Design and Implementation of a Face Recognition-Based Attendance Management System

Computer Science — 2025, Undergraduate

This study designed and implemented a Face Recognition-Based Attendance Management System to capture student attendance automatically and eliminate proxy registration. Manual roll-call is slow, unreliable, and consumes lecture time. The system detects and matches faces against enrolled records and timestamps attendance without physical contact. Built with Python Django and SQLite using computer vision libraries, the system was evaluated in a classroom environment. Results showed accurate recognition under controlled conditions and a significant reduction in attendance-taking time. The study recommends deployment with adequate lighting standards and periodic model updates.

For reference and learning only. Do not submit this work as your own.

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