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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:数字水印已经在文献中讨论了数十年。在业务方面,它是潜在的版权保护方法,所有权证明广播监视等的重要手段。在学术方面,这是一个有趣的研究问题。音频水印是最具有挑战性的,因为人类听觉系统即使对原始音频的很小改动也很敏感。除了信号的不可感知性之外,容量和鲁棒性也很重要。经验模式分解是音频水印技术中的最新革命性概念。在本文中,我们提出了一种鲁棒的音频水印方案,该方案可确保感知力,鲁棒性和高有效负载能力。为了防止未经授权的第三方删除水印,我们利用Tinkerbell混沌图生成随机密钥,并在密钥之后嵌入水印。使用多个密钥来确保水印的有效分发,以防止裁剪攻击并启用水印校正并与接收器同步。实验结果表明,该方法对重采样,裁剪,重量化,AWGN攻击具有鲁棒性。

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