Digital Attendance System Using Face Recognition

Traditional attendance systems in educational institutions are often inefficient, time-consuming, and susceptible to errors such as proxy attendance. To overcome these limitations, this paper presents an automated digital attendance system based on face recognition technology. The proposed system utilizes image processing and machine learning techniques to detect and identify student faces in real time, ensuring accurate and reliable attendance marking. The system includes features such as user registration, face data acquisition, identity verification, and automated storage of attendance records in a centralized database. It offers a contactless and secure solution that reduces manual effort while improving efficiency and transparency. Additionally, the integration of real-time monitoring and reporting enhances overall academic management. Experimental results demonstrate that the system significantly reduces attendance marking time and effectively prevents unauthorized attendance, making it suitable for modern classroom environments.