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T-Comm_Article 4_4_2020

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Vyacheslav I. Voronov, Moscow Technical University of Communications and Informatics, Moscow, Russia, vorvi@mail.ru
Alexey D. Bykov, Moscow Technical University of Communications and Informatics, Moscow, Russia, 79778742616@yandex.ru
Lilia I. Voronova, Moscow Technical University of Communications and Informatics, Moscow, Russia, voronova.lilia@yandex.ru

The task of biometric identification of a person is extremely urgent and can be solved in many ways. It is possible by a number of static and dynamic characteristics such as: papillary finger pattern, hand geometry, iris, face geometry (2D and 3D), vein pattern, handwriting, silhouette, gait, voice. Given the extreme growth in the number of available digital video and photo cameras in public places, a serious improvement in the quality of the data received, reducing the cost of receiving, processing and transmitting them, have received an impetus to develop methods for identifying people by video and photo images. At the same time, the vast majority of methods focus on facial recognition. The largest companies in the world are developing their own software solutions that implement facial recognition functionality in photos and video stream, and offer the market ready-made competitive solutions. All these solutions use their own set of methods and algorithms, while the use of neural networks has become a de facto industry standard, because the methods provide the fastest and most accurate results. Despite the complexity of hardware-software implementation of biometric identification systems based on face recognition, the relevant market is very promising — according to Bloomberg estimates its volume will grow to 7.76 billion U.S. dollars by 2022. In Moscow Technical University of Communications and Informatics (MTUCI) at the Department of Intelligent Systems in Control and Automation (ISCA) in the framework of scientific grant 3-2/2019-2-B the development of a prototype of hardware-software complex for biometric identification (HSC BI) with the use of modern methods of computer vision and neural network methods of face recognition with the possibility of subsequent integration into the security system of the university is underway. The article deals with the subsystems of face detection, file manager and server database included in the projected HSC BI.

Keywords: biometric identification, face recognition, neural network recognition, hardware-software complex, Viola-Jones method, centroid tracking method, Haar features, hardware-software architecture.


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Information about authors:
Vyacheslav I. Voronov, docent, ISCA, Cand. of Sc, Moscow Technical University of Communications and Informatics, Moscow, Russia
Alexey D. Bykov, graduate student, Moscow Technical University of Communications and Informatics, Moscow, Russia
Lilia I. Voronova, Head of the Department of ISCA, Full Professor, Doctor of Sc., Moscow Technical University of Communications and Informatics, Moscow, Russia