Face Recognition Attendance System using Haar Cascade Classifier and Local Binary Pattern Histogram Algorithm

Abstract

Traditional classroom attendance methods, like roll-call and sign-in sheets, are time-consuming and error-prone. This paper introduces a cost-effective solution leveraging Real-Time Face Recognition to efficiently manage student attendance. The proposed model, implemented in Python with OpenCV, uses Haar Cascade for face detection and LBPH for recognition, considering both positive and negative facial features for accuracy. The Tkinter GUI interface enhances user interaction, marking a departure from cumbersome traditional approaches and addressing the challenges of managing large student groups