"Anti-Theft Car Tracking and Controlling Security System based on Face Recognition" is an international journal written by Patil and Sardeshmukh 2014. The paper explains an intelligent anti-theft security system. The system employs biometric application along with global positioning system (GPS) module in order to track and locate a lost car. Face recognition is an example of the biometric application used in this system. As a whole, the system is comprised of embedded control ARM platform of processor, GPS, face recognition and multimedia messaging service (MMS) module for avoiding loss of vehicle(Patil, Sardeshmukh 2014).
This system, according to the authors has the most evident advantage of not only preventing the car from loss, but also locates a car along with the victim responsible for theft. A web cam is placed in the vehicle where video frames will be recorded. The face of the person is recognized by means of face recognition system as he/she tries to enter the vehicle. In the case where a person is not an authorized user, his/her image together with GPS co-ordinates is sent to the owner of the vehicle via multimedia messaging service module. This module is located within the vehicle. Upon receiving multimedia message service, the mobile owner will be able to stop the vehicle by sending SMS to the multimedia messaging service module. The MMS then activates the interrupt of the ARM processor. The processor will in turn generate interrupt to stop the ignition unit of the vehicle. The car can finally be tracked and recovered depending on the co-ordinates of GPS. In addition, the person responsible for theft can also be identified (Patil, Sardeshmukh 2014).
The system of face recognition relies on Weber law Descriptor (WLD). The WLD divides the image into several blocks after when WLD is computed for every block. The WLD histograms are also gotten from blocks of an image for reasons of preserving spatial information. The histogram from diverse blocks is put together to generate the ultimate feature set of the image for the face. A comparison is then made between this feature set and that of the database image followed by real time user verification for purposes of detecting any unauthorized entry. This system was finally proved to be reliable and helpful in preventing the vehicle from theft in comparison with the traditional sensor based vehicle system of security. Moreover, WLD approach of face recognition was also found to be extra efficient as compared to local based feature methods like local binary patterns among others (Patil, Sardeshmukh 2014).
My view is related to the idea of future scope given by the authors. I am also for the idea that extra high security can be enhanced by improving on the accuracy of face recognition along with the necessary biometric applications. The quality of communication also has to be improved by using Multimedia message service and global positioning system with enhanced baud rate. However, the future scope of the article could have also included the use of this security system to secure other valuable electronic assets like computers, phones and others.
Patil, Shardool, and M. M. Sardeshmukh. "Anti-Theft Car Tracking and Controlling Security System based on Face ,"(2014).