基于Hu矩的人类视频对象水印

P. Tzouveli, K. Ntalianis, S. Kollias
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引用次数: 2

摘要

本文提出了一种新的基于视频对象的水印方案,为语义内容提供版权保护。为了实现这一目标,首先使用自适应二维高斯肤色分布模型来检测初始图像中的面部和身体区域。然后设计了一个不变水印,并使用不变Hu矩对攻击进行了测试。所提出的算法具有鲁棒性好、计算效率高、传输到解码器端的开销非常低等优点。在JPEG有损压缩、模糊、滤波和裁剪等多种信号失真条件下对所提出的基于目标的水印系统进行了性能测试,在真实图像上的实验结果表明了所提方案的有效性和鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Human video object watermarking based on Hu moments
A novel video object based watermarking scheme is proposed in this paper, providing copyright protection of the semantic content. To achieve this goal, an adaptive two-dimensional Gaussian model of skin color distribution is initially used in order to detect face and body regions within the initial image. An invariant watermark is then designed and tested against attacks using invariant Hu moments. The proposed algorithms have the advantages of being robust, computationally efficient, and overheads transmitted to the decoder side are very low. Performance of the proposed object based watermarking system is tested under various signal distortions such as JPEG lossy compression, blurring, filtering and cropping, Experimental results on real life images indicate the efficiency and robustness of the proposed scheme.
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