FACIAL RECOGNITION

Attendance management in academic tertiary institutions is a critical administrative task that directly impacts the credibility of academic records. Traditional methods such as manual roster calls, paper-based attendance sheets, and ID card verification have proven inefficient, timeconsuming, and vulnerable to impersonation attendance fraud. This project highlights the necessity for automated attendance systems using modern technologies such as biometric verification, Radio Frequency Identification (RFID) tracking, and facial recognition. Considering the operational constraints and specific requirements of the University of Benin, Department of Computer Science, this project proposes a Web-Based Facial Recognition Attendance System as an optimal solution. The project focuses on implementing a functional prototype of the facial recognition attendance system, where students register their facial biometrics during enrollment and subsequently mark attendance by scanning their faces via a web-based application. The system follows an objectoriented approach to system analysis and design, utilizing use case diagrams, class diagrams, and sequence diagrams to model the system architecture. These designs form the foundation for a system capable of handling the complete attendance process from student authentication to generating real-time attendance reports for courses offered by the Department of Computer Science. The key features of this attendance system include real-time face detection, liveness verification to prevent bypass attempts, and geolocation validation to ensure attendance is marked within authorized locations. The system also provides administrative dashboards for attendance monitoring and analytics. By implementing this solution, the University of Benin would probably have achieved a more secure, efficient, and fraud-resistant attendance management system compared to conventional methods

Attendance tracking in classes is a very important activity in any institution, and taking attendance of students using facial recognition is a more efficient and accurate method than the traditional methods which includes paper- based and roll call methods. The facial recognition system is an application of computer vision that can perform two major tasks of identifying and verifying a person from a given database. Facial recognition proves to be more effective in taking attendance than the traditional method, which is inaccurate, time- consuming and vulnerable in most cases of large class environments. This system is designed with a login page for authentication, it also provides a mailing platform where the attendance will be sent to the school authority for record keeping. This study develops a deep-learning-based facial recognition system used to detect the face of students in a class environment for the sole purpose of taking their attendance records.