具有统计不相关性的图像投影鉴别分析及人脸识别

提出了一种新的图像投影鉴别分析方法。与Liu鉴别投影分析方法相比，该方法具有能够消除投影特征向量之间相关性的优点，另外，所提出的方法是直接基于图像矩阵的，与以往的基于图像向量的鉴别方法相比，它的突出优点是大大地提高了特征抽取的速度。最后，在ORL标准人脸库和MUST603人脸库上的试验结果表明，所提出的图像投影鉴别分析方法较Liu的方法在识别性能上有了较大幅度的提高，在ORL标准人脸库和NUST603人脸库上的试验结果表明，所提出的图像投影鉴别分析方法较Liu的方法在识别性能上有了较大幅度的提高，在普通的分类器下分别达到95.5%和99.4%的识别率，该识别率明显优于颇有影响的Fisherfaces方法，而且，特征抽取的速度提高了近15倍。

Uncorrelated Image Projection Discriminant Analysis and Face Recognition

In this paper, a novel image projection analysis method is developed for image feature extraction Compared with the Liu's projection analysis method, the proposed method has a desirable property, i e , the projective features vectors are mutual uncorrelated What's more, the proposed method is directly based on image matrices That is to say, it need not to convert the image matrix into high dimensional image vector like the existing image vector based linear discriminant methods Thus, much computational time will be saved if the method is used for feature extraction Finally, the proposed method is tested on ORL and NUST603 face databases The experimental results indicate that the proposed method is more powerful than Liu's, and a recognition accuracy of 95 5% on ORL and 99 4% on NUST603 are achieved with ordinary classifiers The experimental results also show that the proposed method outperforms Fisherfaces and its speed for feature extraction is nearly 15 times faster than Fisherfaces Moreover, the experiments also demonstrate that the proposed method is robust in the uncontrolled lighting condition