中文摘要：

在主成分分析方法（PCA）的基础上,采用3种神经网络（BP、RBF、LVQ）分类器进行人脸识别实验研究.实验中引入多数投票法（MVS）,构建了多分类器组合决策体系,对分类结果进行决策融合.最后,将使用此决策体系的人脸识别结果与使用单一分类器的人脸识别结果进行对比分析.分析结果显示,采用MVS规则的人脸识别系统,能有效提高人脸识别系统的准确率和稳定性,且方法简单可行.

英文摘要：

Based on Principal Component Analysis Method,three neural network（BP、RBF、LVQ）classifiers are adopted in the recognition of human faces.A multi-classifier combination decision system is built with Majority Voting Scheme,through which a combination decision on the classified results can be made.In the end,the face recognition result by using this method is analyzed by comparison with that by using single classifier.The analysis shows that this method can effectively improve the recognition accuracy and stability and that the method is convenient and workable.