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People Recognition Interface based on Biometric Sensors Connected to an Arduino Mega 2560 Board
International Journal of Computer Science and Network Security ; 22(4):750-756, 2022.
Article in English | English Web of Science | ID: covidwho-1884904
ABSTRACT
Biometric authentication has grown significantly since the events in the United States in 2001. Moreover, during the COVID-19 pandemic, many more researches have been done on contactless biometric authentication or recognition methods. Arduino Mega 2560 is a module often used in designing applications, but most of the time it can only be used as an interface in image processing. During the post-doctoral researches in multimodal biometrics, it was developed a complex application using the Arduino Mega 2560 board and several sensors attached to it, including two fingerprint sensors, an infrared imaging camera, a keyboard and a Bluetooth module that allows communication between this device and a mobile device or a desktop / laptop system. The developed application can be used for registration or authentication to an internet banking system, by entering the biometric features represented by iris and fingerprint, in addition to the classic authentication methods, based on username and a password generated by a digipass. The application and the device only have the role of taking the iris or the fingerprint, these being transmitted via Bluetooth for processing on a mobile or laptop device. Biometric analysis and extraction cannot be performed on the Arduino Mega 2560 due to the low frequency of the processor (12 MHz only) and the relatively small memory space.
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Full text: Available Collection: Databases of international organizations Database: English Web of Science Language: English Journal: International Journal of Computer Science and Network Security Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: English Web of Science Language: English Journal: International Journal of Computer Science and Network Security Year: 2022 Document Type: Article