Efficient Attendance Tracking with Facial Recognition

Abstract

This paper presents a face recognition-based attendance monitoring system developed to automate attendance tracking. The objective is to enhance accuracy, efficiency, and security in attendance recording, addressing the limitations of traditional manual methods. The proposed system successfully achieved these goals by utilizing face recognition technology for precise attendance recording, real-time monitoring, and user-friendly interaction. The methodology involved implementing face detection and recognition using HaarCascades and Local Binary Pattern Histogram (LBPH) algorithms, integrating a graphical user interface for ease of use, and efficiently managing data. The results demonstrate an effective system for automated attendance tracking, showcasing the potential of facial recognition in improving traditional attendance methods