Human Face Recognition using FSVD and RBF Neural Network

A Biometric system is a pattern recognition system. It operates by acquiring Biometric data from an individual, extracting a feature set from the acquired data, and comparing this feature set against the template set in the database. A number of Biometric characteristics exist and are in use in various applications. Each Biometric has its strengths and weaknesses, and the choice depends on the application. The match between a specific Biometric with an application is determined depending upon the operational mode of the application and the properties of the Biometric characteristic. Research in automated face recognition has been conducted since the 1960s. The reliability of face recognition schemes still poses a great challenge to the scientific community. Face recognition has several advantages over other Biometric techniques. Face recognition is natural, non-intrusive and easy to use since it is based on images recorded by a distant camera and can be very effective even if the user is not aware of the existence of the face recognition system. The increased interest in automated face recognition systems have gained largely due to increasing public concerns for security.

Autorentext

I am Kalpana Jondhale, working as Professor and Head, Department of Electronics and Telecom Engg, at MGM'CEN, India. The current FR systems does not support identification in controlled environments, especially in crowd situations. Scope is to extend the FR system to more difficult environment in public security and crowd surveillance.