4 research outputs found

    Towards Optimal Copyright Protection Using Neural Networks Based Digital Image Watermarking

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    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

    Robust digital image watermarking algorithms for copyright protection

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    Digital watermarking has been proposed as a solution to the problem of resolving copyright ownership of multimedia data (image, audio, video). The work presented in this thesis is concerned with the design of robust digital image watermarking algorithms for copyright protection. Firstly, an overview of the watermarking system, applications of watermarks as well as the survey of current watermarking algorithms and attacks, are given. Further, the implementation of feature point detectors in the field of watermarking is introduced. A new class of scale invariant feature point detectors is investigated and it is showed that they have excellent performances required for watermarking. The robustness of the watermark on geometrical distortions is very important issue in watermarking. In order to detect the parameters of undergone affine transformation, we propose an image registration technique which is based on use of the scale invariant feature point detector. Another proposed technique for watermark synchronization is also based on use of scale invariant feature point detector. This technique does not use the original image to determine the parameters of affine transformation which include rotation and scaling. It is experimentally confirmed that this technique gives excellent results under tested geometrical distortions. In the thesis, two different watermarking algorithms are proposed in the wavelet domain. The first algorithm belongs to the class of additive watermarking algorithms which requires the presence of original image for watermark detection. Using this algorithm the influence of different error correction codes on the watermark robustness is investigated. The second algorithm does not require the original image for watermark detection. The robustness of this algorithm is tested on various filtering and compression attacks. This algorithm is successfully combined with the aforementioned synchronization technique in order to achieve the robustness on geometrical attacks. The last watermarking algorithm presented in the thesis is developed in complex wavelet domain. The complex wavelet transform is described and its advantages over the conventional discrete wavelet transform are highlighted. The robustness of the proposed algorithm was tested on different class of attacks. Finally, in the thesis the conclusion is given and the main future research directions are suggested
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