Robust and Blind Audio Watermarking Scheme Based on Genetic Algorithm in Dual Transform Domain

Qiuling Wu, Aiyan Qu, Dandan Huang and Lejun Ma

Mathematical Problems in Engineering, 2021, vol. 2021, 1-14

Abstract:

In order to protect the copyright of audio media in cyberspace, a robust and blind audio watermarking scheme based on the genetic algorithm (GA) is proposed in a dual transform domain. A formula for calculating the embedding depth is developed, and two embedding depths with different values are used to represent the “1” and “0” states of the binary watermark, respectively. In the extracting process, the embedding depth in each audio fragment will be calculated and compared with the average embedding depth to determine the watermark bit by bit, so this scheme can blindly extract the watermark without the original audio. GA will be applied to optimize the algorithm parameters for meeting the performance requirements in different applications. Besides, the embedding rule is further optimized to enhance the transparency based on the principle of minimal modification to the audio. Experimental results prove that the payload capacity reaches 172.27 bps, the bit error rate (BER) is 0.1% under the premise that its transparency is higher than 25 dB, and its robustness is strong against many attacks. Significantly, this scheme can adaptively select the algorithm parameters to satisfy the specific performance requirements.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:3378683

DOI: 10.1155/2021/3378683

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