Local Geometric Distortions Resilient Watermarking Scheme Based on Symmetry

As an efficient watermark attack method, geometric distortions destroy the synchronization between watermark encoder and decoder. And the local geometric distortion is a famous challenge in the watermark field. Although a lot of geometric distortions resilient watermarking schemes have been proposed, few of them perform well against local geometric distortion like random bending attack (RBA). To address this problem, this paper proposes a novel watermark synchronization process and the corresponding watermarking scheme. In our scheme, the watermark bits are represented by random patterns. The message is encoded to get a watermark unit, and the watermark unit is flipped to generate a symmetrical watermark. Then the symmetrical watermark is embedded into the spatial domain of the host image in an additive way. In watermark extraction, we first get the theoretically mean-square error minimized estimation of the watermark. Then the auto-convolution function is applied to this estimation to detect the symmetry and get a watermark units map. According to this map, the watermark can be accurately synchronized, and then the extraction can be done. Experimental results demonstrate the excellent robustness of the proposed watermarking scheme to local geometric distortions, global geometric distortions, common image processing operations, and some kinds of combined attacks

A Color Image Watermarking Scheme Resistant against Geometrical Attacks

The geometrical attacks are still a problem for many digital watermarking algorithms at present. In this paper, we propose a watermarking algorithm for color images resistant to geometrical distortions (rotation and scaling). The singular value decomposition is used for watermark embedding and extraction. The log-polar map- ping (LPM) and phase correlation method are used to register the position of geometrical distortion suffered by the watermarked image. Experiments with different kinds of color images and watermarks demonstrate that the watermarking algorithm is robust to common image processing attacks, especially geometrical attacks

Spread spectrum-based video watermarking algorithms for copyright protection

Merged with duplicate record 10026.1/2263 on 14.03.2017 by CS (TIS)Digital technologies know an unprecedented expansion in the last years. The consumer can now benefit from hardware and software which was considered state-of-the-art several years ago. The advantages offered by the digital technologies are major but the same digital technology opens the door for unlimited piracy. Copying an analogue VCR tape was certainly possible and relatively easy, in spite of various forms of protection, but due to the analogue environment, the subsequent copies had an inherent loss in quality. This was a natural way of limiting the multiple copying of a video material. With digital technology, this barrier disappears, being possible to make as many copies as desired, without any loss in quality whatsoever. Digital watermarking is one of the best available tools for fighting this threat. The aim of the present work was to develop a digital watermarking system compliant with the recommendations drawn by the EBU, for video broadcast monitoring. Since the watermark can be inserted in either spatial domain or transform domain, this aspect was investigated and led to the conclusion that wavelet transform is one of the best solutions available. Since watermarking is not an easy task, especially considering the robustness under various attacks several techniques were employed in order to increase the capacity/robustness of the system: spread-spectrum and modulation techniques to cast the watermark, powerful error correction to protect the mark, human visual models to insert a robust mark and to ensure its invisibility. The combination of these methods led to a major improvement, but yet the system wasn't robust to several important geometrical attacks. In order to achieve this last milestone, the system uses two distinct watermarks: a spatial domain reference watermark and the main watermark embedded in the wavelet domain. By using this reference watermark and techniques specific to image registration, the system is able to determine the parameters of the attack and revert it. Once the attack was reverted, the main watermark is recovered. The final result is a high capacity, blind DWr-based video watermarking system, robust to a wide range of attacks.BBC Research & Developmen

Robust Object-Based Watermarking Using SURF Feature Matching and DFT Domain

In this paper we propose a robust object-based watermarking method, in which the watermark is embedded into the middle frequencies band of the Discrete Fourier Transform (DFT) magnitude of the selected object region, altogether with the Speeded Up Robust Feature (SURF) algorithm to allow the correct watermark detection, even if the watermarked image has been distorted. To recognize the selected object region after geometric distortions, during the embedding process the SURF features are estimated and stored in advance to be used during the detection process. In the detection stage, the SURF features of the distorted image are estimated and match them with the stored ones. From the matching result, SURF features are used to compute the Affine-transformation parameters and the object region is recovered. The quality of the watermarked image is measured using the Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM) and the Visual Information Fidelity (VIF). The experimental results show the proposed method provides robustness against several geometric distortions, signal processing operations and combined distortions. The receiver operating characteristics (ROC) curves also show the desirable detection performance of the proposed method. The comparison with a previously reported methods based on different techniques is also provided

Towards Optimal Copyright Protection Using Neural Networks Based Digital Image Watermarking

In the field of digital watermarking, digital image watermarking for copyright protection has attracted a lot of attention in the research community. Digital watermarking contains varies techniques for protecting the digital content. Among all those techniques,Discrete Wavelet Transform (DWT) provides higher image imperceptibility and robustness. Over the years, researchers have been designing watermarking techniques with robustness in mind, in order for the watermark to be resistant against any image processing techniques. Furthermore, the requirements of a good watermarking technique includes a tradeoff between robustness, image quality (imperceptibility) and capacity. In this paper, we have done an extensive literature review for the existing DWT techniques and those combined with other techniques such as Neural Networks. In addition to that, we have discuss the contribution of Neural Networks in copyright protection. Finally we reached our goal in which we identified the research gaps existed in the current watermarking schemes. So that, it will be easily to obtain an optimal techniques to make the watermark object robust to attacks while maintaining the imperceptibility to enhance the copyright protection

