模糊支持向量机和独立成分分析在人脸识别中的应用

Fuzzy Support Vector Machine and Independent Component Analysis for Face Recognition

将独立成分分析(ICA)、模糊支持向量机(FSVM)以及三叉决策树相结合并应用于人脸识别。首先对人脸图像做独立成分分析,提取有利于分类的面部特征的主要独立成分,然后在特征空间中,用FSVM和三叉决策树相结合设计人脸分类器。在ORL人脸库上的实验结果表明,该算法能够取得较好的分类效果。

Proposes a face recognition method which combines independent component analysis(ICA),fuzzy support vector machine(FSVM) and triple decision tree. First,the ICA method is used to get the representation basis of face image set,and then a classifier is designed on the feature space by using the combination of FSVM and triple decision tree. The result of the experiment on ORL face images indicates that the proposed method has good classification performance.