Face Duplication Identifier Using Artificial Nerves

bit-Tech Pub Date : 2023-08-25 DOI:10.32877/bt.v6i1.899
S. R. C. Nursari, Rizki Rahmatunisa
{"title":"Face Duplication Identifier Using Artificial Nerves","authors":"S. R. C. Nursari, Rizki Rahmatunisa","doi":"10.32877/bt.v6i1.899","DOIUrl":null,"url":null,"abstract":"The facial recognition system develops a basic identity verification system based on the natural features of human faces. The study included duplicate passport identification, which checks each person's facial accuracy through a sample of facial data. The data used in this study were 180 face samples at the training stage and 30 face samples at the testing stage. The face sample taken is a forward-facing face that is not obstructed by an object. Face image recognition in this study combines GLCM method, color moment, shape extraction and backpropagation algorithm. The test process recognition rate is 78.83%.","PeriodicalId":405015,"journal":{"name":"bit-Tech","volume":"237 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"bit-Tech","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32877/bt.v6i1.899","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The facial recognition system develops a basic identity verification system based on the natural features of human faces. The study included duplicate passport identification, which checks each person's facial accuracy through a sample of facial data. The data used in this study were 180 face samples at the training stage and 30 face samples at the testing stage. The face sample taken is a forward-facing face that is not obstructed by an object. Face image recognition in this study combines GLCM method, color moment, shape extraction and backpropagation algorithm. The test process recognition rate is 78.83%.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于人工神经的人脸重复识别
人脸识别系统基于人脸的自然特征,开发了一个基本的身份验证系统。这项研究包括了重复的护照识别,通过面部数据样本来检查每个人的面部准确性。本研究使用的数据为180张训练阶段的人脸样本和30张测试阶段的人脸样本。所采集的面部样本为未被物体遮挡的正面面部。本研究中人脸图像识别结合了GLCM方法、颜色矩、形状提取和反向传播算法。测试过程识别率为78.83%。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Implementation Search Engine Optimization (SEO) to Improve Marketing F&B Industry Analysis And Design Of Online Based Plastic Sales Information System With User Acceptance Testing Method Design a Web-based Education Development Contribution Payment Application at SDIT Tahfidz Bintangku Clustering Mental Health on Instagram Users Using K-Means Algorithm Implementation of Business Intelligence In Analyzing Data Using Tableau at PT Global Bintan Permata
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1