Face Recognition based Attendance System – A Deep Dive

Facial recognition software is becoming commonplace in today's workplaces. It has several applications, including security, authentication, and identity. The fact that it doesn't touch the user and is completely painless undoubtedly contributes to its universal adoption. Building access can be monitored with facial recognition technology in places like schools, offices, and government buildings. We intend to develop a facial recognition-based solution to replace the present tedious and time-consuming manual attendance tracking method. At the hearing, a different prosecutor can show up. As a result, there is expanding backing for further research into this strategy. Find a person in a database, get their personal information, and then pretend to be them online. Student portraits for the database are the students' heads. The LBPH technique and the Haar-Cascade classifier are combined for this purpose. Furthermore, this system encourages the machine learning models to significantly improve their face detection authenticity or accuracy even under poor lighting or in a situation of blocked view. The research can also be used in large institutions by supporting real-time monitoring and centralised attendance ranking. Also, data privacy is ensured through effective encryption techniques. This system can be further extended for emotion recognition and attendance behaviour analytics. This will only require minimal human intervention and the processing speed will be much faster. Consequently, it contributes to a secure technology-driven attendance ecosystem.