Face-recognition System Design and Manufacture

Menq-Jiun Wu, Ye Chen, Yi-Sheng Liao, Jun-An Chen, Hao-Han Lin
{"title":"Face-recognition System Design and Manufacture","authors":"Menq-Jiun Wu, Ye Chen, Yi-Sheng Liao, Jun-An Chen, Hao-Han Lin","doi":"10.1109/SNPD51163.2021.9705014","DOIUrl":null,"url":null,"abstract":"The theory of face recognition is mainly from the idea of feature vectors. The face image is converted into a series of numbers to form a feature vector. For a feature vector of a face image, its content includes various features, such as: face height, face width, average face color, lips width, and nose height. The face-recognition operation is to compare the input of the feature vector of a face image with a large number of feature vectors in a dataset to identify the personal identity.The face recognition system in this paper is mainly implemented in the Python environment. Face generation is achieved by selfie of face. The image is cut to retain the part of the face, and stored in the database. Comparing the face image input with those saved in the dataset, if the similarity value passes the threshold value of true. The program will show the face image identification. Otherwise, the system will display a false message. The face recognition system is completed and the experimental results show the correct face-recognition. Finally the laptop Webcam is used to take the face image, and the result of comparison is also correct.","PeriodicalId":235370,"journal":{"name":"2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SNPD51163.2021.9705014","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

The theory of face recognition is mainly from the idea of feature vectors. The face image is converted into a series of numbers to form a feature vector. For a feature vector of a face image, its content includes various features, such as: face height, face width, average face color, lips width, and nose height. The face-recognition operation is to compare the input of the feature vector of a face image with a large number of feature vectors in a dataset to identify the personal identity.The face recognition system in this paper is mainly implemented in the Python environment. Face generation is achieved by selfie of face. The image is cut to retain the part of the face, and stored in the database. Comparing the face image input with those saved in the dataset, if the similarity value passes the threshold value of true. The program will show the face image identification. Otherwise, the system will display a false message. The face recognition system is completed and the experimental results show the correct face-recognition. Finally the laptop Webcam is used to take the face image, and the result of comparison is also correct.
人脸识别系统设计与制造
人脸识别的理论主要来源于特征向量的思想。将人脸图像转换成一系列数字,形成特征向量。对于人脸图像的特征向量,其内容包括各种特征,如:人脸高度、人脸宽度、平均面部颜色、嘴唇宽度和鼻子高度。人脸识别操作是将人脸图像的特征向量输入与数据集中大量的特征向量进行比较,从而识别出个人身份。本文的人脸识别系统主要是在Python环境下实现的。人脸生成是通过脸部自拍实现的。图像被切割以保留人脸的部分,并存储在数据库中。将输入的人脸图像与数据集中保存的人脸图像进行比较,如果相似度值超过阈值true。该程序将显示人脸图像识别。否则,系统将显示错误信息。完成了人脸识别系统的设计,实验结果表明,人脸识别是正确的。最后利用笔记本电脑摄像头拍摄人脸图像,对比结果也是正确的。
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