Blind SVD-based audio watermarking using entropy and log-polar transformation

This paper proposes a blind singular value decomposition (SVD) based audio watermarking scheme using entropy and log-polar transformation (LPT) for copyright protection of audio signal. In our proposed scheme, initially the original audio is segmented into non-overlapping frames and discrete cosine transform (DCT) is applied to each frame. Low frequency DCT coefficients are divided into sub band and entropy of each sub band is calculated. Watermark data is embedded into the Cartesian components of the largest singular value obtained from the DCT sub band with highest entropy value of each frame by quantization. Simulation results indicate that the hidden watermark data is robust against different attacks. The comparison analysis shows that the proposed scheme has high data payload and provides superior performance compared to the state-of-the-art watermarking schemes reported recently.