616 research outputs found

    Cognitive computation of compressed sensing for watermark signal measurement

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    As an important tool for protecting multimedia contents, scrambling and randomizing of original messages is used in generating digital watermark for satisfying security requirements. Based on the neural perception of high-dimensional data, compressed sensing (CS) is proposed as a new technique in watermarking for improved security and reduced computational complexity. In our proposed methodology, watermark signal is extracted from the CS of the Hadamard measurement matrix. Through construction of the scrambled block Hadamard matrix utilizing a cryptographic key, encrypting the watermark signal in CS domain is achieved without any additional computation required. The extensive experiments have shown that the neural inspired CS mechanism can generate watermark signal of higher security, yet it still maintains a better trade-off between transparency and robustness

    Reversible color video watermarking scheme based on hybrid of integer-to-integer wavelet transform and Arnold transform

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    Unauthorized redistribution and illegal copying of digital contents are serious issues which have affected numerous types of digital contents such as digital video. One of the methods, which have been suggested to support copyright protection, is to hide digital watermark within the digital video. This paper introduces a new video watermarking system which based on a combination of Arnold transform and integer wavelet transforms (IWT). IWT is employed to decompose the cover video frames whereby Arnold transform is used to scramble the watermark which is a grey scale image. Scrambling the watermark before the concealment makes the transmission more secure by disordering the information. The system performance was benchmarked against related video watermarking schemes, in which the evaluation processes consist of testing against several video operations and attacks. Consequently, the scheme has been demonstrated to be perfectly robust

    Survey of watermarking techniques

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    Spread spectrum-based video watermarking algorithms for copyright protection

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    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

    Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust

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    Watermarking the outputs of generative models is a crucial technique for tracing copyright and preventing potential harm from AI-generated content. In this paper, we introduce a novel technique called Tree-Ring Watermarking that robustly fingerprints diffusion model outputs. Unlike existing methods that perform post-hoc modifications to images after sampling, Tree-Ring Watermarking subtly influences the entire sampling process, resulting in a model fingerprint that is invisible to humans. The watermark embeds a pattern into the initial noise vector used for sampling. These patterns are structured in Fourier space so that they are invariant to convolutions, crops, dilations, flips, and rotations. After image generation, the watermark signal is detected by inverting the diffusion process to retrieve the noise vector, which is then checked for the embedded signal. We demonstrate that this technique can be easily applied to arbitrary diffusion models, including text-conditioned Stable Diffusion, as a plug-in with negligible loss in FID. Our watermark is semantically hidden in the image space and is far more robust than watermarking alternatives that are currently deployed. Code is available at https://github.com/YuxinWenRick/tree-ring-watermark.Comment: 16 pages, 8 figures, code is available at https://github.com/YuxinWenRick/tree-ring-watermark, fixed the repo lin

    A New Model of Securing Iris Authentication Using Steganography

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    The integration of steganography in biometric system is a solution for enhancing security in iris. The process of biometric enrollment and verification is not highly secure due to hacking activities at the biometric point system such as overriding iris template in database. In this paper, we proposed an enhancement of temporal-spatial domain algorithm which involves the scheme of Least Significant Bits (LSB) as the new model which converts iris images to binary stream and hides into a proper lower bit plane. Here, the stego key, n, will be inserted into the binary values from the plane which concealed the information; where n is the input parameter in binary values which inserted to the iris codes, m. These values produce the output which is the new iris stego image after binary conversion. Theoretically, the proposed model is promising a high security performance implementation in the future
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