Development of a method for determining the position of an object using a typical form of its image

Authors

DOI:

https://doi.org/10.15587/1729-4061.2023.275655

Keywords:

image processing, standard image shape, Levenberg-Marquardt algorithm, parameter evaluation

Abstract

Violating the observation conditions for the investigated objects leads to the formation of diverse typical forms of objects throughout the frame in the series. As a consequence, determining the exact position of the object on the frame becomes difficult. To this end, a method was devised to determine the position of an object using the typical form of its image on a series of frames.

This method is based on the formation of a typical form of a digital image of an object based on data from all frames of the series. This makes it possible to take into account the peculiarities of the very formation of the digital image of an object on each frame of the original series. Based on this, a more accurate assessment of the initial approximation of the parameters of all Gaussians of the object's image is performed. Adapting the method specifically for the typical form allows for a more accurate assessment of the positional parameters (coordinates) of the object in comparison with the analytically set profile. The estimation of the position of an object was obtained using the method of least squares. After that, minimization was performed using the Levenberg-Marquardt algorithm. Also, the use of the method makes it possible to improve identification with reference objects and reduce the number of false detections. The study showed a reduction in the standard deviation of frame identification errors by 7–10 times when using a typical digital image shape.

The method devised for determining the position of an object using the typical form of its image was tested in practice within the framework of the CoLiTec project. It was implemented in the intraframe processing unit of the Lemur software to automatically detect new objects and track known ones. Owing to the use of Lemur software and the proposed computational method implemented in it, more than 700,000 measurements of various objects under study were successfully processed and identified

Author Biographies

Sergii Khlamov, Kharkiv National University of Radio Electronics

PhD, Assistant

Department of Media Systems and Technologies

Vadym Savanevych, Kharkiv National University of Radio Electronics

Doctor of Technical Sciences, Professor

Department of Systems Engineering

Oleksandr Briukhovetskyi, National Space Facilities Control and Test Center

PhD

Western Center of Radiotechnical Surveillance

Vladimir Vlasenko, National Space Facilities Control and Test Center

PhD

Space Research and Communications Center

Tetiana Trunova, Kharkiv National University of Radio Electronics

Engineer, Assistant

Department of Media Systems and Technologies

Viktoriia Shvedun, National University of Civil Defence of Ukraine

Doctor of Science in Public Administration, Professor, Head of Scientific Department

Scientific Department of Management Problems in the Field of Civil Protection

Larysa Hren, National Technical University “Kharkiv Polytechnic Institute”

Doctor of Technical Sciences, Professor

Department of Pedagogy and Psychology of Social Systems Management

Iryna Tabakova, Kharkiv National University of Radio Electronics

PhD, Associate Professor

Department of Media Systems and Technologies

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Development of a method for determining the position of an object using a typical form of its image

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Published

2023-04-17

How to Cite

Khlamov, S., Savanevych, V., Briukhovetskyi, O., Vlasenko, V., Trunova, T., Shvedun, V., Hren, L., & Tabakova, I. (2023). Development of a method for determining the position of an object using a typical form of its image . Eastern-European Journal of Enterprise Technologies, 2(2 (122), 6–12. https://doi.org/10.15587/1729-4061.2023.275655

Issue

Vol. 2 No. 2 (122) (2023): Information technology. Industry control systems

Section

Information technology

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Copyright (c) 2023 Sergii Khlamov, Vadym Savanevych, Oleksandr Briukhovetskyi, Vladimir Vlasenko, Tetiana Trunova, Viktoriia Shvedun, Larysa Hren, Iryna Tabakova

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