A prototype of a robust and secured access control system using principal component analysis

Abstract

The need for a robust and secured access control system using a suitable algorithm is highly inevitable to forestall daily online harkers that are responsible in defrauding people of invaluable information and transactions worth billions of dollars in the process. In this paper, faces were employed as the only control means of right of entrance and usage of information on the super-highway. Principal Component Analysis (PCA) was used to perform dimensionality reduction on the feature vectors of the digitized face images. Also, Euclidean distance was the required similarity measure employed to match the tested face with the trained faces inside the database for actual recognition. The result obtained showed that its avarage percentage of rightly classified face was 90.43% and FAR and FRR were 0.1077 &0.0609. An evaluation of the results demostrated PCA to be a very good algorithm for a robust and secured access control and recognition system.