FACE RECOGNITION ATTENDANCE SYSTEM USING EHD AND LBPH ALGORITHM

The Face Recognition Attendance System represents a modern biometric-based solution specifically designed to automate the process of tracking attendance using facial recognition technology. This innovative system addresses and resolves several limitations and inefficiencies that are commonly associated with traditional attendance methods, including manual roll calls, sign-in sheets, and the use of RFID cards. By minimizing human intervention, it significantly reduces the occurrence of human errors and prevents fraudulent practices such as proxy attendance. The system integrates real-time image acquisition, facial detection algorithms, and advanced deep learning models to ensure a high level of accuracy and reliability in personal identification. Furthermore, the interface of the application is intentionally designed to be user-friendly, making it easy for administrators and users to operate and manage the system effectively. The inclusion of a structured and optimized database architecture ensures streamlined data storage, retrieval, and management. Additionally, the contactless mode of operation aligns with current health and safety guidelines by minimizing physical interaction, thereby supporting hygienic practices in public and private institutions. Through comprehensive testing across a variety of environmental and user conditions, the system has proven to maintain consistent performance and robustness. Future improvements under consideration involve the incorporation of features such as real-time face mask detection, integration with cloud-based storage systems for scalable data access, and the application of more sophisticated artificial intelligence capabilities. This system is particularly suitable for deployment in educational institutions, corporate offices, and industrial sectors where secure, efficient, and tamper-proof attendance recording mechanisms are essential.