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An optimized high payload audio watermarking algorithm based on LU-factorization

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Abstract

In the field of audio watermarking, reliably embedding the large number of watermarking bits per second in an audio signal without affecting the audible quality of the host audio with good robustness against signal processing attacks is still one of the most challenging issues. In this paper, a high payload, perceptually transparent and robust audio watermarking solution for such a problem by optimizing the existing problem using genetic algorithm is presented. The genetic algorithm in this paper is used to find the optimal number of audio samples required for hiding each watermarking bit. The embedding is done using the imperceptible properties of LU (lower upper) factorization in wavelet domain. This paper addresses the robustness within perceptual constraints at high payload rate in both mathematical analysis and experimental testing by representing behavior of various attacks using attack characterization. Experimental results show that the proposed audio watermarking algorithm can achieve 1280 bps capacity at an average Signal-to-noise ratio (SNR) of 31.02 dB with good robustness to various signal processing attacks such as noise addition, filtering, and compression. In addition, the proposed watermarking algorithm is blind as it does not require the original signal or watermark during extraction. The comparison of the proposed algorithm with the existing techniques also shows that the proposed algorithm is able to achieve high payload with good robustness under perceptual constraints.

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Authors and Affiliations

  1. Department of CSE, Amity University, Noida, Uttar Pradesh, India

    Arashdeep Kaur

  2. Department of ECE, Amity University, Noida, Uttar Pradesh, India

    Malay Kishore Dutta

Authors
  1. Arashdeep Kaur
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  2. Malay Kishore Dutta
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Correspondence to Arashdeep Kaur.

Additional information

Communicated by L. Zhou.

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Kaur, A., Dutta, M.K. An optimized high payload audio watermarking algorithm based on LU-factorization. Multimedia Systems 24, 341–353 (2018). https://doi.org/10.1007/s00530-017-0545-x

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