This method emphasizes and gives prominence to features which own higher discriminatory power, so the recognition accuracy is enhanced in the low dimension space.
该方法着重强调和突出判别能量较高的特征，从而提高在低维空间的人脸识别正确率。
This method reduces the number of space dimension, makes the equation system lower order, less data input and higher efficiency .
边界单元法降低了求解空间的维数，减少了离散线性方程组的阶数，输入数据比较少，而工作效率高。
The result indicated: the method has a higher recognition rate than the traditional LDA and PCA in the lower dimension space.
实验表明，本文提出的方法在低维空间比传统LDA和PCA有更高的识别正确率。
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