Feature-based Watermarking Schemes Research Articles

Robust hybrid image watermarking scheme based on KAZE features and IWT-SVD

Digital watermarking is a critical technique for digital rights management (DRM). In the last decade, the local feature-based watermarking schemes have attracted much attention because of their remarkable robustness against geometrical attacks, which will destroy the synchronization between watermark embedding and detection. However, they only used local feature and thus their robustness is based on invariances of the particular local features, which still have limitations when suffering various signal processing attacks. To address this problem, a robust hybrid color image watermarking scheme (RHIW) is proposed in our study by fusing a local feature-based watermarking procedure with a traditional transform domain-based watermarking procedure. In the local feature-based procedure, watermarks are embedded into significant bit-planes of the KAZE feature regions repeatedly by modifying their histograms. In the transform domain-based procedure, watermark is embedded into the IWT-SVD domain by modifying the entries of left singular vector matrices. For a queried image, all the watermarks of KAZE-based and IWT-SVD-based procedures are extracted and compared with the original watermark. Then, the comparison results are fused following an attention-based fusion method to identify the copyright ownership. The experimental results demonstrate that RHIW is sufficient robust not only against geometrical attacks such as cropping, row & column removal and rotation attacks, but also against various common signal processing attacks such as filtering, noise addition, brightness modification and contrast modification, which outperforms state-of-the-art local feature-based watermarking schemes.

Geometrically Invariant Image Watermarking using Connected Objects and Gravity Centers

The design of geometrically invariant watermarking is one of the most challenging work in digital image watermarking research area. To achieve the robustness to geometrical attacks, the inherent characteristic of an image is usually used. In this paper, a geometrically invariant image watermarking scheme using connected objects and gravity center is proposed. First, the gray-scale image is converted into the binary one, and the connected objects according to the connectedness of binary image are obtained, then the coordinates of these connected objects are mapped to the gray-scale image, and the gravity centers of those bigger objects are chosen as the feature points for watermark embedding. After that, the line between each gravity center and the center of the whole image is rotated an angle to form a sector, and finally the same version of watermark is embedded into these sectors. Because the image connectedness is topologically invariant to geometrical attacks such as scaling and rotation, and the gravity center of the connected object as feature points is very stable, the watermark synchronization is realized successfully under the geometrical distortion. The proposed scheme can extract the watermark information without using the original image or template. The simulation results show the proposed scheme has a good invisibility for watermarking application, and stronger robustness than previous feature-based watermarking schemes against geometrical attacks such as rotation, scaling and cropping, and can also resist common image processing operations including JPEG compression, adding noise, median filtering, and histogram equalization, etc.

Joint robustness and security enhancement for feature-based image watermarking using invariant feature regions

Local image features have been widely applied in feature-based watermarking schemes. The feature invariance is exploited to achieve robustness against attacks, but the leakage of information about hidden watermarks from publicly known locations and sizes of features are often unconsidered in security. This paper, therefore, proposes a novel image watermarking approach, which adopts invariant feature regions to jointly enhance its robustness and security. Initially, circular feature regions are determined by the scale-adapted auto-correlation matrix and the Laplacian-of-Gaussian operation. Leakage of secret information is also controlled carefully during feature detection procedure. An optimal selection process formulated as a multidimensional knapsack problem is then proposed to select robust non-overlapping regions from those circular feature regions to resist various attacks. This process is implemented by a genetic algorithm-based approach, and incorporates randomization to mitigate the security risk. Finally, each selected region is normalized to obtain a geometrically invariant feature region, and embedded with a region-dependent watermark to overcome the weakness of multiple-redundant watermarks. The evaluation results based on the StirMark benchmark present the proposed scheme can tolerate various attacks, including noise-like signal processing and geometric distortions. A security analysis in terms of differential entropy also confirms the security improvement of the proposed method.

Robust localized image watermarking based on invariant regions

The robustness of the localized watermarking methods mainly depends on the robustness of the feature locating the watermark. Based on the mean luminance of the disk, a rotation and scale invariant feature extraction algorithm is proposed. A theoretical verification of the rotation and scale invariance of extracted feature points in the continuous image is further performed. The extracted feature points are used to construct rotation and scale invariant circular regions, where the watermark is embedded after affine normalization. Experimental results show that the constructed regions fit the watermarking applications much better than those in previous feature-based watermarking schemes from the aspect of robustness against common attacks including filtering, JPEG compression, cropping, rotation and scaling, and the proposed localized image watermarking scheme has better robustness than previous feature-based watermarking schemes against common signal process and geometrical attacks while maintaining imperceptibility.