Neural network face recognition using statistical feature extraction

S. El-Khamy, O. Abdel-Alim, M. Saii
{"title":"Neural network face recognition using statistical feature extraction","authors":"S. El-Khamy, O. Abdel-Alim, M. Saii","doi":"10.1109/NRSC.2000.838960","DOIUrl":null,"url":null,"abstract":"Recognition method of human face using statistical analysis feature extraction and a neural network algorithm is proposed. In the preprocessing step we detect the edges of the face image by using the Sobel algorithm. Then we propose a new method to transform the two-dimension black and white image to a one-dimension vector. Finally, based on the statistical analysis, we extract seven features. In the recognition step we use the fast backpropagation (FBP) algorithm. Computer simulation results with 100 test images of 10 persons (the images of each person in a various pauses, facial expression, and facial details) show that the proposed method yields a high recognition rate.","PeriodicalId":211510,"journal":{"name":"Proceedings of the Seventeenth National Radio Science Conference. 17th NRSC'2000 (IEEE Cat. No.00EX396)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2000-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Seventeenth National Radio Science Conference. 17th NRSC'2000 (IEEE Cat. No.00EX396)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NRSC.2000.838960","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14

Abstract

Recognition method of human face using statistical analysis feature extraction and a neural network algorithm is proposed. In the preprocessing step we detect the edges of the face image by using the Sobel algorithm. Then we propose a new method to transform the two-dimension black and white image to a one-dimension vector. Finally, based on the statistical analysis, we extract seven features. In the recognition step we use the fast backpropagation (FBP) algorithm. Computer simulation results with 100 test images of 10 persons (the images of each person in a various pauses, facial expression, and facial details) show that the proposed method yields a high recognition rate.
基于统计特征提取的神经网络人脸识别
提出了一种基于统计分析、特征提取和神经网络的人脸识别方法。在预处理步骤中,我们使用Sobel算法检测人脸图像的边缘。然后提出了一种将二维黑白图像变换为一维矢量的新方法。最后,在统计分析的基础上,提取出7个特征。在识别步骤中,我们使用快速反向传播(FBP)算法。计算机仿真结果表明,该方法具有较高的识别率,其中包括10个人的100张测试图像(每个人在各种停顿、面部表情和面部细节中的图像)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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:481959085
Book学术官方微信