{"title":"Smart Anti-Theft Door locking System","authors":"S. Jahnavi, C. Nandini","doi":"10.1109/ICATIECE45860.2019.9063836","DOIUrl":null,"url":null,"abstract":"Privacy and security are two pivotal rights in day-to-day life. At present, keys, passwords and PIN’s are used to secure the confidential data. However the above mentioned methods can be compromised and thus propose threats to security. This paper provides an advanced method to enhance the security system using face detection and recognition algorithms integrated with raspberry pi that is used to control the access to the door. Since face is indubitably related to an individual, it cannot be duplicated. This paper consists of three subsystems-Face detection, Feature extraction and Face recognition for door access. Initially the system is trained with authorized persons features, stored in the database. Firstly, the process is started by capturing the image of an object using raspberry pi camera followed by face detection done using Viola Jones algorithm as it provides a greater accuracy in real-time object detection. Next the feature extraction and face detection is done using Local Binary Pattern (LBP) algorithm that can extract local neighboring texture information of grey scale image and can efficiently differentiate between object and background. The extracted features are dimensionally reduced using Principal Component Analysis (PCA) algorithm .The detected face is compared against the stored features and if there is a match the access is provided to the authorized person. If not, the access to the door is denied and an alarm is raised alerting the admin.","PeriodicalId":106496,"journal":{"name":"2019 1st International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 1st International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICATIECE45860.2019.9063836","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

Privacy and security are two pivotal rights in day-to-day life. At present, keys, passwords and PIN’s are used to secure the confidential data. However the above mentioned methods can be compromised and thus propose threats to security. This paper provides an advanced method to enhance the security system using face detection and recognition algorithms integrated with raspberry pi that is used to control the access to the door. Since face is indubitably related to an individual, it cannot be duplicated. This paper consists of three subsystems-Face detection, Feature extraction and Face recognition for door access. Initially the system is trained with authorized persons features, stored in the database. Firstly, the process is started by capturing the image of an object using raspberry pi camera followed by face detection done using Viola Jones algorithm as it provides a greater accuracy in real-time object detection. Next the feature extraction and face detection is done using Local Binary Pattern (LBP) algorithm that can extract local neighboring texture information of grey scale image and can efficiently differentiate between object and background. The extracted features are dimensionally reduced using Principal Component Analysis (PCA) algorithm .The detected face is compared against the stored features and if there is a match the access is provided to the authorized person. If not, the access to the door is denied and an alarm is raised alerting the admin.
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
智能防盗门锁系统
隐私和安全是日常生活中的两项关键权利。目前,使用密钥、密码和PIN码来保护机密数据。然而,上述方法可能被破坏,从而对安全构成威胁。本文提供了一种先进的方法来增强安全系统的人脸检测和识别算法集成的树莓派,用于控制门禁。因为脸无疑与个人有关,所以它不能被复制。本文主要包括人脸检测、人脸特征提取和人脸识别三个子系统。最初,系统被训练具有授权人员的特征,并存储在数据库中。首先,这个过程是通过使用树莓派相机捕捉物体的图像开始的,然后使用维奥拉琼斯算法进行人脸检测,因为它在实时物体检测中提供了更高的精度。其次,采用局部二值模式(LBP)算法进行特征提取和人脸检测,该算法能够提取灰度图像的局部相邻纹理信息,能够有效区分目标和背景;使用主成分分析(PCA)算法对提取的特征进行降维。将检测到的人脸与存储的特征进行比较,如果存在匹配,则向授权人员提供访问权限。如果没有,则拒绝访问该门,并发出警报,提醒管理员。
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
Customer Experience Enhancement Using Artificial Intelligence A Comprehensive Survey on Multi Object Tracking Under Occlusion in Aerial Image Sequences Smart Vehicle Driving System using Computer Vision based Hand Motion Tracking UIDBA: Unique Identity & Biometric Based Architecture for E-governance Solutions An Agent Cluster Based Routing Protocol for Enhancing Lifetime of Wireless Sensor Network
×
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