A robust zero-watermarking algorithm for audio
EURASIP Journal on Advances in Signal Processing
Multi-watermarking Scheme for Copyright Protection and Content Authentication of Digital Audio
PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Speech watermarking for analog flat-fading bandpass channels
IEEE Transactions on Audio, Speech, and Language Processing
Audio watermarking scheme robust against desynchronization based on the dyadic wavelet transform
EURASIP Journal on Advances in Signal Processing
A robust digital audio watermarking scheme using wavelet moment invariance
Journal of Systems and Software
A pseudo-Zernike moment based audio watermarking scheme robust against desynchronization attacks
Computers and Electrical Engineering
An SVD audio watermarking approach using chaotic encrypted images
Digital Signal Processing
Digital audio watermarking technique using pseudo-zernike moments
ICICS'09 Proceedings of the 11th international conference on Information and Communications Security
A robust content based audio watermarking using UDWT and invariant histogram
Multimedia Tools and Applications
Robust and secure watermarking scheme for breath sound
Journal of Systems and Software
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On the basis of support vector regression (SVR), a new adaptive blind digital audio watermarking algorithm is proposed. This algorithm embeds the template information and watermark signal into the original audio by adaptive quantization according to the local audio correlation and human auditory masking. The procedure of watermark extraction is as follows. First, the corresponding features of template and watermark are extracted from the watermarked audio. Then, the corresponding feature of template is selected as training sample to train SVR and an SVR model is returned. Finally, the actual outputs are predicted according to the corresponding feature of watermark, and the digital watermark is recovered from the watermarked audio by using the well-trained SVR. Experimental results show that our audio watermarking scheme is not only inaudible, but also robust against various common signal processing (such as noise adding, resampling, requantization, and MP3 compression), and also has high practicability. In addition, the algorithm can extract the watermark without the help of the original digital audio signal, and the performance of it is better than other SVM audio watermarking schemes.