Robust and Transparent Spread Spectrum Audio Watermarking
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32797
Robust and Transparent Spread Spectrum Audio Watermarking

Authors: Ali Akbar Attari, Ali Asghar Beheshti Shirazi

Abstract:

In this paper, we propose a blind and robust audio watermarking scheme based on spread spectrum in Discrete Wavelet Transform (DWT) domain. Watermarks are embedded in the low-frequency coefficients, which is less audible. The key idea is dividing the audio signal into small frames, and magnitude of the 6th level of DWT approximation coefficients is modifying based upon the Direct Sequence Spread Spectrum (DSSS) technique. Also, the psychoacoustic model for enhancing in imperceptibility, as well as Savitsky-Golay filter for increasing accuracy in extraction, is used. The experimental results illustrate high robustness against most common attacks, i.e. Gaussian noise addition, Low pass filter, Resampling, Requantizing, MP3 compression, without significant perceptual distortion (ODG is higher than -1). The proposed scheme has about 83 bps data payload.

Keywords: Audio watermarking, spread spectrum, discrete wavelet transform, psychoacoustic, Savitsky-Golay filter.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1316119

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 801

References:


[1] Attari, A. A. and Asghar Beheshti Shirazi, A. 2017. Robust and Blind Audio Watermarking in Wavelet Domain. Proceedings of the International Conference on Graphics and Signal Processing (New York, NY, USA, 2017), 69–73.
[2] Cvejic, N. 2004. Algorithms for audio watermarking and steganography. Oulun yliopisto.
[3] D. Ellis http://labrosa.ee.columbia.edu/matlab/.
[4] Fallahpour, M. et al. 2015. Audio watermarking based on Fibonacci numbers. Audio, Speech, and Language Processing, IEEE/ACM Transactions on. 23, 8 (2015), 1273–1282.
[5] He, X. 2012. Signal Processing, Perceptual Coding, and Watermarking of Digital Audio: Advanced Technologies and Models. Information Science Reference.
[6] Hu, H.-T. and Hsu, L.-Y. 2015. A DWT-Based Rational Dither Modulation Scheme for Effective Blind Audio Watermarking. Circuits, Systems, and Signal Processing. (2015), 1–20.
[7] Li, L. and Fang, X. 2010. Adaptive detection for spread spectrum audio watermarking. IEEE International Conference on Wireless Communications, Networking and Information Security (WCNIS). (2010), 58–62.
[8] Li, R. et al. 2016. Spread spectrum audio watermarking based on perceptual characteristic aware extraction. IET Signal Processing. 10, 3 (2016), 266–273.
[9] Lin, Y. and Abdulla, W.H. 2015. Audio Watermark - A comprehensive Foundation Using MATLAB. Springer.
[10] Malik, H. et al. 2008. Robust audio watermarking using frequency-selective spread spectrum. IET Information Security. 2, 4 (2008), 129–150.
[11] Malvar, H. S. and Florêncio, D. A. F. 2003. Improved spread spectrum: a new modulation technique for robust watermarking. IEEE transactions on signal processing. 51, 4 (2003), 898–905.
[12] Press, W. et al. 1987. Numerical Recipes: The Art of Scientific Computing.
[13] Seok, J. 2012. Audio watermarking using independent component analysis. Journal of information and communication convergence engineering. 10, 2 (2012), 175–180.
[14] Tewari, T. K. 2015. Novel Techniques for Improving the Performance of Digital Audio Watermarking for Copyright Protection. Ph.D. dissertation, Dept. Computer Science Engineering & Information Technology, Jaypee Institue Of Information Technology, Noida, India.
[15] Wook Kim, H. et al. 2010. Selective correlation detector for additive spread spectrum watermarking in transform domain. Signal Processing. 90, 8 (2010), 2605–2610.