In this paper we propose the FD-TR: Feature Detector Based on Scale Invariant Feature Transform and Bidirectional Feature Regionalization for digital image watermarking. The Scale Invariant Feature Transform method is applied to extract keypoints and an Edge and Neighbor Filtering method is proposed to generate the candidate feature points. Then the Bidirectional Feature Regionalization method is proposed and applied in order to classify candidate feature points and form candidate feature regions. On this basis, the Candidate Feature Region Filtering method is proposed to select the final feature regions for watermarking. During the watermarking process, the Nonsubsampled Contourlet Transform is employed to the extracted feature regions to extract the low-frequency coefficients. Next, we use the Diagonal Matrix-based Spread Transform Dither Modulation for watermark embedding and extraction. Extensive experiments have been conducted to evaluate the performance of the proposed scheme and the comparison with existing methods demonstrate that the proposed method is superior to the existing methods in terms of robustness and quality.

在本文中，我们提出了 FD-TR：基于尺度不变特征变换和双向特征区域化的特征检测器，用于数字图像水印。应用尺度不变特征变换方法提取关键点，并提出边缘和邻居过滤方法来生成候选特征点。然后提出并应用双向特征区域化方法对候选特征点进行分类，形成候选特征区域。在此基础上，提出了候选特征区域过滤方法来选择最终的特征区域进行水印。在水印过程中，对提取的特征区域采用非下采样Contourlet变换来提取低频系数。下一个，我们使用基于对角矩阵的扩展变换抖动调制进行水印嵌入和提取。已经进行了大量实验来评估所提出方案的性能，并且与现有方法的比较表明，所提出的方法在鲁棒性和质量方面优于现有方法。