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T-Comm_Article 8_5_2020

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DESIGNING A NEURAL NETWORK IDENTIFICATION SUBSYSTEM IN THE HARDWARE-SOFTWARE COMPLEX OF FACE RECOGNITION

DOI: 10.36724/2072-8735-2020-14-5-69-76

Vyacheslav I. Voronov, Moscow Technical University of Communications and Informatics, Moscow, Russia, Vorvi@mail.ru
Ivan A. Zharov, Moscow Technical University of Communications and Informatics, Moscow, Russia, 303.08@mail.ru
Aleksej D. Bykov, Moscow Technical University of Communications and Informatics, Moscow, Russia, 79778742616@yandex.ru
Artem S. Trunov, Moscow Technical University of Communications and Informatics, Moscow, Russia, greek17@yandex.ru
Lilia I. Voronova, Moscow Technical University of Communications and Informatics, Moscow, Russia, Voronova.lilia@ya.ru

Abstract
With the development of information technologies the popularity of access control systems and personal identification systems is growing. One of the most common methods of access control is biometric identification. Biometric identification is more reliable than traditional identification methods, such as login/password, card, PIN-code, etc. In recent years, special attention has been paid to biometric identification based on facial recognition in access control systems, due to sufficient accuracy, scalability and a wide range of applications: face recognition of intruders in public places, providing access control, etc. The purpose of this article is to design the architecture of the subsystem «Identifier» in the hardware-software complex face recognition. In article methods and models for recognition of the face on the image and in video stream are considered. As a base method the deep neural network is chosen, the basic advantages and lacks of the chosen approach are considered. Special attention is paid to the description of architecture and scenario of work of subsystem «Identifier» of neural network identification software and hardware complex, which implements face recognition in real time from the incoming video stream of IP and USB cameras. Improvements of the traditional algorithm of face recognition using the k-neighbor method are described in detail. The results of the conducted experiments including the influence of head rotation angle on the accuracy of identification are given, and conclusions about the applicability of this method in security systems are made. On the basis of carried out researches the software and hardware complex of biometric identification on the basis of neural network recognition of faces, for the subsequent integration into the security system of the Moscow Technical University of Communications and Informatics (MTUCI) is created.

Keywords: face identification, biometric identification, neural network modeling, Microsoft ResNet, kNN method, biometric identification system, access control systems.

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Information about authors:

Vyacheslav I. Voronov, Moscow Technical University of Communication and Informatics, Associate Professor of the department «Intelligent systems in control and automation», PhD in engineering, Moscow, Russia
Ivan A. Zharov, Moscow Technical University of Communication and Informatics, undergraduate, Moscow, Russia
Aleksej D. Bykov, Moscow Technical University of Communication and Informatics, undergraduate, Moscow, Russia
Artem S. Trunov, Moscow Technical University of Communication and Informatics, senior teacher, Moscow, Russia
Lilia I. Voronova, Moscow Technical University of Communication and Informatics, head of the department «Intelligent systems in control and automation», D.Sc. in Physical and Mathematical Sciences, Moscow, Russia