Student Attendance System Using Face Recognition

Abstract

Manually recording attendance in educational institutions takes a lot of time and is prone to mistakes. This project showcases a Python-based face recognition-based automated student attendance system. To detect and identify students' faces with high accuracy, the system makes use of the face-recognition library and OpenCV for real- time image capture. The system automatically logs attendance in a CSV/Excel file with the student's name, date, and time after successful identification. In addition to ensuring safe and effective attendance management, the suggested solution increases accuracy and decreases human labor. A database or web-based interface can be added to expand it further for widespread use in smart classrooms. It involves capturing images through web cam then it trains the image and marks the attendance in dashboard.