The paper introduces a robust image watermark based on an invariant image feature vector. Normalized Zernike moments of an image are used as the vector. The watermark is generated by modifying the vector. The watermark signal is designed with Zernike moments. The signal is added to the cover image in the spatial domain after the reconstruction process. We extract the feature vector from the modified image and use it as the watermark. The watermark is detected by comparing the computed Zernike moments of the test image and the given watermark vector. Rotation invariance is achieved by taking the magnitude of the Zernike moments. An image normalization method is used for scale and translation invariance. The robustness of the proposed method is demonstrated and tested using Stirmark 3.1. The test results show that our watermark is robust with respect to geometrical distortions and compression.

Invariant image watermark using Zernike moments

In this paper, we present two watermarking approaches that are robust to geometric distortions. The first approach is based on image normalization, in which both watermark embedding and extraction are carried out with respect to an image normalized to meet a set of predefined moment criteria. We propose a new normalization procedure, which is invariant to affine transform attacks. The resulting watermarking scheme is suitable for public watermarking applications, where the original image is not available for watermark extraction. The second approach is based on a watermark resynchronization scheme aimed to alleviate the effects of random bending attacks. In this scheme, a deformable mesh is used to correct the distortion caused by the attack. The watermark is then extracted from the corrected image. In contrast to the first scheme, the latter is suitable for private watermarking applications, where the original image is necessary for watermark detection. In both schemes, we employ a direct-sequence code division multiple access approach to embed a multibit watermark in the discrete cosine transform domain of the image. Numerical experiments demonstrate that the proposed watermarking schemes are robust to a wide range of geometric attacks.

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Digital watermarking robust to geometric distortions

The illegal distribution of a digital movie is a common and significant threat to the film industry. With the advent of high-speed broadband Internet access, a pirated copy of a digital video can now be easily distributed to a global audience. A possible means of limiting this type of digital theft is digital video watermarking whereby additional information, called a watermark, is embedded in the host video. This watermark can be extracted at the decoder and used to determine whether the video content is watermarked. This paper presents a review of the digital video watermarking techniques in which their applications, challenges, and important properties are discussed, and categorizes them based on the domain in which they embed the watermark. It then provides an overview of a few emerging innovative solutions using watermarks. Protecting a 3D video by watermarking is an emerging area of research. The relevant 3D video watermarking techniques in the literature are classified based on the image-based representations of a 3D video in stereoscopic, depth-image-based rendering, and multi-view video watermarking. We discuss each technique, and then present a survey of the literature. Finally, we provide a summary of this paper and propose some future research directions.

An Overview of Digital Video Watermarking

In this article, we review the algorithms for rotation, scaling and translation (RST) invariant image watermarking. There are mainly two categories of RST invariant image watermarking algorithms. One is to rectify the RST transformed image before conducting watermark detection. Another is to embed and detect watermark in an RST invariant or semi-invariant domain. In order to help readers understand, we first introduce the fundamental theories and techniques used in the existing RST invariant image watermarking algorithms. Then, we discuss in detail the work principles, embedding process, and detection process of the typical RST invariant image watermarking algorithms. Finally, we analyze and evaluate these typical algorithms through implementation, and point out their advantages and disadvantages.

A survey of RST invariant image watermarking algorithms

This paper proposes a novel content-based image watermarking method based on invariant regions of an image. The invariant regions are self-adaptive image patches that deform with geometric transformations. Three different invariant-region detection methods based on the scale-space representation of an image were considered for watermarking. At each invariant region, the watermark is embedded after geometric normalization according to the shape of the region. By binding watermarking with invariant regions, resilience against geometric transformations can be readily obtained. Experimental results show that the proposed method is robust against various image processing steps, including geometric transformations, cropping, filtering, and JPEG compression.

/pdf/image-watermarking-based-on-invariant-regions-of-scale-space-43puz5kxr7.pdf

Image watermarking based on invariant regions of scale-space representation

Geometric attacks are among the most challenging problems in present day watermarking. Such attacks are very simple to implement yet they can defeat most of the existing watermarking algorithms without causing serious perceptual image distortion. In this paper we propose a new public watermarking algorithm, which is robust to such attacks. This algorithm uses a normalized with respect to affine transformation representation of the image based on the image moments. Then, a CDMA scheme is used to embed a multi-bit watermark in the discrete cosine transform domain of the normalized image. Numerical experiments are shown where the properties of the proposed algorithm are tested. These numerical experiments show that the proposed algorithm is very robust to wide range of geometric attacks.

Affine transformation resistant watermarking based on image normalization

While geometric attacks are one of the most challenging problems in watermarking, random bending is probably the most difficult to handle among all geometric attacks. We present a watermarking scheme based on a new deformable mesh model to combat such attacks. The distortion is corrected using the distortion field (DF) estimated by minimizing the matching error between the meshes of the original and the attacked image. A CDMA watermarking method is used for testing the proposed method, which embeds a multi-bit signature in the DCT domain and uses mesh model correction to achieve robustness. Experiments show that the proposed scheme can survive a wide range of random bending attacks.

Geometric robust watermarking based on a new mesh model correction approach

In this paper, a watermark pattern design approach is proposed to combat the general geometric attacks to watermarking systems. Geometric attacks pose a major threat to most existing watermarking systems by destroying the synchronization between the watermark patterns and the watermarked images. We propose to shape the watermark patterns so that the output of the correlation-type demodulator is in the shape of a specified function. Such a watermark pattern shaping can be used directly to combat moderate geometric attack, or used with other watermark schemes to improve decoding performance. A design example of the shaping filter is presented. Experiments show that the proposed watermarking scheme can survive survive (1999) bending attack to a wide range.

Ping Dong

Papers

Digital watermarking robust to geometric distortions

Affine transformation resistant watermarking based on image normalization

Geometric robust watermarking based on a new mesh model correction approach

Geometric robust watermarking through watermark pattern shaping