This project aims to implement a user-friendly, low cost, and high accuracy face recognition system used in airports for security purpose. This thesis presents the implementation and developments of face recognition technology, the system is deployed through a Django web server configured on Raspberry Pi 3B+ microcontroller. With an integration of OpenCV library and other supporting libraries using Python computer language, the face recognition algorithms were implemented. The web server provides multiple web pages and buttons for the interaction with system operation. An SQLite database was used to store the passenger’s information. A training of the system’s training set, and a face recognition with a responded message of granted access or denied access along with LED status indication was performed.