基于神经分类器的人脸识别系统

Xiaoyin Xu, M. Ahmadi
{"title":"基于神经分类器的人脸识别系统","authors":"Xiaoyin Xu, M. Ahmadi","doi":"10.1109/CGIV.2007.6","DOIUrl":null,"url":null,"abstract":"Traditional subspace methods for face recognition, from the original eigenfaces technique to the recently introduced Laplacian faces method, measure the similarity between images after projecting them onto a face subspace. In this paper, we present a robust face recognition system that uses a neural classifier and Laplacian faces method. Computer simulation shows that the proposed algorithm has better noise immunity and yields higher recognition rate compared with several conventional face recognition algorithms.","PeriodicalId":433577,"journal":{"name":"Computer Graphics, Imaging and Visualisation (CGIV 2007)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"A Human Face Recognition System Using Neural Classifiers\",\"authors\":\"Xiaoyin Xu, M. Ahmadi\",\"doi\":\"10.1109/CGIV.2007.6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Traditional subspace methods for face recognition, from the original eigenfaces technique to the recently introduced Laplacian faces method, measure the similarity between images after projecting them onto a face subspace. In this paper, we present a robust face recognition system that uses a neural classifier and Laplacian faces method. Computer simulation shows that the proposed algorithm has better noise immunity and yields higher recognition rate compared with several conventional face recognition algorithms.\",\"PeriodicalId\":433577,\"journal\":{\"name\":\"Computer Graphics, Imaging and Visualisation (CGIV 2007)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer Graphics, Imaging and Visualisation (CGIV 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CGIV.2007.6\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Graphics, Imaging and Visualisation (CGIV 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CGIV.2007.6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

传统的人脸识别子空间方法,从最初的特征脸技术到最近引入的拉普拉斯人脸方法,都是在将图像投影到人脸子空间后测量图像之间的相似性。本文提出了一种基于神经分类器和拉普拉斯人脸方法的鲁棒人脸识别系统。计算机仿真结果表明,与几种传统的人脸识别算法相比,该算法具有更好的抗噪性和更高的识别率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Human Face Recognition System Using Neural Classifiers
Traditional subspace methods for face recognition, from the original eigenfaces technique to the recently introduced Laplacian faces method, measure the similarity between images after projecting them onto a face subspace. In this paper, we present a robust face recognition system that uses a neural classifier and Laplacian faces method. Computer simulation shows that the proposed algorithm has better noise immunity and yields higher recognition rate compared with several conventional face recognition algorithms.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信