Robust Mel-Frequency Cepstral coefficients feature detection and dual-tree complex wavelet transform for digital audio watermarking

Abstract

A novel digital audio watermarking scheme based on robust Mel-Frequency Cepstral coefficients feature detection and dual-tree complex wavelet transform is proposed in this paper, which is similar as patchwork based methods that several segments are extracted from the host audio clip for watermarking use. The robust Mel-Frequency Cepstral coefficients feature detection method is proposed to extract the feature segments which should be relocated when the host audio signal attacked by various distortions including both the common audio signal processing and the conventional geometric distortions. With the robust feature segments, the approximate shift invariant transform dual-tree complex wavelet transform based watermarking method is proposed to embed the watermark into the DT CWT real low-pass coefficients of each segment, using the spread spectrum techniques. The linear correlation is calculated to judge the existence of the watermark during the watermark detection. Experimental results show that the proposed digital audio watermarking scheme based on robust Mel-Frequency Cepstral coefficients feature detection and dual-tree complex wavelet transform can achieve high robustness against the common audio signal processing, such as low-pass filtering, MP3 compression, echo addition, volume change, and normalization; and geometric distortions, such as resample Time-Scale Modification (TSM), pitch invariant TSM, and tempo invariant pitch shifting. In addition, the proposed audio watermarking scheme is resilient to Stir-mark for Audio, and it performs much better comparing with the existing state-of-the art methods.