Face Recognition Based Vehicle Theft Detection

Adding a vehicle theft security system and improving vehicle technology systems are becoming more and more popular study topics in an effort to prevent car theft in parking lots and occasionally when driving in unsafe locations. This work objective is to develop a prototype model to detect vehicle theft using a facial recognition algorithm. The image is initially captured using a camera that is angled differently, and it is subsequently trained using the cascade Haar classifier technique. Furthermore, a linear binary pattern algorithm in a Python environment is used to extract the captured images. If the extracted image and the training image differ, theft is detected, and the vehicle owner is contacted via the mobile app. The developed prototype model offers a superior security alarm for vehicle theft and is tested with a real-time application.