FD-TR: feature detector based on scale invariant feature transform and bidirectional feature regionalization for digital image watermarking
Abstract
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.
Mianjie Li
Phd student (2020.6)
