Application of side-informed embedding and polynomial detection to audio watermarking

Spread spectrum watermarking proceeds by extracting a feature vector from the cover contents and embedding a pseudo-random watermark signal in that feature vector. To detect the presence of the watermark, a correlation of the feature vector with the pseudo-random signal is performed and the result compared to a threshold. This correlation detection function is a first-order function of the feature vector components. In recent work, we have proposed that higher-order polynomial detection functions, combined with a side-informed watermark embedding strategy, can be used to increase the efficiency of the watermarking system. We have demonstrated this through a statistical analysis. In this paper, we apply our new family of detection functions to the watermarking of real audio signals. The schemes are tested on a database of over 300 different audio signals and a robustness analysis is performed on the experimental results.