Pose, illumination and expression invariant face recognition using laplacian of Gaussian and Local Binary Pattern

Pradip Panchal, Palak Patel, V. Thakkar, Rachna Gupta
{"title":"Pose, illumination and expression invariant face recognition using laplacian of Gaussian and Local Binary Pattern","authors":"Pradip Panchal, Palak Patel, V. Thakkar, Rachna Gupta","doi":"10.1109/NUICONE.2015.7449622","DOIUrl":null,"url":null,"abstract":"This paper presents an effective approach for the application of Face Recognition using Local Binary Pattern operator. The face image is firstly divided in to the sub regions to generate the locally enhanced Local Binary Histogram, which provide the features information on pixel level by creating LBP labels for histogram. Global Local Binary Histogram for the entire face image is obtained by concatenating all the individual local histograms. As a pre-processing technique the differential excitation of pixel is used to make the algorithm invariant to the illumination changes. The performance of the algorithm is verified under constrains like pose, illumination and expression variation.","PeriodicalId":131332,"journal":{"name":"2015 5th Nirma University International Conference on Engineering (NUiCONE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 5th Nirma University International Conference on Engineering (NUiCONE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NUICONE.2015.7449622","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13

Abstract

This paper presents an effective approach for the application of Face Recognition using Local Binary Pattern operator. The face image is firstly divided in to the sub regions to generate the locally enhanced Local Binary Histogram, which provide the features information on pixel level by creating LBP labels for histogram. Global Local Binary Histogram for the entire face image is obtained by concatenating all the individual local histograms. As a pre-processing technique the differential excitation of pixel is used to make the algorithm invariant to the illumination changes. The performance of the algorithm is verified under constrains like pose, illumination and expression variation.
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
基于拉普拉斯高斯和局部二值模式的姿态、光照和表情不变人脸识别
提出了一种应用局部二值模式算子进行人脸识别的有效方法。首先将人脸图像划分为子区域,生成局部增强的局部二值直方图,通过对直方图创建LBP标签来提供像素级的特征信息;整个人脸图像的全局局部二值直方图是由所有的局部直方图拼接而成的。作为一种预处理技术,利用像素的差分激励使算法不受光照变化的影响。在姿态、光照和表情变化等约束条件下验证了算法的性能。
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
Brain computer interface: A review A comparative study of various community detection algorithms in the mobile social network TCP with sender assisted delayed acknowledgement — A novel ACK thinning scheme Data streams and privacy: Two emerging issues in data classification ANFIS as a controller for fractional order system
×
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