基于SIFT的椭圆区域鲁棒数字水印方案

如何有效抵抗去同步攻击是数字图像水印研究领域的热点问题之一。利用图像仿射协变特征，提出一种可有效抵抗去同步攻击的鲁棒水印算法。对目前流行的利用多尺度Harris和SIFT描述算子来匹配图像的方法，后者有较好的匹配效果，对恢复同步水印更加稳定，并且能较好抵抗去同步攻击。该算法利用性能稳定的SIFT算子提取图像特征点，并通过基于最小生成树聚类算法的选择策略获得一组稳定且彼此独立的椭圆仿射协变特征区域，基于特征区域，利用椭圆归一化得到具有缩放和旋转不变性的圆形区域。将圆形区域进行非下采样轮廓变换（NSCT），其中非下采样轮廓变换不仅克服了小波（Wavelet）变换的非奇异性最优基缺点，而且提供了优于轮廓（Contourlet）变换的平移不变性。将水印嵌入变换后的低频子带中。该算法实现盲提取，仿真实验结果表明，提出的算法是有效的且对常规图像处理、几何攻击以及组合攻击均具有较好的鲁棒性。

Robust watermark scheme using SIFT in ellipse region

Watermark synchronization is very crucial to design robust image watermarking scheme. A novel robust image watermarking scheme against desynchronization attacks is proposed. The stable performance of the SIFT algorithm is used to extract feature points of a given host image. A set of stable and non-overlapped ellipse affine covariant regions are then chosen via selection criterion based on the minimum spanning tree clustering algorithm. Based on feature regions, ellipse normalization is performed on these circular feature regions to achieve scaling and rotation invariance. Nonsubsampled Contourlet Transform（NSCT） is made in the circular region, and the watermark is embedded in the transformed low-pass subband. This algorithm realizes blind detection. Simulation results demonstrate that the proposed scheme is robust against common image processing operations, geometric attacks, and combined attacks.