Dynamic stochastic resonance-based watermark extraction from audio signals in SVD domain

In this paper a dynamic stochastic resonance (DSR)-based watermark extraction technique from audio signal using singular value decomposition (SVD) has been presented. Watermark embedding has been done by weighted addition of the binary watermark in the singular values of the audio signal. DSR has been used in the extraction process to improve the authenticity of the extracted watermark by utilizing the noise or degradation introduced during different signal processing attacks. DSR is an iterative process that tunes the coefficient of possibly attacked watermarked audio signal so that effect of noise is suppressed and hidden information is enhanced. An adaptive optimization procedure has been adopted for selection of bistable parameters to achieve maximum correlation coefficient under minimum computational complexity. Resilience of this technique has been tested in presence of various signal processing attacks. Using proposed technique robust extraction of watermark is obtained without trading off the audibility of audio signal. Comparison with plain SVD-based, DWT-based and DCT-based techniques reflects that the proposed DSR-based audio watermarking scheme gives remarkably better performance in terms of correlation between original and extracted watermarks.