In this paper, we propose a robust feature extraction based digital image watermarking method using Distortion- Compensated Dither Modulation (DC-DM). Our proposed local watermarking method provides stronger robustness and better flexibility than traditional global watermarking methods. We improve robustness by introducing feature extraction and DC-DM method. To extract the robust feature points, we propose a DAISY-based Robust Feature Extraction (DRFE) method by employing the DAISY descriptor and applying the entropy calculation based filtering. The experimental results show that the proposed method achieves satisfactory robustness under the premise of ensuring watermark imperceptibility quality compared to other existing methods.
This paper proposes a local digital image watermarking method based on Robust Feature Extraction. The segmentation is achieved by Simple Linear Iterative Clustering (SLIC) based on which an Image Segmentation-based Robust Feature Extraction (ISRFE) method is proposed for feature extraction. Our method can adaptively extract feature regions from the blocks segmented by SLIC. This novel method can extract the most robust feature region in every segmented image. Each feature region is decomposed into low-frequency domain and high-frequency domain by Discrete Cosine Transform (DCT). Watermark images are then embedded into the coefficients in the low-frequency domain. The Distortion-Compensated Dither Modulation (DC-DM) algorithm is chosen as the quantization method for embedding. The experimental results indicate that the method has good performance under various attacks. Furthermore, the proposed method can obtain a trade-off between high robustness and good image quality.