计算技术与自动化2017，Vol.36Issue(2)：122-124,3.
基于特征脸的主成分分析人脸识别
Face Recognition Based on Principal Component Analysis with Eigenface
摘要
Abstract
The main work of this thesis is to determine whether a given image is a human face picture by using the eigenface approach-a face recognition method based on PCA (Principal Component Analysis).The approach calculate eigenvector (or eigenface) from the training set to obtain a subspace spanned by the eigenfaces,and then project the face images in training set onto the subspace.When detecting faces,the two-dimensional face image is projected onto the face space and the Euclidian distance between the image and the subspace is computed.If the distance under a chosen threshold,then the image is classified as a face image,the accuracy of the test results is 97.5%.关键词
人脸识别/特征脸/主成分分析Key words
face recognition/eigenface/principal component analysis分类
信息技术与安全科学引用本文复制引用
陈勇,林颖..基于特征脸的主成分分析人脸识别[J].计算技术与自动化,2017,36(2):122-124,3.基金项目
国家自然科学基金(61473318),广东省普通高校特色创新项目(2015KTSCX152),佛山市科技创新项目(2014AG10018) （61473318）
