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机构地区:[1]西安电子科技大学电子工程学院,陕西西安710071
出 处:《西安电子科技大学学报》2011年第3期13-19,共7页Journal of Xidian University
基 金:国家自然科学基金资助项目(61072110);陕西省自然科学基金资助项目(SJ08F15);陕西省工业攻关资助项目(2010K06-20);陕西省工业攻关计划资助项目(2010K01-077)
摘 要:提出了一种能够有效抵抗几何攻击的视频双水印方法,挖掘了一种几何形变不变量-视频低维流形,理论推导和实验验证了其几何不变性.首先根据不同视频镜头的低维流形实时生成零水印及动态水印;为了兼顾鲁棒性和透明性,将水印嵌入在大能量AVS预测残差DCT中频系数上;深入研究了视频时空三维特性,利用低维流形有效量化表征了视频运动信息,建立了包含运动特征、亮度特征及纹理特征的视觉动态掩蔽模型,以自适应控制水印嵌入强度.实验结果表明,该方法可以有效抵抗中心裁剪、不规则裁剪、行裁剪、旋转、缩放和平移等大强度几何攻击及其联合攻击,如旋转加边角裁剪、中心裁剪加旋转等,对于常规信号处理及多种视频水印攻击也具有强鲁棒性.How to resist geometric attacks is currently the focus and difficulty in video watermarking fields. This paper presents a video dual watermarking method which could effectively resist geometric attacks. The method mines a geometric deformation invariant, namely the low-dimensional manifold of video, and theoretically derives and experimentally demonstrates geometric invariance. First of all, the method generates zero-watermark or dynamic semantics watermark online according to low-dimensional manifolds of different video shots. In order to balance the robustness and transparency, the method embeds watermark in the IF DCT coefficients of AVS predicted residuals with large energy. This paper studies deeply the three-dimensional space-time characteristics of video, effectively quantifies and characterizes video motion information by lowdimensional manifold of video, establishes the human dynamic masking model including movement features, brightness features and texture features, so as to adaptively control watermark embedding strength. Experiments and analysis show that this method can effectively resist center cutting, irregular cutting, row cutting, rotation, scaling, translation and other high intensity geometric attacks and combined attacks, such as rotation and corner cutting, center cutting and rotation, etc. It also has strong robustness to the conventional video signal processing and various video attacks.
关 键 词:视频水印 低维流形 流形学习 几何攻击 AVS标准
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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