Robust Audio Data Hiding Using Correlated Quantization With Histogram-Based Detector

In this paper, two blind audio watermarking methods using correlated quantization for data embedding with histogram-based detector have been proposed. First, a novel mapping called the point-to-point graph (PPG) is introduced. In this mapping, the value of samples is important as well as the correlation among them. As this mapping increases the dimension of the signal, the data embedding procedure (quantization) will be diversified more securely than that of the 1-D domains such as the time or frequency domains. Hence, two watermarking techniques coined as hard and soft quantization methods based on the quantization of the PPG point radii are suggested. The performance of both techniques is analyzed by obtaining the radii distribution of PPG points after watermarking. Experimental results against AWGN attack confirm the validity of theoretical analysis. Moreover, the robustness of the proposed methods against other common attacks such as echo, low pass, resampling, and MP3 are investigated through extensive simulations.