DESIGN AND IMPLEMETATION OF FACE RECOGNITION SYSTEM FOR STUDENT IDENTIFICATION
Abstract
This project presents the “design and implementation of face recognition system for student identification” and identification software using machine-learning techniques. The primary objective is to enhance security and accuracy in identity verification processes by utilizing advanced facial recognition algorithms. The system captures and analyzes unique facial features to authenticate individuals in real-time, thereby mitigating issues such as impersonation and identity fraud. Implemented using Python and integrated with a secure database, the solution ensures efficient data management and seamless retrieval of user information. Through rigorous testing on a sample dataset, the project demonstrates improved recognition accuracy and reduced processing and impersonation compare to manual verification and identification methods. The study emphasizes the potential of biometric systems in educational institutions for secure student identification during examinations, contributing to a more reliable and effective authentication framework.
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