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Secret audio watermarking using empirical mode decomposition and chaotic map

机译:使用经验模式分解和混沌映射的秘密音频水印

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Digital watermarking has been discussed in the literature for decades. In business perspective, it is important as a potential method for copy right protection, proof of ownership broadcast monitoring etc. In academic perspective, it is an interesting research problem. Audio watermarking is the most challenging of all as Human Auditory System is sensitive to even a very small change to the original audio. Other than imperceptibility of the signal, capacity and robustness are important too. Empirical mode decomposition is the latest revolutionary concept in audio watermarking. In this paper we present a robust audio watermarking scheme which ensures imperceptibility, robustness and high payload capacity. To prevent un-authorized third parties from removing the watermark, we make use of Tinkerbell chaotic map to generate random secret keys and watermark is embedded following the keys. Multiple keys are used to ensure efficient distribution of the watermark to prevent cropping attacks and enable watermark correction and synchronization with receiver. The experimental results show that the method is robust against re-sampling, cropping, re-quantization, AWGN attacks.
机译:数十年来,在文献中讨论了数字水印。在商业角度来看,作为复制权限保护的潜在方法,是学术视角的潜在方法,是一个有趣的研究问题。音频水印是人类听觉系统最敏感的最具挑战性,甚至对原始音频的更小的变化也很敏感。除了信号,容量和鲁棒性的不可察视之外也很重要。经验模式分解是音频水印中的最新革命性概念。在本文中,我们提供了一种强大的音频水印方案,可确保难以察觉,鲁棒性和高的有效载荷容量。为防止未授权的第三方删除水印,我们利用Tinkerbell混沌映射映射来生成随机秘密键,水印嵌入钥匙后嵌入。多个键用于确保水印有效分布,以防止裁剪攻击并实现与接收器的水印校正和同步。实验结果表明,该方法对重新采样,裁剪,重新量化,AWGN攻击稳健。

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