Watermarking technique is a method to protect ownership of digital multimedia. Most existing watermarking techniques achieve a good level of imperceptibility and robustness. The challenges to achieve higher invisibili...
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Watermarking technique is a method to protect ownership of digital multimedia. Most existing watermarking techniques achieve a good level of imperceptibility and robustness. The challenges to achieve higher invisibility and resistance with lower computational time motivate researchers to work on new watermarking schemes. Robustness against noise attacks and JPEG2000 compression needs to be improved to acquire a better resistance capability of the watermark. In this paper, we present a block-based Tchebichef watermarking technique for protecting copyrights. In this technique, the host image is first divided into non-overlapping blocks and Tchebichef moments are calculated for each block. The watermarks are embedded into the blocks with lower visual entropies. The watermark image is scrambled by Arnold transform before embedding into the Tchebichef moments of the selected image blocks. The proposed watermarking scheme was tested under noise additions, filtering, cropping and compressing attacks. Our scheme was verified and compared to the existing watermarking techniques under image geometric and processing attacks. Furthermore, the proposed scheme demonstrated a superior performance in robustness under noise attacks and JPEG2000.
Ensuring conflicting requirements such as imperceptibility, payload capacity, and robustness, becomes a great challenge for a robust audio/speech watermarking algorithm. To achieve this, this paper proposes a blind an...
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Ensuring conflicting requirements such as imperceptibility, payload capacity, and robustness, becomes a great challenge for a robust audio/speech watermarking algorithm. To achieve this, this paper proposes a blind and robust audio/speech watermarking algorithm that combines the discrete Tchebichef moment transform (DTMT), the chaotic system of the mixed linear-nonlinear coupled map lattices (MLNCML), and discrete wavelet transform (DWT). The watermark is encrypted by the MLNCML system, and then it is embedded in the norm of the Tchebichef moments of the low frequency components. DTMT and MLNCML are used to achieve high robustness, high payload capacity, and high security, while DWT is used to achieve a satisfactory level of imperceptibility. In addition, the adopted strategy has a blind nature, where no original audio/speech is needed in watermark extraction. Compared to other existing audio/speech watermarking algorithms, the proposed algorithm gives better results in terms of robustness and payload capacity while keeping the embedding effect non-perceptible and undetectable. (c) 2021 Elsevier Inc. All rights reserved.
With the advent of internet, secured transmission of data over networks offers a great challenge. This problem of secrecy of information has drawn a lot of attention due to its immense demand in real life applications...
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ISBN:
(纸本)9781467393553
With the advent of internet, secured transmission of data over networks offers a great challenge. This problem of secrecy of information has drawn a lot of attention due to its immense demand in real life applications such as information security systems. The objective of this study consist of three-fold. In the first phase, we propose an embedding algorithm to hide a secret image within the cover image. In the second phase, the stego image quality is optimized using GA. Then, in the third phase, we have presented the procedure to extract the secret image from the optimized stego image with 100% data lossless. The experimental results demonstrate that the proposed method significantly outperforms the five state-of-the-art steganography techniques known to date in terms of enhanced peak signal to noise ratio (PSNR) of the stego image.
The advancements in education technology have encouraged businesses to offer a wide range of educational resources aimed at teaching labor market-related skills. However, the ever-changing abundance of information in ...
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