Implementation of a Face Recognition-Based Access Control System for Enhanced Campus Security Using Python

With the increasing need for robust security measures in educational institutions, biometric authentication has emerged as a reliable and convenient solution. This paper presents the design and implementation of a face recognition-based access control system tailored for college campuses. Leveraging Python and its powerful libraries such as OpenCV and face_recognition, the system captures and processes facial images to authenticate individuals in real-time. The proposed system enhances security by restricting unauthorized access and streamlining the entry process without physical tokens or cards. Performance evaluation demonstrates high accuracy and efficiency, indicating potential for scalable campus deployment. This research contributes to the advancement of automated security systems in academic settings, providing a practical approach to safeguarding campus facilities.