Face Recognition Attendance System

With the increasing need for smart and automated systems, attendance management using face recognition has become an effective alternative to traditional methods. Manual attendance processes are often time-consuming, inaccurate, and vulnerable to proxy entries. This paper presents a real-time Face Recognition Attendance Management System developed using Artificial Intelligence and Computer Vision techniques. The system captures facial images through a webcam, detects faces using Haar Cascade classifiers, and identifies individuals using the LBPH face recognition algorithm. Once verified, attendance is automatically recorded with timestamps and stored in CSV and Excel files for easy management and reporting. The proposed system minimizes human intervention, improves attendance accuracy, and reduces administrative workload while operating efficiently on standard computing devices, making it suitable for educational institutions and workplaces.