Facial recognition vehicle theft prevention system using PCA algorithm

Mohamed Embaiah Abdulsalam Gerza

Publication:

Facial recognition vehicle theft prevention system using PCA algorithm

dc.contributor.author	Mohamed Embaiah Abdulsalam Gerza
dc.date.accessioned	2025-12-17T07:46:47Z
dc.date.available	2025-12-17T07:46:47Z
dc.date.issued	2018
dc.description	Master of Science in Embedded System Design Engineering
dc.description.abstract	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.
dc.identifier.uri	https://hdl.handle.net/20.500.14170/15520
dc.language.iso	en
dc.publisher	Universiti Malaysia Perlis (UniMAP)
dc.subject	Pattern recognition systems
dc.subject	Security systems
dc.subject	Global Positioning System
dc.title	Facial recognition vehicle theft prevention system using PCA algorithm
dc.type	Resource Types::text::thesis::master thesis
dspace.entity.type	Publication
oaire.citation.endPage	106
oaire.citation.startPage	1
oairecerif.author.affiliation	School of Computer and Communication Engineering