Robust Audio Watermarking Algorithms

In the recent years, more and more digital audio media are available due to internet and audio processing techniques. It is beneficial to our daily life but brings the problem of ownership protection. As a solution, audio watermarking technique is developed fast. However, some key issues are still open. In this dissertation, we pay more attention to robustness of audio watermarking, and partly resolve the key problems of the Digital to Analog (DA) and Analog to Digital (AD) conversions, and TSM in audio watermarking. And, we introduce a robust audio watermarking scheme by using Zernike moments. The main contributions are as follows:(1) In many applications of audio watermarking, the DA/AD conversions are involved. Based on extensive experiments, we analyze and conclude that the main degradations on the audio signal are linear temporal scaling and wave magnitude distortion. The scaling is viewed as an interpolation processing, and the scaling amount relies on the soundcard, sampling rate, and media player in the test. And, wave magnitude distortion may be modeled as amplitude scaling followed by the additional noise corruption. Then, we analyze the performance of quantization-based audio watermarking in case of additional gaussian noise, amplitude modification and temporal scaling, presented the calculation expression of BER in case of Gaussian noises and audio amplitude modification. As a conclusion, quantization audio watermarking is very susceptible to the DA/ AD conversions.(2) By analyzing the distortion caused by the DA/AD conversions, we proposed a robust watermark embedding strategy. The watermark is embedded into in the...