计算机与现代化

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一种基于Chebyshev混沌神经网络的视频水印算法

  

  1. 青岛科技大学数理学院,山东青岛266061
  • 收稿日期:2016-08-02 出版日期:2017-04-20 发布日期:2017-05-08
  • 作者简介:梁家栋(1991-),男,山东威海人,青岛科技大学数理学院硕士研究生,研究方向:图像水印,视频水印; 通信作者:杨树国(1970-),男,教授,博士,研究方向:数字水印,数字图像处理。
  • 基金资助:
    山东省重点研发计划项目(2015GGX101020); 山东省高等学校科研计划项目(J13LN34); 青岛市科技发展计划项目(KJZD-13-27-JCH); 青岛科技大学大学生创新创业训练计划项目(201606001)

A Video Watermarking Algorithm Based on Chebyshev Chaotic Neural Network

  1. School of Mathematics and Physics, Qingdao University of Science & Technology, Qingdao 266061, China
  • Received:2016-08-02 Online:2017-04-20 Published:2017-05-08

摘要: 针对视频版权的保护,提出一种基于Chebyshev混沌神经网络的视频水印算法。首先选取二值图像作为图像水印,利用Chebyshev混沌神经网络对图像进行加密;然后对宿主视频进行分帧处理,通过Henon映射产生混沌序列提取关键帧,同时提取关键帧亮度分量的低频系数,将处理后的图像水印自适应地嵌入小波变换后亮度分量的低频系数中。实验结果表明,该算法具有较好的不可见性,且针对噪声、高斯滤波、旋转、帧丢失等攻击具有良好的鲁棒性。

关键词: 视频水印, Chebyshev混沌神经网络, Henon映射

Abstract: For the copyright protection of digital video, this paper proposes a video watermarking algorithm based on Chebyshev chaotic neural network. First, to enhance the watermarking images safety, we process it using Chebyshev chaotic neural network, then decompose the host video into the frames, extract key frames from the chaotic sequences generated by Henon mapping, and extract the low frequence coefficient of the key frames luminance component. The processed image watermark is adaptively embedded into the low frequency coefficients of the luminance component after the wavelet transform. The experimental results show that this algorithm has a good invisibility, and has good robustness for the attacks such as noise, Gauss filtering, rotation, frame shear, etc.

Key words: video watermarking, Chebyshev chaotic neural network, Henon mapping

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