SVD Singular Value Decomposition 矩阵奇异值分解
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Use singular value decomposition (SVD) in the watermark algorithm may enhance the anti-geometry distortion of the image, but it is very weak to some attacks such as salt, gauss, filter and etc.
在水印算法中用奇异值分解可以提高图像的抗几何失真性，但它对椒盐、高斯、滤波等攻击的抵抗能力却很弱。
In addition, a method based on singular value decomposition (SVD) was proceed to deal with the obtained result for dropping influence of noise.
为降低噪声的影响，采用一个基于奇异值分解(SVD)的方法对识别的结构进行处理。
A face identification method based on singular value decomposition (SVD) and data fusion is proposed in this paper.
提出了一种基于奇异值分解和数据融合的脸像鉴别方法。
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