Development of a student attendance system using face recognition

Face recognition systems are certainly an essential component of our digital world, finding use in a variety of applications due to their non-intrusive and contactless nature. Those systems are very popular despite the fact that they might not be as accurate as fingerprint or iris recognition. The development of a student attendance system is one such application that aims to replace the current manual procedure, which is known for its time-consuming and laborious nature. The proposed face recognition attendance system comprises four stages of processes: creating databases, detecting and recognizing faces, and updating attendance records. Initially, a database is built by taking students’ images in the class. Data collection and preprocessing are the first stages of the main algorithm in which machine learning is used. The primary algorithm in this system is trained and tested using a training set and a testing set respectively for performance assessment. The system offers many advantages, including increased efficiency, decreased administrative work, and improved attendance monitoring accuracy. Furthermore, it encourages a secure and contactless method to track attendance, addressing the changing requirements of workplaces, offices, and other sectors.