A Robust Audio Watermark Representation Based on Linear Chirps

In this paper, we introduce a novel watermark representation for audio watermarking, where we embed linear chirps as watermark signals. Different chirp rates, i.e., slopes on the time–frequency (TF) plane, represent watermark messages such that each slope corresponds to a unique message. These watermark signals, i.e., linear chirps, are embedded and extracted using an existing watermarking algorithm. The extracted chirps are then postprocessed at the receiver using a line detection algorithm based on the Hough–Radon transform (HRT). The HRT is an optimal line-detection algorithm, which detects directional components that satisfy a parametric constraint equation in the image of a TF plane, even at discontinuities corresponding to bit errors. Simulation results show that HRT correctly detects the embedded watermark message after common signal processing operations for bit error rates up to 20%. The new watermark representation and the postprocessing stage based on HRT significantly improve the performance of the watermark detection process and can be combined with existing watermark embedding/extraction algorithms for increased robustness.