On Image Analysis by the Methods of Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Invariant Image Recognition by Zernike Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Accuracy of Zernike Moments for Image Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
StirMark Benchmark: Audio Watermarking Attacks
ITCC '01 Proceedings of the International Conference on Information Technology: Coding and Computing
A Multibit Geometrically Robust Image Watermark Based on Zernike Moments
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Time-scale invariant audio watermarking based on the statistical features in time domain
IH'06 Proceedings of the 8th international conference on Information hiding
Subjective and objective quality evaluation of watermarked audio tracks
WEDELMUSIC'02 Proceedings of the Second international conference on Web delivering of music
Invariant image watermark using Zernike moments
IEEE Transactions on Circuits and Systems for Video Technology
Multiple Scrambling and Adaptive Synchronization for Audio Watermarking
IWDW '07 Proceedings of the 6th International Workshop on Digital Watermarking
Robust hashing for music copyright protection by combining beat segmentation and chroma
Proceedings of the international conference on Multimedia
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
Digital Signal Processing
A high capacity image adaptive watermarking scheme with radial harmonic Fourier moments
Digital Signal Processing
An efficient speech content authentication algorithm based on coefficients self-correlation degree
IWDW'12 Proceedings of the 11th international conference on Digital Forensics and Watermaking
A novel speech content authentication algorithm based on Bessel-Fourier moments
Digital Signal Processing
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Extensive testing shows that the audio Zernike moments in lower orders are very robust to common signal processing operations, such as MP3 compression, low-pass filtering, etc. Based on the observations, in this paper, a robust watermark scheme is proposed by embedding the bits into the low-order moments. By analyzing and deducting the linear relationship between the audio amplitude and moments, watermarking the low-order moments is achieved in time domain by scaling sample values directly. Thus, the degradation in audio reconstruction from a limited number of watermarked Zernike moments is avoided. Experimental works show that the proposed algorithm achieves strong robustness performance due to the superiorities of exploited low-order moments.