Development of Real-Time Face Recognition for Smart Door Lock Security System using Haar Cascade and OpenCV LBPH Face Recognizer

Abstract

Face recognition is a technology that is widely used in security systems. In a door security system, facial recognition can be used to open the door simply by recognizing the face of the door owner. This study aims to develop a real-time facial recognition system for smart locking doors using Haar Cascade and OpenCV LBPH Face Recognizer. The purpose of this project is creating security system to limit people who can access a room. The Haar Cascade method is used to detect faces in images, while the OpenCV LBPH Face Recognizer is used to recognize detected faces. This system was developed using the Python programming language and the OpenCV library. The test results show that this system can detect and recognize faces with an accuracy of 62.7% with our dataset and can be improved by adding more datasets and using deep learning algorithms to train the recognizer model. Thus, the developed real-time facial recognition system can be used as a smart locking door security solution with high accuracy.