Anti-Spoofing Face-Recognition Technique for eKYC Application

Sudarshan Paul, P. Bruntha, A. Raj, Saurabh Saurabh, Samarpit Masih
{"title":"Anti-Spoofing Face-Recognition Technique for eKYC Application","authors":"Sudarshan Paul, P. Bruntha, A. Raj, Saurabh Saurabh, Samarpit Masih","doi":"10.1109/ICSPC51351.2021.9451703","DOIUrl":null,"url":null,"abstract":"This paper presents a module of eKYC (Electronic Know Your Customer) system using face recognition for identification and authentication of an individual from a variety of digital sources. The proposed method implements the Local Binary Pattern Histogram (LBPH) algorithm to solve the face recognition problem. The recognition rate varies under lighting conditions, facial expression, attitude deflection and transformations. The anti- spoofing system is based on a proposed Convolution Neural Network (CNN) based architecture. The accuracy of the proposed system is 95%.","PeriodicalId":182885,"journal":{"name":"2021 3rd International Conference on Signal Processing and Communication (ICPSC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 3rd International Conference on Signal Processing and Communication (ICPSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSPC51351.2021.9451703","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

This paper presents a module of eKYC (Electronic Know Your Customer) system using face recognition for identification and authentication of an individual from a variety of digital sources. The proposed method implements the Local Binary Pattern Histogram (LBPH) algorithm to solve the face recognition problem. The recognition rate varies under lighting conditions, facial expression, attitude deflection and transformations. The anti- spoofing system is based on a proposed Convolution Neural Network (CNN) based architecture. The accuracy of the proposed system is 95%.
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
eKYC应用中的抗欺骗人脸识别技术
本文介绍了eKYC (Electronic Know Your Customer)系统的一个模块,该系统使用人脸识别对来自各种数字来源的个人进行身份识别和认证。该方法采用局部二值模式直方图(LBPH)算法来解决人脸识别问题。在光照条件、面部表情、姿态偏转和变换的情况下,识别率会发生变化。该防欺骗系统基于一种基于卷积神经网络(CNN)的架构。该系统的准确率为95%。
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
Investigation on Maternal and Fetal Heart Signal Extraction Using Adaptive Filtering Techniques and Integrating with Block Sparse Bayesian Learning Implementation of Machine Learning Algorithms For Human Activity Recognition Study on Public Chest X-ray Data sets for Lung Disease Classification Optimized Transmission Line Flaw Disclosure and Inkling System Based on IOT CNN Architecture for Diabetes Classification
×
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:604180095
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