International Research Journal of Education and Technology

Attendance management is a fundamental administrative process in educational institutions and corporate organizations. Conventional methods, including manual registers and biometric fingerprint systems, are often time-consuming, susceptible to proxy attendance, and limited in providing real-time data accessibility and centralized record management. To address these limitations, this paper proposes a Smart Attendance System based on Face Recognition that automates attendance marking using computer vision and machine learning techniques.

The proposed system employs OpenCV for real-time face detection and utilizes the Local Binary Pattern Histogram (LBPH) algorithm for efficient facial recognition. A web-based application interface is developed using the Flask framework, while SQLite is used for secure and structured data storage. The system captures facial data through a webcam, processes and matches it against a trained dataset, and records attendance with accurate timestamps. Administrative dashboards enable monitoring, report generation, and user management.

Keywords: Face Recognition, OpenCV, Local Binary Pattern Histogram (LBPH), Smart Attendance System, Computer Vision, Flask, SQLite.