Segmenting Histogram-based Robust Audio Watermarking Approach

Abstract

Based on the invariant features and data distribution in time domain before and after attacking on the audio, it is clearly that the standard variance shows good invariant statistical feature. The relation of four consecutive bins in a histogram maintains change less than 5%. Then, a general data selection approach, which meets the demands of normal distribution and other distributions, is created for the watermark hiding. Based on segmenting idea, an audio watermarking algorithm of embedding and extracting is designed with statistical features by the stable relation of four consecutive bins. Experimental results show that the algorithm can resist on attack of low-pass filtering with large hiding bandwidth up to 17 bit/s. It shows much better than the existed histogram approach with relations of three consecutive bins. The algorithm can also resist on the attacks of TSM and other common attacks.