The security system of a vehicle starts with the key system. This is because there is no guarantee that a car invasion will occur. Due to this shortage, the intruders took advantage of the vehicle's theft. Therefore, facial recognition vehicle theft prevention system is developed using the Principle Component Analysis (PCA) algorithm. PCA algorithm consists of four functions which are converts the set of training image to image vectors and normalizes the image vectors. Thirdly, covariance matrix and the Eigenvectors are calculated before the face is recognized. Viola Jones algorithm is also applied in this project to detect the driver's face. This project is implemented using MA TLAB for image processing and Arduino Mega board for tracking system to detect the location of vehicle. The project begins when a person enters the vehicle and sits in the driver's seat, the switch mounted on the driver's seat will activate a hidden camera that focuses on the driver's position. Once the image is taken from an activated camera, the person's face is detected using the Viola Jones algorithm. Executed faces will be identified using the PCA algorithm by comparing with the faces stored in the database in an image format such as the face of the vehicle owner. If comparison of face images is not the same, then warning messages will be sent via the Short Messaging Service (SMS) to the vehicle owners on a regular basis. The SMS contains GPS latitude and longitude information tracked by GPS. This system will light up the green LED when the vehicle intruder is identified and the red LED is lit if the intruder cannot be traced. The design of this system is started by installing the circuit and software development to be the prototype of the project. Finally, vehicle safety systems can be implemented using PCA with the help ofGPS and GSM technology.
