A constructive and unifying framework for zero-bit watermarking

In the watermark detection scenario, also known as zero-bit watermarking, a watermark, carrying no hidden message, is inserted in content. The watermark detector checks for the presence of this particular weak signal in content. The article looks at this problem from a classical detection theory point of view, but with side information enabled at the embedding side. This means that the watermark signal is a function of the host content. Our study is twofold. The first step is to design the best embedding function for a given detection function, and the best detection function for a given embedding function. This yields two conditions, which are mixed into one `fundamental' partial differential equation. It appears that many famous watermarking schemes are indeed solution to this `fundamental' equation. This study thus gives birth to a constructive framework unifying solutions, so far perceived as very different.Comment: submitted to IEEE Trans. on Information Forensics and Securit

Robust Image Watermarking Using QR Factorization In Wavelet Domain

A robust blind image watermarking algorithm in wavelet transform domain (WT) based on QR factorization, and quantization index modulation (QIM) technique is presented for legal protection of digital images. The host image is decomposed into wavelet subbands, and then the approximation subband is QR factorized. The secret watermark bit is embedded into the R vector in QR using QIM. The experimental results show that the proposed algorithm preserves the high perceptual quality. It also sustains against JPEG compression, and other image processing attacks. The comparison analysis demonstrates the proposed scheme has better performance in imperceptibility and robustness than the previously reported watermarking algorithms

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

Improved digital watermarking schemes using DCT and neural techniques

The present thesis investigates the copyright protection by utilizing the digital watermarking of images. The basic spatial domain technique DCT based frequency based technique were studied and simulated. Most recently used Neural Network based DCT Scheme is also studied and simulated. The earlier used Back Propagation Network (BPN) is replaced by Radial Basis Function Neural Network (RBFNN) in the proposed scheme to improve the robustness and overall computation requirements. Since RBFNN requires less number of weights during training, the memory requirement is also less as compared to BPN. Keywords : Digital Watermarking, Back Propagation Network (BPN), Hash Function, Radial Basis Function Neural Network (RBFNN), and Discrete Cosine Transform (DCT). Watermarking can be considered as a special technique of steganography where one message is embedded in another and the two messages are related to each other in some way. The most common examples of watermarking are the presence of specific patterns in currency notes, which are visible only when the note is held to light, and logos in the background of printed text documents. The watermarking techniques prevent forgery and unauthorized replication of physical objects. In digital watermarking a low-energy signal is imperceptibly embedded in another signal. The low-energy signal is called the watermark and it depicts some metadata, like security or rights information about the main signal. The main signal in which the watermark is embedded is referred to as the cover signal since it covers the watermark. In recent years the ease with which perfect copies can be made has lead large-scale unauthorized copying, which is a great concern to the music, film, book and software publishing industries. Because of this concern over copyright issues, a number of technologies are being developed to protect against illegal copying. One of these technologies is the use of digital watermarks. Watermarking embeds an ownership signal directly into the data. In this way, the signal is always present with the data. Analysis Digital watermarking techniques were implemented in the frequency domain using Discrete Cosine Transform (DCT). The DCT transforms a signal or image from the spatial domain to the frequency domain. Also digital watermarking was implemented using Neural Networks such as: 1. Back Propagation Network (BPN) 2. Radial Basis Function Neural Network (RBFNN) Digital watermarking using RBFNN was proposed which improves both security and robustness of the image. It is based on the Cover’s theorem which states that nonlinearly separable patterns can be separated linearly if the pattern is cast nonlinearly into a higher dimensional space. RBFNN contains an input layer, a hidden layer with nonlinear activation functions and an output layer with linear activation functions. Results The following results were obtained:- 1. The DCT based method is more robust than that of the LSB based method in the tested possible attacks. DCT method can achieve the following two goals: The first is that illegal users do not know the location of the embedded watermark in the image. The second is that a legal user can retrieve the embedded watermark from the altered image. 2. The RBFNN network is easier to train than the BPN network. The main advantage of the RBFNN over the BPN is the reduced computational cost in the training stage, while maintaining a good performance of approximation. Also less number of weights are required to be stored or less memory requirements for the verification and testing in a later stage