Facial Recognition Attendance System

By identifying students' frontal faces from classroom photos, this research attempts to construct a general face detection and identification system that will automate the process of gathering school attendance. The main issue with conventional attendance management systems is the accuracy of the data that is gathered. Numerous automated techniques are in use, including biometric attendance. Nonetheless, the effectiveness of these methods is always impacted by scanning equipment technical issues. In order to enhance data quality and information accessibility for authorised parties, this article uses OpenCV for face recognition and principal component analysis techniques for face detection. The database that holds user data in the system was developed using SQL, while the Python programming language was utilised to create the suggested system. After testing, it was determined that the new system is safe and secures students' identities by providing an anonymous attendance environment.