Person Identification from Ear Images Using Convolutional Neural Networks

Natchapon Petaitiemthong, Potsawat Chuenpet, S. Auephanwiriyakul, N. Theera-Umpon
{"title":"Person Identification from Ear Images Using Convolutional Neural Networks","authors":"Natchapon Petaitiemthong, Potsawat Chuenpet, S. Auephanwiriyakul, N. Theera-Umpon","doi":"10.1109/ICCSCE47578.2019.9068569","DOIUrl":null,"url":null,"abstract":"Nowadays, biometric identification is utilized in several applications especially in security system. One of the recently popular biometric identifications is person identification from ear because each person has a unique ear and it does not change overtime. In addition, we believe that not only side view ear image is useful in identifying a person, but a front view ear image is also useful. Hence, in this paper, we develop two convolutional neural networks (CNNs) schemes to recognize front view and side view human ear. From the blind test data set results, we found that the system based on front view images provides 84% correct. Meanwhile, the side view image-based system yields 80% correct classification on the same data set.","PeriodicalId":221890,"journal":{"name":"2019 9th IEEE International Conference on Control System, Computing and Engineering (ICCSCE)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 9th IEEE International Conference on Control System, Computing and Engineering (ICCSCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSCE47578.2019.9068569","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

Nowadays, biometric identification is utilized in several applications especially in security system. One of the recently popular biometric identifications is person identification from ear because each person has a unique ear and it does not change overtime. In addition, we believe that not only side view ear image is useful in identifying a person, but a front view ear image is also useful. Hence, in this paper, we develop two convolutional neural networks (CNNs) schemes to recognize front view and side view human ear. From the blind test data set results, we found that the system based on front view images provides 84% correct. Meanwhile, the side view image-based system yields 80% correct classification on the same data set.
利用卷积神经网络从耳朵图像中识别人
目前,生物特征识别在安防系统中得到了广泛的应用。最近流行的一种生物识别技术是人耳识别,因为每个人都有一个独特的耳朵,而且不会随着时间的推移而改变。此外,我们认为,不仅侧视图耳图像是有用的识别一个人,但正面视图耳图像也很有用。因此,在本文中,我们开发了两种卷积神经网络(cnn)方案来识别人耳的正面视图和侧面视图。从盲测数据集的结果来看,我们发现基于前视图像的系统正确率为84%。同时,基于侧视图的系统在同一数据集上的分类正确率达到80%。
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 求助全文
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:604180095
Book学术官方微信