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Audio watermarking with HOS-based cepstrum feature

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TLDR
A more robust scheme of audio watermarking which is based on cepstrum (or cepstral coefficients) and HOS (higher-order statistics) schemes is proposed, which could outperform the previous innovative one.
Abstract
In this paper, we propose a more robust scheme of audio watermarking which is based on cepstrum (or cepstral coefficients) and HOS (higher-order statistics) schemes. This scheme is a zero-watermarking one for the reason to maintain the audio quality. The audio signal is firstly kurtosis-estimated and feature-recognized, and then analyzed via CC and HOS, respectively, to extract the essential parameters and characteristics, which are then used for information embedding and extracting. The achievement of the proposed scheme could outperform the previous innovative one [1].

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Journal ArticleDOI

An Audio Zero-Watermarking Algorithm Based on Wavelet and Cepstrum Coefficients Mean Comparison

TL;DR: An audio zero-watermarking algorithm based on wavelet and cepstrum coefficients mean comparison that had fine robustness under common attacks like resampling, requantization, MP3 compression, Gaussian white noise, low-pass filtering, wavelet denoising and echo attack.
References
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Concept and Application of Zero-Watermark

Sun Tan
TL;DR: The result of experiment shows that this zero watermark constructed by this method has good performance and is a new digital watermarking technology without modifying the data of original image.
Journal ArticleDOI

A robust zero-watermarking algorithm for audio

TL;DR: An efficient and robust zero-watermarking technique for audio signal is presented that uses the multiresolution characteristic of discrete wavelet transform, the energy compression characteristics of discrete cosine transform, and the Gaussian noise suppression property of higher-order cumulant to extract essential features from the host audio signal and use them for watermark detection.
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