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Robust audio watermarking algorithm resisting cropping based on SIFT transform
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AI
DOI：10.1007/s11042-023-16827-3.png)
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Abstract
En 中文
Robust watermarking plays a key role in copyright protection and information leakage tracking, network conference recording, etc. However, cropping attack is a strong geometric attack, which can destroy the watermarked information of audio signal. For this problem, this paper proposes a robust audio watermarking algorithm by combining chaotic system, scale invariant feature transform (SIFT) feature and discrete wavelet transform (DWT) to resist cropping attack. After applying DWT to the original signal, we use the obtained DWT low-frequency coefficients to construct a square matrix and extract the SIFT features with scale invariance from this matrix. The watermark is encrypted by Tent map, and then it is embedded into the low-frequency components according to the sift features location information. Watermark extraction is the inverse process of embedding. Compared with the state of the art audio watermarking algorithms, the proposed algorithm has better performance in terms of robustness and payload capacity while ensuring good imperceptibility.
Keywords:
Cropping attack
Discrete wavelet transform
Scale-invariant feature transform
Audio watermarking
Robustness
Journal
IF:
3
Papers:
1.9W
Citations:
3.2W
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