ISLAMABAD: Ministry of Information Technology and Telecommunications said it was in the process of developing a face recognition security system which would be available soon for video surveillance.
Official sources at Ignite on Wednesday said it would not only add value to the international research scenario but would also carry a significant contribution to the society.
The system will be available as a stand-alone FPGA-based prototype solution that can be marketed through a startup company in the domain of video surveillance.
The project called “Design and Development of an FPGA-Based Multi-Scale Face Recognition System” is expected to cost Rs 13.84 million and has been developed by the PAF Karachi Institute of Economics and Technology.
The sources said that for security applications, video surveillance was an efficient way of securing a facility. It was said that with the increasing security threats, the problem of invulnerable authentication systems was becoming acute.
Traditional means of securing a facility essentially depend on strategies corresponding to “what you have” or “what you know”, for example, smart cards, keys and passwords.
These systems, however, can easily be fooled, the sources said and added that passwords, for example, were difficult to remember. Also, people tend to use the same password for multiple facilities making it more susceptible to hacking.
Similarly, cards and keys can easily be stolen or forged. A more inalienable approach is, therefore, to go for strategies corresponding to “what you are” or “what you exhibit” i.e. biometrics.
Among the other available biometrics, such as speech, iris, fingerprints, hand geometry and gait, the face seems to be the most natural choice. It is non-intrusive, requires a minimum of user cooperation and is cheap to implement.
The sources said this project focuses on design and development of a high-speed FPGA-based multi-scale face recognition system using Linear Binary Pattern (LBP) features.
The sources said the project is, therefore, aimed to identify discriminant sub-bands for efficient and robust face recognition.
