This graduation project is the work of the student Ezz Eldin Khalid Mahmoud from the Systems Engineering Department, supervised by Asst. Prof. Dr. Ammar Ibrahim. 

In today’s educational landscape, ensuring accurate and efficient tracking of student attendance is crucial. Traditional attendance methods, such as manual roll calls or ID-based systems, often prove to be time-consuming and susceptible to human error. This graduation project, titled “Design and Implementation of Class Attendance System Based on OpenCV”, presents a modern solution through the development of an automated attendance system using facial recognition technologies.

The system employs OpenCV for real-time face detection and leverages the face_recognition library to identify students. A webcam captures live video as students enter the classroom, enabling the system to detect and match faces against a pre-registered database. When a student’s face is successfully recognized, a green rectangle appears around the face displaying the student’s name, and the attendance is automatically recorded in an Excel file along with a timestamp. If the face is unrecognized, a red rectangle labeled “Unknown” is displayed. The system runs continuously, providing real-time attendance monitoring, and can be terminated at any time by pressing the ‘Q’ key.

This solution offers several benefits. It automates the attendance process, reducing manual effort and saving time, while enhancing accuracy by minimizing human error. The system is efficient, user-friendly, and adaptable to typical classroom environments, making it a practical tool for academic institutions.

Despite its advantages, the system also tackles a number of technical challenges, including variations in lighting, changes in facial appearance, and partial occlusions. Nevertheless, it has shown reliable performance under standard classroom conditions and offers strong potential for further development and integration with broader educational management systems.

In conclusion, the Design and Implementation of Class Attendance System Based on OpenCV showcases the practical application of computer vision and artificial intelligence in the educational sector. It reflects a significant step toward smarter classrooms and more efficient administrative processes, setting a foundation for future innovation in academic technologies.