基于局部二值模式图像的光照归一化

Y. Cheng, Zhigang Jin, Cunming Hao
{"title":"基于局部二值模式图像的光照归一化","authors":"Y. Cheng, Zhigang Jin, Cunming Hao","doi":"10.1109/IHMSC.2012.29","DOIUrl":null,"url":null,"abstract":"This paper presents a novel and efficient illumination normalization method based on the local binary pattern Image (LBPI). LBPI is a global description combined by the descriptions of every points in the face image using the local binary pattern (LBP) Compared with the traditional approaches, the experimental results show that our algorithms can significantly improve the performance of face recognition under varying illumination conditions on Yale Face database B.","PeriodicalId":431532,"journal":{"name":"2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Illumination Normalization Based on Local Binary Pattern Image\",\"authors\":\"Y. Cheng, Zhigang Jin, Cunming Hao\",\"doi\":\"10.1109/IHMSC.2012.29\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a novel and efficient illumination normalization method based on the local binary pattern Image (LBPI). LBPI is a global description combined by the descriptions of every points in the face image using the local binary pattern (LBP) Compared with the traditional approaches, the experimental results show that our algorithms can significantly improve the performance of face recognition under varying illumination conditions on Yale Face database B.\",\"PeriodicalId\":431532,\"journal\":{\"name\":\"2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IHMSC.2012.29\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IHMSC.2012.29","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

提出了一种基于局部二值模式图像(LBPI)的光照归一化方法。LBPI是利用局部二值模式(local binary pattern, LBP)对人脸图像中每个点的描述组合而成的一种全局描述。与传统方法相比,在耶鲁人脸数据库B上,实验结果表明,我们的算法可以显著提高在不同光照条件下的人脸识别性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Illumination Normalization Based on Local Binary Pattern Image
This paper presents a novel and efficient illumination normalization method based on the local binary pattern Image (LBPI). LBPI is a global description combined by the descriptions of every points in the face image using the local binary pattern (LBP) Compared with the traditional approaches, the experimental results show that our algorithms can significantly improve the performance of face recognition under varying illumination conditions on Yale Face database B.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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