Implementation of an Efficient Access Control System for Secure Building

Abstract

This paper describes hybrid access control system based on a new approach of face recognition and PIN (Personal Identification Number) code identification, which is done by finding the closest match between features implemented on the same databases. This approach involves two identification and matching subsystems. The outputs from these subsystems are combined to decide the final output that authorizes the access to the secure building for certain persons while denying the access for the others.
In verification, a biometric identifier is compared to another template through a PIN number of database. Identification involves comparing an existing image against a large image database in order to identify the individual depicted. For this purpose, a camera is set in the door looking at the enter and the captured frames are analyzed. The implementation includes neural networks for PIN code identifications, and analysis starts by selecting the regions of interest in the face images using NN.