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

Authors

DOI:

https://doi.org/10.15587/1729-4061.2023.278367

Keywords:

image processing, image typical shape, aperture brightness, parameter estimation

Abstract

The object of this study is the aperture brightness of the image of the object, which has a variety of typical shapes in the frames of the series. It directly depends on the stability of the shooting conditions of the objects under study. Thus, determining the exact aperture brightness of an object in the frame becomes more difficult. For this purpose, a method was devised for determining the aperture brightness of an object using the typical shape of its image on a series of frames.

This method is based on the formation of a typical shape of a digital image of an object based on data from all frames of the series. The typical shape makes it possible to take into account the peculiarities of the formation of the image of the object on each frame of the series. Based on this, a more accurate estimate of the initial approximation of the parameters of all Gaussian images of the object is performed. In addition, the adaptation of the method to the standard shape makes it possible to perform a more accurate assessment of the aperture brightness of the object in comparison with the analytically defined profile. An estimate of the aperture brightness of the object was derived using the least squares method. Due to minimization using the Levenberg-Marquardt algorithm, the use of the method improved identification with reference objects and reduced the number of false positives. The study showed a decrease in the standard deviation of frame identification errors by 5–7 times when using a typical shape of a digital image.

The devised method for determining an object's aperture brightness using its image's typical shape was tested in practice within the framework of the CoLiTec project. It was implemented in the intra-frame processing unit of the CoLiTecVS software for the automated construction of brilliance curves of the studied variable stars. Owing to the use of the CoLiTecVS 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

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

Оlenа Postupna, National University of Civil Defence of Ukraine

Doctor of Science in Public Administration, Professor, Associate Professor

Department of Management

Iryna Tabakova, Kharkiv National University of Radio Electronics

PhD, Associate Professor

Department of Media Systems and Technologies

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Devising a method for determining the aperture brightness of an object using a typical shape of its image

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Published

2023-06-30

How to Cite

Khlamov, S., Savanevych, V., Vlasenko, V., Trunova, T., Shvedun, V., Postupna О., & Tabakova, I. (2023). Development of a method for determining the aperture brightness of an object using a typical form of its image. Eastern-European Journal of Enterprise Technologies, 3(2 (123), 6–13. https://doi.org/10.15587/1729-4061.2023.278367

Issue

Vol. 3 No. 2 (123) (2023): Information technology. Industry control systems

Section

Information technology

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Copyright (c) 2023 Sergii Khlamov, Vadym Savanevych, Vladimir Vlasenko, Tetiana Trunova, Viktoriia Shvedun, Оlenа Postupna, Iryna Tabakova

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