文章基本信息

标题：Kernel Principle Component Analysis in Face Recognition System: A Survey
本地全文：下载
作者：Ritu Upadhayay ; Rakesh Kumar Yadav
期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2013
卷号：3
期号：6
出版社：S.S. Mishra
摘要：Face recognition is a dynamic topic in the fields of biometrics. Many achievements have been obtained in face recognition. Principal Components Analysis (PCA) and kernel principal components Analysis (KPCA) is a elementary technique broadly used in face feature extraction and recognition. This research paper presents nitty-gritty of KPCA and an up to date review of techniques KPCA. Papers also notify benefits of KPCA over PCA. Finally, it finds that it is appropriate technique in face recognition system. Therefore, it will be a possibility to seek a good system using this approach.
关键词：kernel; principal components Analysis; PCA; KPCA; Face recognition