TY - EJOUR
AU - Kurniawan, Turkhamun Adi
AU - Sumadikarta, Istiqomah
AU - Nauli, Sukarno Bahat
AU - Zuli, Faizal
AU - Santoso, Teguh Budi
AU - Desma, Muhammad Roufiqi
PY - 2024
DA - February
TI - Room Security System with Face Recognition using Local Binary Pattern Histogram Algorithm based on the Internet of Things
T2 - Majlesi Journal of Electrical Engineering
VL - 17
L1 - https://oiccpress.com/Majlesi-Journal-of-Electrical-Engineering/article/room-security-system-with-face-recognition-using-local-binary-pattern-histogram-algorithm-based-on-the-internet-of-things/
DO - 10.30486/mjee.2023.1984928.1120
N2 - An Internet of Things-based security system and OpenCV technology have been developed to improve the efficiency and ease of monitoring video footage from CCTV. The face detection process is carried out using the Haar Cascade method, while facial recognition is carried out using the Local Binary Pattern Histogram algorithm. The test results show that light intensity has a significant influence on system accuracy, but this system provides convenience in monitoring CCTV video in real-time through a webserver and improves security, especially in rooms by utilizing Internet of Things technology. The current facial recognition success rate is 72%. Therefore, for the subsequent development of the system, it is recommended to increase the success rate of facial recognition and also implement the File Transfer Protocol to ensure better and better system performance.
IS - 2
PB - OICC Press
KW - webserver, Internet of Things, Security system, OpenCV, face detection, Facial recognition. Light intensity 
EN -