; Chang, C-C, A video watermark algorithm based on tensor decomposition, Mathematical Biosciences and Engineering, 2019, 16 (5), pp. 3435-3449

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