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.
Highlights
Facial recognition technology is widely used, especially in transportation hubs that require high levels of security, such as banks, airports, railway stations, public security departments, hotels, automotive systems and laboratories
Compared with other biometric systems that use fingerprints or palm prints or the iris, facial recognition requires no contact with the equipment and it can capture facial images at a distance [2]
EXPERIMENTAL RESULTS The Results section has into two parts: facial recognition and Intelligence Radio Frequency Identification (RFID)
Summary
Facial recognition technology is widely used, especially in transportation hubs that require high levels of security, such as banks, airports, railway stations, public security departments, hotels, automotive systems and laboratories. An access control system is used to control the personnel who enter a facility. It allows a self-managed (no human intervention) system that allows safe areas to be separated from unsafe or public areas. Xiang Pan used a FNN (Fuzzy Neural Network) for RFID and facial recognition to implement an access control system [3]. Xiang Pan Wazwaz et al used a Raspberry Pi facial recognition system for security systems in public places, such as shopping malls, universities and airports, and for different situations and scenarios [4]. The Raspberry Pi is a supportive do-it-yourself platform for projects and
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