Automatic Face Recognition Attendance System using Python and Open CV

Abstract

The primary goal of this project is to develop a face recognition-based attendance monitoring system for educational institutions, aiming to improve and modernize the current attendance procedures, making them more efficient and effective. The existing system suffers from ambiguities that lead to inaccuracies and inefficiencies in attendance recording. Numerous issues arise when authorities cannot enforce the regulations of the old system. This project leverages face recognition technology to address these problems. During attendance sessions, the system will compare faces against a database to verify identities. Once an individual is identified, their attendance will be automatically recorded, with the necessary information in an Excel sheet. This automated system aids faculty in taking attendance for the entire class without causing any disruption or wasting time. We propose and have implemented a smart attendance system with the potential to incorporate Quick Response (QR) codes as a future method for managing attendance. This system aims to streamline and document student attendance during lectures and other activities across all relevant courses. At the end of the day, the Excel sheet containing attendance details for all individuals will be emailed to the respective faculty members.