A face detection system based on principal component analysis algorithm and neural net‐work techniques ,a different technique of recognizing the characteristic points was put forward .The de‐tection system was used to feature extraction ,principal component analysis and artificial neural net‐work ,the eigenfaces methods and the algorithm were paid on face recognition .In the algorithm ,the characteristic vectors and the eigenfaces were obtained by recognizing the images from the initial face im‐age set ,and these faces are projected onto the eigenfaces for calculating the weights .These weights cre‐ated a face database to recognize the face by using neural network .The test result showed that the accu‐racy w as 82% ,achieved the ideal result .%当前人脸检测系统主要使用的是基于主成分分析算法和神经网络技术，本文提出了识别不同特征点的另一种技术，所提出的识别系统用来实现特征提取、主成分分析和人工神经网络，即用特征脸和主成分分析算法进行人脸识别．在主成分分析算法中，通过识别初始人脸图像集得到特征向量和特征脸，然后这些人脸被投射到特征脸上以计算权重，这些权重建立人脸数据库以便通过神经网络进行人脸识别．测试结果表明，其准确率达82．1％，达到了理想效果．
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