Audio Watermarking System Using EMD with Psychoacoustic Model
International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC).
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A new adaptive audio watermarking algorithm based on empirical mode decomposition (EMD) with human auditory and psychoacoustic model is used in this research. The audio signal is divided into frames and each one is decomposed adaptively, by EMD, into intrinsic oscillatory components called Intrinsic Mode Functions (IMFs). The watermark and the synchronization codes are embedded into the extrema of the last IMF, a low frequency mode stable under different attacks and preserving audio perceptual quality of the host signal. The data embedding rate of the EMD algorithm is 46.9–50.3 b/s. Relying on exhaustive simulations, show the robustness of the hidden watermark for additive noise, MP3 compression, re-quantization, filtering, cropping and resampling. Empirical Mode Decomposition (EMD) has been introduced for analyzing nonstationary signals derived or not from linear systems in totally adaptive way. A major advantage of EMD relies on no a priori choice of filters or basis functions. EMD is fully data-driven method that recursively breaks down any signal into a reduced number of zero-mean with symmetric envelopes AM-FM components called Intrinsic Mode Functions (IMFs). The decomposition starts from finer scales to coarser ones. The psychoacoustic model is basically based on many studies of human auditory perception. In this research, the watermark in audio can be embedded and extracted with different techniques. The psychoacoustic model can be done before embedding the watermark bit. In the scheme, the additive watermarking technique is used to embed a unique pseudo- random sequence, considered as a watermark, into the transformed domain of audio signal. The watermark strength is properly adjusted based on weighting factors derived from the proposed psychoacoustic models. The results show that at the equivalent quality of the watermarked audio, judged by the human hearing system, the robustness of the embedded watermark was increased to higher percentage, compared to the results obtained from the scheme with non- psychoacoustic model and the psychoacoustic model.
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Ambisonics, audio watermarking, rotation matrix, spatial masking