纹理特征自适应的全息水印算法

Algorithm of Holographic Watermark with Adaptive Textural Features

中文关键词: FCM聚类  灰度共生矩阵  光全息加密  Hough变换

英文关键词: FCM cluster  gray-level co-occurrence matrix  optical holographic encryption  Hough transform

中文摘要:

      目的 在保证算法鲁棒性的同时最大化实现水印的不可见性，自适应地选择水印的嵌入区域，并根据图像特征嵌入不同强度的水印信号。方法 利用分块的思想，根据载体图像灰度共生矩阵二次统计量下的各特征参量选择纹理复杂度最高的区域，通过模糊C均值聚类实现对纹理特征的定义，再利用灰度直方图分析各分块的纹理强弱，将不同强度的光全息加密水印信号自适应嵌入至图像小波域的对角分量。结果 水印的不可见性得到显著提高（PSNR=49），且图像在滤波、噪声、剪切和旋转等操作下提取的水印内容依旧可被清晰识别。结论 文中算法在确保鲁棒性和安全性的同时，极大地提升水印的不可见性。

英文摘要:

      The work aims to maximize the invisibility of watermark while ensuring the algorithm robustness, adaptively select the embedded area of the watermark and embed the watermark signals of different intensities according to the image features. By means of blocked image, the area with the most complicated texture was selected according to the various characteristic parameters of gray-level co-occurrence matrix quadratic statistic for the carrier image. Textural features were defined by fuzzy C-means (FCM) cluster. Then, the texture intensity of all blocks was analyzed by grey level histograms. Optical holography encrypted watermark signals with diverse intensities were adaptively embedded into the diagonal component of image wavelet domain. The invisibility of watermark was significantly improved (PSNR=49), and the watermark information extracted when the image was subject to such operations as filtering, noise, cutting and rotation could still be clearly recognized. The proposed algorithm has greatly improved the invisibility of watermark while ensuring the robustness and security.