基于人脸检测与识别的考勤系统新方法

M. Ghareb, Dyaree Jamal Hamid, Sako Dilshad Sabr, Zhyar Tofiq
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引用次数: 0

摘要

图像处理最有益的用途之一是人脸识别,这在当今的技术环境中是必不可少的。特别是在跟踪学生出勤方面,人脸识别是身份验证领域的一个热门问题。人脸识别考勤系统是一种基于高清监控和其他使用人脸生物统计学的计算机技术来识别学生的技术。建立这个系统的目的是用电子方式取代传统的点名和保存纸质记录的考勤程序。现有的考勤程序既繁琐又费时。本文的目标和目标是使用OpenCV库开发一个考勤管理系统,该系统可以识别人脸并将其存储在数据库中,以便大学、企业和其他机构可以使用它来跟踪考勤情况。本研究将采用Open CV和HOG库相结合的方法对边界框内的人脸进行检测,准确率为99.38 %。此外,它还提出了在任何教育机构的所有大厅和实验室使用这些技术来准确记录学生出勤的新想法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
New approach for Attendance System using Face Detection and Recognition
One of the most beneficial uses of image processing is face recognition, which is essential in today's technology environment. Particularly when it comes to tracking student attendance, the identification of a human face is a popular issue in the authentication sector. A face recognition attendance system is a technique for identifying pupils based on high-definition surveillance and other computer technologies that employ face biostatistics. The purpose of creating this system is to electronically replace the conventional procedure of recording attendance by calling names and maintaining paper records. The existing procedures for taking attendance are cumbersome and time-consuming. Our goal and ambition for this article is to use the OpenCV library to develop an attendance management system that can identify faces and store them in a database so that colleges, businesses, and other institutions may use it to track attendance. This research will use a combination method of using Open CV and HOG library detecting the face in boundary box with accuracy %99.38. Adding more, it has been proposing new idea of using these techniques in all halls and labs in any educational institutes in recording the student's attendance precisely.
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CiteScore
0.50
自引率
0.00%
发文量
23
审稿时长
12 weeks
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