Development of a facial recognition-based attendance system

Abstract

This project presents a facial recognition-based time-tracking system that aims to improve the process of monitoring employee attendance. The system utilizes the LBPH (Local Binary Patterns Histograms) algorithm to collect and analyze facial data in real-time, allowing for accurate identification of individuals even in varying lighting conditions and from different angles. To ensure precise time tracking, the system creates unique facial templates for each user, which are securely stored and matched against actual data during check-in. Additionally, the system addresses common challenges such as spoofing and prioritizes data privacy through encryption. The deployment also includes a user-friendly interface for easy management of attendance records and the option to integrate with existing HR systems. By reducing manual errors and saving time compared to traditional time tracking methods, this solution offers an efficient and scalable option suitable for organizations of all sizes.