Aim:
The proposed work aims to monitor real-time attendance using face recognition in every institutional sector. It is one of the key concerns in every organization.
Background:
Nowadays, most organizations spend a lot of time marking attendance for a large number of individuals manually. Many technologies like Radio Frequency Identification (RFID), and biometric systems are introduced to overcome the manual attendance system. However, not all of these technologies are automatic, and people must queue to have their presence recorded.
Objective:
The main objective of the system is to provide an automated attendance system with the help of face recognition owing to the difficulty in the manual as well as other traditional attendance systems.
Methods:
The main objective of the system is to provide an automated attendance system with the help of face recognition owing to the difficulty in the manual as well as other traditional attendance systems.
Results:
Using the web camera connected to the computer, face detection and recognition are performed, and recognized faces are attended. Here, the admin module and teacher modules are implemented with different functionalities to monitor attendance.
Conclusion:
Experiment results get 94.5% accuracy of face detection and 98.5% accuracy of face recognition by using the Haarcascade classifier and LBPH algorithm. This application system will be simple to implement, accurate, and efficient in monitoring attendance in real-time.
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