Multi-object face recognition using Content Based Image Retrieval (CBIR)

M. Fachrurrozi, Erwin, Saparudin, Mardiana
{"title":"Multi-object face recognition using Content Based Image Retrieval (CBIR)","authors":"M. Fachrurrozi, Erwin, Saparudin, Mardiana","doi":"10.1109/ICECOS.2017.8167132","DOIUrl":null,"url":null,"abstract":"Real-time face recognition system process divided into three steps, feature extraction, clustering, detection, and recognition. Each step uses a different method that is Local Binary Pattern (LBP), Agglomerative Hierarchical Clustering (AHC) and Euclidean Distance. Content Based Image Retrieval (CBIR), an image searching techniques based on image feature, is implemented as the searching method. Based experiments and the testing result, recall and precision values are 65.32% and 64.93% respectively.","PeriodicalId":6528,"journal":{"name":"2017 International Conference on Electrical Engineering and Computer Science (ICECOS)","volume":"5 1","pages":"193-197"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Electrical Engineering and Computer Science (ICECOS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECOS.2017.8167132","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 24

Abstract

Real-time face recognition system process divided into three steps, feature extraction, clustering, detection, and recognition. Each step uses a different method that is Local Binary Pattern (LBP), Agglomerative Hierarchical Clustering (AHC) and Euclidean Distance. Content Based Image Retrieval (CBIR), an image searching techniques based on image feature, is implemented as the searching method. Based experiments and the testing result, recall and precision values are 65.32% and 64.93% respectively.
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
基于内容图像检索(CBIR)的多目标人脸识别
实时人脸识别系统的过程分为三个步骤,特征提取、聚类、检测和识别。每一步使用不同的方法,即局部二值模式(LBP)、聚类层次聚类(AHC)和欧几里得距离。基于内容的图像检索(CBIR)是一种基于图像特征的图像检索技术。基于实验和测试结果,查全率和查准率分别为65.32%和64.93%。
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
Lightning data mapping of West Java province Android-based application using mobile adhoc network for search and rescue operation during disaster Monitoring system of stand alone solar photovoltaic data Approaches for improving VoIP QoS in WMNs Smart monitoring apps for salvaging neolissochillus thienemanni sumateranus (batak heritage) from extinction
×
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