红外图像分析用于人脸识别

Muhammad Eka Setio Aji, R. Alfanz, E. Prakasa
{"title":"红外图像分析用于人脸识别","authors":"Muhammad Eka Setio Aji, R. Alfanz, E. Prakasa","doi":"10.1109/icci54321.2022.9756103","DOIUrl":null,"url":null,"abstract":"Thermal infrared images have potential to captured the images without being affected by illumination. In this paper, we proposed a face recognition method using infrared images. The Convolution Neural Network are used to extract feature from the images with the combination of Haar Cascade, and Local Binary Pattern to indicate the face area. At the same time, images were acquired by using infrared camera and webcam. Compared between infrared and visible images, the experimental result from infrared images by using Convolutional Neural Network in combined with Haar Cascade show superiority in the measurement result of several parameters used with the highest score in accuracy up to 98% which outperforms the other experiment in this paper.","PeriodicalId":122550,"journal":{"name":"2022 5th International Conference on Computing and Informatics (ICCI)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Infrared Image Analysis for Human Face Recognition\",\"authors\":\"Muhammad Eka Setio Aji, R. Alfanz, E. Prakasa\",\"doi\":\"10.1109/icci54321.2022.9756103\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Thermal infrared images have potential to captured the images without being affected by illumination. In this paper, we proposed a face recognition method using infrared images. The Convolution Neural Network are used to extract feature from the images with the combination of Haar Cascade, and Local Binary Pattern to indicate the face area. At the same time, images were acquired by using infrared camera and webcam. Compared between infrared and visible images, the experimental result from infrared images by using Convolutional Neural Network in combined with Haar Cascade show superiority in the measurement result of several parameters used with the highest score in accuracy up to 98% which outperforms the other experiment in this paper.\",\"PeriodicalId\":122550,\"journal\":{\"name\":\"2022 5th International Conference on Computing and Informatics (ICCI)\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-03-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 5th International Conference on Computing and Informatics (ICCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/icci54321.2022.9756103\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 5th International Conference on Computing and Informatics (ICCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/icci54321.2022.9756103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

热红外图像具有不受光照影响而捕获图像的潜力。本文提出了一种基于红外图像的人脸识别方法。利用卷积神经网络结合哈尔级联和局部二值模式从图像中提取特征来表示人脸区域。同时利用红外摄像机和网络摄像机采集图像。将红外图像与可见光图像进行对比,利用卷积神经网络结合Haar级联对红外图像进行的实验结果在多个参数的测量结果上显示出优越性,准确率最高达到98%,优于本文的其他实验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Infrared Image Analysis for Human Face Recognition
Thermal infrared images have potential to captured the images without being affected by illumination. In this paper, we proposed a face recognition method using infrared images. The Convolution Neural Network are used to extract feature from the images with the combination of Haar Cascade, and Local Binary Pattern to indicate the face area. At the same time, images were acquired by using infrared camera and webcam. Compared between infrared and visible images, the experimental result from infrared images by using Convolutional Neural Network in combined with Haar Cascade show superiority in the measurement result of several parameters used with the highest score in accuracy up to 98% which outperforms the other experiment in this paper.
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