Abstract:
The security currently become a very important
issue in public or private institutions in which various security
systems have been proposed and developed for some crucial
processes such as person identifications, verification or
recognition especially for building access control, suspect
identifications by the police, driver licenses and many others.
Face recognitions have been an active area of research with
numerous applications since three decades ago and become one
of the important elements in security system development. This
paper focuses on the study and development on an automated
face recognition system with the potential application for office
door access control. The technique of eigenfaces based on the
Principal component analysis (PCA) and artificial neural
networks have been applied into the system. The study
includes the analysis of the influences of three main factors of
head orientation on the developed face recognition system and
it is purposely built for office door access control. The
experimental results have shown that the developed system has
achieved good performance of face recognition rate of 80% at
the distance of camera and subject between 40 cm to 60 cm and orientation head angle must be within the range
of -20 to +20 degrees.
