EMD and psychoacoustic model based watermarking for audio

Abstract

The audio watermarking method proposed in this paper offers the copyright protection to an audio without the use of the original signal for watermark detection. The analysis filterbank decomposition, the psychoacoustic model and the empirical mode decomposition (EMD) are the three key techniques used in the novel audio watermarking method. Unlike the traditional audio watermarking algorithms where the watermark bits are embedded directly in the signal either by time domain or transform domain processing, the novel blind audio watermarking algorithm proposed in this paper embeds the watermark bits in the final residue of the subbands in the transform domain. Four watermark messages are embedded into the proposed audio watermarking system. The inaudibility, capacity and robustness of the audio watermarking system are evaluated, in order to optimize the system performance. The experimental results show that the proposed blind watermarking scheme is robust against MP3 compression and adding Gaussian noise attacks.