Class Attendance Management System Using Face Recognition

Omar Abdul Rhman Salim, R. F. Olanrewaju, Wasiu Adebayo Balogun
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引用次数: 53

Abstract

We are living in a world where everything is automated and linked online. The internet of things, image processing, and machine learning are evolving day by day. Many systems have been completely changed due to this evolve to achieve more accurate results. The attendance system is a typicalexample of this transition, starting from the traditional signature on a paper sheet to face recognition. This paper proposes a method of developing a comprehensive embedded class attendance systemusing facial recognition with controlling the door access. The system is based on Raspberry Pi thatruns Raspbian (Linux) Operating System installed on micro SD card. The Raspberry Pi Camera, as well as a 5-inch screen, are connected to the Raspberry Pi. By facing the camera, the camera will capture the image then pass it to the Raspberry Pi which is programmed to handle the face recognition by implementing the Local Binary Patterns algorithm LBPs. If the student’s input image matches withthetrained dataset image the prototype door will open using Servo Motor, then the attendance results will be stored in the MySQL database. The database is connected to Attendance Management Syste(AMS) web server, which makes the attendance results reachable to any online connected web browser.The system has 95{\% accuracy with the dataset of 11 person images.
基于人脸识别的班级考勤管理系统
我们生活在一个一切都是自动化和在线连接的世界。物联网、图像处理和机器学习正在一天天发展。由于这种演变,许多系统已经完全改变,以获得更准确的结果。考勤系统就是这种转变的一个典型例子,从传统的在纸上签名到人脸识别。本文提出了一种基于人脸识别的综合嵌入式考勤系统的开发方法。本系统基于Raspberry Pi,运行安装在micro SD卡上的Raspbian (Linux)操作系统。树莓派的摄像头,以及一个5英寸的屏幕,连接到树莓派。通过面对相机,相机将捕获图像,然后将其传递给树莓派,树莓派被编程为通过实现局部二进制模式算法lbp来处理人脸识别。如果学生输入的图像与训练数据集图像匹配,则原型门将使用伺服电机打开,然后出勤结果将存储在MySQL数据库中。数据库连接到考勤管理系统(AMS) web服务器,使任何在线连接的web浏览器都可以访问考勤结果。该系统对11个人图像数据集的准确率为95%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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