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Robust digital watermarking techniques for multimedia protection .

机译:鲁棒的数字水印技术用于多媒体保护。

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摘要

The growing problem of the unauthorized reproduction of digital multimedia data such as movies, television broadcasts, and similar digital products has triggered worldwide efforts to identify and protect multimedia contents. Digital watermarking technology provides law enforcement officials with a forensic tool for tracing and catching pirates. Watermarking refers to the process of adding a structure called a watermark to an original data object, which includes digital images, video, audio, maps, text messages, and 3D graphics. Such a watermark can be used for several purposes including copyright protection, fingerprinting, copy protection, broadcast monitoring, data authentication, indexing, and medical safety.;The second part of the thesis is devoted to a joint exploitation of the geometry and topology of 3D objects and its subsequent application to 3D watermarking. The key idea consists of capturing the geometric structure of a 3D mesh in the spectral domain by computing the eigen-decomposition of the mesh Laplacian matrix. We also use the fact that the global shape features of a 3D model may be reconstructed using small low-frequency spectral coefficients. The eigen-analysis of the mesh Laplacian matrix is, however, prohibitively expensive. To lift this limitation, we first partition the 3D mesh into smaller 3D sub-meshes, and then we repeat the watermark embedding process as much as possible in the spectral coefficients of the compressed 3D sub-meshes. The visual error of the watermarked 3D model is evaluated by computing a nonlinear visual error metric between the original 3D model and the watermarked model obtained by our proposed algorithm.;The third part of the thesis is devoted to video watermarking. We propose robust, hybrid scene-based MPEG video watermarking techniques based on a high-order tensor singular value decomposition of the video image sequences. The key idea behind our approaches is to use the scene change analysis to embed the watermark repeatedly in a fixed number of the intra-frames. These intra-frames are represented as 3D tensors with two dimensions in space and one dimension in time. We embed the watermark information in the singular values of these high-order tensors, which have good stability and represent the video properties. Illustration of numerical experiments with synthetic and real data are provided to demonstrate the potential and the much improved performance of the proposed algorithms in multimedia watermarking.;The proposed thesis addresses the problem of multimedia protection and consists of three parts. In the first part, we propose new image watermarking algorithms that are robust against a wide range of intentional and geometric attacks, flexible in data embedding, and computationally fast. The core idea behind our proposed watermarking schemes is to use transforms that have different properties which can effectively match various aspects of the signal's frequencies. We embed the watermark many times in all the frequencies to provide better robustness against attacks and increase the difficulty of destroying the watermark.
机译:诸如电影,电视广播和类似数字产品之类的数字多媒体数据的未授权再现的日益严重的问题引发了全世界识别和保护多媒体内容的努力。数字水印技术为执法人员提供了一种追踪和捕​​捉海盗的法医工具。水印是指将称为水印的结构添加到原始数据对象的过程,该结构包括数字图像,视频,音频,地图,文本消息和3D图形。这样的水印可用于多种目的,包括版权保护,指纹保护,复制保护,广播监视,数据认证,索引编制和医疗安全。;论文的第二部分致力于联合开发3D的几何和拓扑对象及其在3D水印中的后续应用。关键思想是通过计算网格拉普拉斯矩阵的特征分解来捕获光谱域中3D网格的几何结构。我们还使用以下事实:可以使用较小的低频频谱系数来重建3D模型的全局形状特征。然而,网格拉普拉斯矩阵的特征分析非常昂贵。为了消除此限制,我们首先将3D网格划分为较小的3D子网格,然后在压缩的3D子网格的频谱系数中尽可能多地重复水印嵌入过程。通过计算原始3D模型与我们提出的算法获得的水印模型之间的非线性视觉误差度量,对水印3D模型的视觉误差进行了评估。第三部分研究视频水印。我们提出了基于视频图像序列的高阶张量奇异值分解的鲁棒的,基于混合场景的MPEG视频水印技术。我们方法背后的关键思想是使用场景变化分析将水印重复嵌入固定数量的帧内。这些帧内表示为3D张量,在空间上具有两个维度,在时间上具有一个维度。我们将水印信息嵌入这些高阶张量的奇异值中,这些奇异值具有良好的稳定性并表示视频属性。通过对合成数据和真实数据进行数值实验,说明了该算法在多媒体水印中的潜力和改进的性能。论文主要针对多媒体保护问题,共分三部分。在第一部分中,我们提出了新的图像水印算法,这些算法对各种故意的和几何的攻击具有鲁棒性,数据嵌入灵活,计算速度快。我们提出的水印方案背后的核心思想是使用具有不同属性的变换,这些变换可以有效地匹配信号频率的各个方面。我们在所有频率中多次嵌入水印,以提供更好的抵抗攻击的鲁棒性,并增加销毁水印的难度。

著录项

  • 作者

    Abdallah, Emad Eddien Awad.;

  • 作者单位

    Concordia University (Canada).;

  • 授予单位 Concordia University (Canada).;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 155 p.
  • 总页数 155
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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