A survey of digital image watermarking techniques

Watermarking, which belong to the information hiding field, has seen a lot of research interest recently. There is a lot of work begin conducted in different branches in this field. Steganography is used for secret conmunication, whereas watermarking is used for content protection, copyright management, content authentication and tamper detection. In this paper we present a detailed survey of existing and newly proposed steganographic and watenmarking techniques. We classify the techniques based on different domains in which data is embedded. Here we limit the survey to images only

Digital Watermarking of Images towards Content Protection.

With the rapid growth of the internet and digital media techniques over the last decade, multimedia data such as images, video and audio can easily be copied, altered and distributed over the internet without any loss in quality. Therefore, protection of ownership of multimedia data has become a very significant and challenging issue. Three novel image watermarking algorithms have been designed and implemented for copyright protection. The first proposed algorithm is based on embedding multiple watermarks in the blue channel of colour images to achieve more robustness against attacks. The second proposed algorithm aims to achieve better trade-offs between imperceptibility and robustness requirements of a digital watermarking system. It embeds a watermark in adaptive manner via classification of DCT blocks with three levels: smooth, edges and texture, implemented in the DCT domain by analyzing the values of AC coefficients. The third algorithm aims to achieve robustness against geometric attacks, which can desynchronize the location of the watermark and hence cause incorrect watermark detection. It uses geometrically invariant feature points and image normalization to overcome the problem of synchronization errors caused by geometric attacks. Experimental results show that the proposed algorithms are robust and outperform related techniques found in literature

Robust feature-based 3D mesh segmentation and visual mask with application to QIM 3D watermarking

The last decade has seen the emergence of 3D meshes in industrial, medical and entertainment applications. Many researches, from both the academic and the industrial sectors, have become aware of their intellectual property protection arising with their increasing use. The context of this master thesis is related to the digital rights management (DRM) issues and more particularly to 3D digital watermarking which is a technical tool that by means of hiding secret information can offer copyright protection, content authentication, content tracking (fingerprinting), steganography (secret communication inside another media), content enrichment etc. Up to now, 3D watermarking non-blind schemes have reached good levels in terms of robustness against a large set of attacks which 3D models can undergo (such as noise addition, decimation, reordering, remeshing, etc.). Unfortunately, so far blind 3D watermarking schemes do not present a good resistance to de-synchronization attacks (such as cropping or resampling). This work focuses on improving the Spread Transform Dither Modulation (STDM) application on 3D watermarking, which is an extension of the Quantization Index Modulation (QIM), through both the use of the perceptual model presented, which presents good robustness against noising and smoothing attacks, and the the application of an algorithm which provides robustness noising and smoothing attacks, and the the application of an algorithm which provides robustness against reordering and cropping attacks based on robust feature detection. Similar to other watermarking techniques, imperceptibility constraint is very important for 3D objects watermarking. For this reason, this thesis also explores the perception of the distortions related to the watermark embed process as well as to the alterations produced by the attacks that a mesh can undergo

Data hiding in images based on fractal modulation and diversity combining

The current work provides a new data-embedding infrastructure based on fractal modulation. The embedding problem is tackled from a communications point of view. The data to be embedded becomes the signal to be transmitted through a watermark channel. The channel could be the image itself or some manipulation of the image. The image self noise and noise due to attacks are the two sources of noise in this paradigm. At the receiver, the image self noise has to be suppressed, while noise due to the attacks may sometimes be predicted and inverted. The concepts of fractal modulation and deterministic self-similar signals are extended to 2-dimensional images. These novel techniques are used to build a deterministic bi-homogenous watermark signal that embodies the binary data to be embedded. The binary data to be embedded, is repeated and scaled with different amplitudes at each level and is used as the wavelet decomposition pyramid. The binary data is appended with special marking data, which is used during demodulation, to identify and correct unreliable or distorted blocks of wavelet coefficients. This specially constructed pyramid is inverted using the inverse discrete wavelet transform to obtain the self-similar watermark signal. In the data embedding stage, the well-established linear additive technique is used to add the watermark signal to the cover image, to generate the watermarked (stego) image. Data extraction from a potential stego image is done using diversity combining. Neither the original image nor the original binary sequence (or watermark signal) is required during the extraction. A prediction of the original image is obtained using a cross-shaped window and is used to suppress the image self noise in the potential stego image. The resulting signal is then decomposed using the discrete wavelet transform. The number of levels and the wavelet used are the same as those used in the watermark signal generation stage. A thresholding process similar to wavelet de-noising is used to identify whether a particular coefficient is reliable or not. A decision is made as to whether a block is reliable or not based on the marking data present in each block and sometimes corrections are applied to the blocks. Finally the selected blocks are combined based on the diversity combining strategy to extract the embedded binary data