The System of Facial Recognition in the Infrared Range

https://doi.org/10.26552/com.C.2020.1.95-101

  • Daniil A. Loktev
  • Alexey A. Loktev
  • Alexandra V. Salnikova
Keywords: object image, background image, cascade classifier, thermal imager, object contour, background subtraction

Abstract

In this paper, a new approach is introduced upgrading the complex object recognizing monitoring system up to the image processing system capable of operating both in the visible and the infrared wavelength ranges. For this purpose, both new algorithmic software and user interface are provided that require from the operator neither special knowledge, nor specific competencies in the fields of object detection, tracking and recognition, while allowing determining the thermal imager parameters necessary for constructing a high-quality image of an object. There are formulated the conditions required for obtaining such image that, by its quality, would make the satisfactory detection of the desired object possible. By means of the conducted tests, it is demonstrated that the application of the proposed mathematical and algorithmic support of the complex monitoring and control system provides the solution for the problem of the highly accurate individual recognition.

Author Biographies

Daniil A. Loktev

Department of Information Systems and Telecommunications, Bauman Moscow State Technical University, Russia

Alexey A. Loktev

Department of Transport Construction, Russian University of Transport (MIIT), Moscow, Russia

Alexandra V. Salnikova

International Laboratory of Statistics of Stochastic Processes and Quantitative Finance, National Research Tomsk State University, Russia and Department of Building Engineering and Urban Planning, University of Zilina, Zilina, Slovak Republic

Published
2020-01-02
How to Cite
Daniil A. Loktev, Alexey A. Loktev, & Alexandra V. Salnikova. (2020). The System of Facial Recognition in the Infrared Range. Communications - Scientific Letters of the University of Zilina, 22(1), 95-101. https://doi.org/10.26552/com.C.2020.1.95-101
Section
Management Science and Informatics in Transport