基于支持向量机(SVM)的数字音频水印

提出了一种新的基于支持向量机（support vector machine，SVM）的数字音频水印算法．主要思想是在宿主音频中嵌入一段模板信息，定义模板信息与宿主音频之间的一种对应关系．将水印的检测问题转化为一个可用SVM处理的二分类问题，利用SVM对先验知识（对应关系）的学习，以达到对未知数字音频水印的正确分类检测．仿真实验结果表明，该数字音频水印具有较强的健壮性和不可感知性，在受到MP3压缩、低通滤波、重采样／量化、噪声干扰等常用信号处理方法的处理后，能正确检测出水印，同时在水印检测时不需要原始音频，实现了水印的盲检测．

Digital Audio Watermarking Based on Support Vector Machine (SVM)

A novel digital audio watermarking technique based on SVM(support vector machine) is proposed in this paper. The main idea of the method is that the retrieval of embedded watermark can be considered as a two-class problem, and SVM can be used to learn the characteristics of the embedded watermark in audio. Because the SVM possesses the learning and adaptive capabilities, it almost exactly recovers the watermark from the watermarked audio. The extensive experimental results show that the embedded watermark is robust against audio signal processing, such as MPEG audio coding, cropping, filtering, resampling and requantizing. The watermarking method does not require the use of the original signal for watermarking detection.