Design of Multi-Functional Access Control System

Abstract

Facial recognition is a biometric recognition technology that verifies identity using information about human facial features so it is used for access control systems. Current access control systems are implemented using traditional Radio Frequency Identification (RFID) technology or keys. Users must carry an access card or key and the access card or a key can be forgotten, lost or copied by others to use an access control system. This study proposes a multi-function facial recognition access control system that uses Python and Intelligence RFID. The system's facial recognition scheme uses Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) facial recognition algorithms. This addresses a problem with current facial recognition technology, which achieve good results for different facial models under different lighting conditions. To render the system more user-friendly and versatile, the system requires swiping and a password. The Intelligence RFID access control function uses a high frequency (13.56 MHz) and the ISO/IEC14443-3 protocol is used for data communication between the access card and the card reader. Using a dynamic binary search algorithm, the password is saved and read using an EEPROM. This study uses a combination of software and hardware to allow double confirmation, which increases the stability and accuracy of the system. The system designed in this paper not only improves security, but also has more flexible functions than other access control systems. This is a good example of other systems trying to implement more flexible validation.