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    基于图像特征点与伪Zernike矩的鲁棒水印算法研究

    A Robust Watermarking Scheme Based on Image Feature and PseudoZernike Moments

    • 摘要: 以HarrisLaplace检测算子及伪Zernike矩相关知识为基础,提出一种可有效抵抗几何攻击的数字水印新算法.该算法首先利用HarrisLaplace检测算子从载体图像中提取出稳定的特征点;然后根据特征尺度自适应确定局部特征区域,并使其尺度标准化;最后通过量化调制伪Zernike矩幅值将水印信息嵌入到局部特征区域中.仿真实验表明,新算法不仅具有较好的透明性,而且对常规信号处理(中值滤波、边缘锐化、叠加噪声和JPEG压缩等)和几何攻击(包括全局仿射变换、局部失真等)均具有较好的鲁棒性.

       

      Abstract: Digital watermarking, as an efficient supplemental method of traditional cryptographic system, has been an important technique for intellectual property protection of digital multimedia. Nowadays, there is an unprecedented development in the image watermarking field. On the other hand, attacks against watermarking systems have become more sophisticated. In general, these attacks can be categorized into common signal processing and geometric distortion. Geometric distortion is known as one of the most difficult attacks to resist. Geometric distortion desynchronizes the location of the watermark and hence causes incorrect watermark detection. Based on HarrisLaplace theory and pseudoZernike moments, a new featurebased image watermarking scheme robust to geometric attacks is proposed in this paper. Firstly, the HarrisLaplace detector is utilized to extract steady feature points from the host image; then, the local feature regions (LFR) are ascertained adaptively according to the feature scale theory, and they are scaled to a standard size; finally, the digital watermark are embedded into the local feature regions (LFR) by quantizing the magnitudes of the pseudoZernike moments. Experimental results show that the proposed scheme is not only invisible and robust against common signals processing such as median filtering, sharpening, noise adding, JPEG compression, etc., but also robust against the geometric attacks such as rotation, translation, scaling, row or column removal, shearing, local geometric distortion, combination attacks, etc.

       

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