MoIT developing security System for face recognition in video surveillance

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ISLAMABAD, Mar 28 (APP):Ministry of Information Technology and Telecommunications is in process of developing a face
recognition System which would be available soon and used in video surveillance.
Official sources at Ignite (formerly known as National ICT R& D Fund)
on Wednesday said it will not only add value to international research scenario
but will also carry significant contribution to the society.
The System will also be available as a stand-alone FPGA-based prototype solution that
can be marketable through a start up company in domain of video
surveillance.
The project called – Design and Development of an FPGA-Based
Multi-Scale Face Recognition System – would cost Rs 13.84 million
and was being developed by PAF-Karachi Institute of Economics and
Technology.
The sources said for security applications, by far, face is the best
choice. Video surveillance is an efficient way of securing a facility.
It said with increasing security threats, the
problem of invulnerable authentication systems is becoming more 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 passwords for example, are difficult to remember and therefore
people tend to use 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, 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.
Special emphasis is being given to algorithm design which
can be efficiently mapped in Hardware. The LBP features primarily
extract texture information of a face image. Wavelet decomposition of
these features result in sub-bands encompassing low and high frequency components. These sub-bands
carry useful information for classification, however some sub-bands are more significant than
others and an intelligent selection of these discriminant sub-bands
is likely to increase overall performance of the face recognition system.
The sources said the project is, therefore, aimed to identify
discriminant sub-bands for efficient and robust face recognition.