摘要
提出了一种基于人脸重要特征的人脸识别方法,首先选取人脸的重要特征并将其具体化,对得到的重要特征进行主成分分析,然后用支持向量机(Support Vector Machine,SVM)设计重要特征分类器来确定测试人脸图像中重要特征,同时设计支持向量机(SVM)人脸分类器,确定人脸图像的所属类别.对ORL人脸图像数据库进行仿真实验,结果表明,该方法要优于一般的基于整体特征的人脸识别方法并有较强的鲁棒性.
A method for face recognition based on face important features proposed in this paper. At first selecting face important feature of regional and then the principle component analysis （PCA） coefficients are extracted as feature vectors from the face component image, then support vector machine （SVM） is used to train features and face recognition machine. Features classification machine distinguishes the component regions in the face image, and face classification machine determines which person the image should belong to. Some experiments have been made on the ORL face image database, This method has better recognition precision.
出处
《应用数学与计算数学学报》
2008年第1期109-114,共6页
Communication on Applied Mathematics and Computation
基金
上海市教委发展基金(项目编号:214665)
关键词
人脸识别
支持向量机
主成分分析
face recognition, support vector machine, principle component analysis
