On Choosing the Precedent Size in the Problem of Objects Detecting in Digital Images

Authors

  • Denis V. Petrov Limited Liability Company "Manatechs"
  • Evgeny G. Zhilyakov Belgorod National Research University
  • Daria A. Chernomorets Belgorod National Research University
  • Evgeniya V. Bolgova Belgorod National Research University
  • Andrey A. Chernomorets Belgorod National Research University

DOI:

https://doi.org/10.52575/2687-0932-2022-49-2-339-348

Keywords:

object detection, image, video camera, equivalent focal length, photo matrix dimension, precedent size, object size, distance to the object

Abstract

In the paper we consider the problem arising in the video surveillance systems development of choosing the precedent size when detecting objects in images, taking into account the optoelectronic system characteristics. The example shows that in order to solve the objects detection problem at different distances from the observer on digital images, based on comparison with precedents, it is essential to choose the appropriate precedent size, which depends on the digital video camera characteristics. Examples of applications in surveillance tasks of video cameras with different equivalent focal lengths are considered. The relations for determining the equivalent focal length of the lens (equivalent to 35 mm) are given based on the value of the actual focal length of the camera lens determined by its design features. Relations are given for calculating the precedent size corresponding to an observed object of a given size and located at a known distance from the observer, taking into account the characteristics of the optoelectronic system. Examples of object size values (pixels) in the image are given depending on the distance to the object of specified dimensions (m) on the observed scene at different values of the digital video camera characteristics. An algorithm has been developed for solving the problem of detecting objects in an image based on the analysis of precedents, which dimensions depend on the video camera characteristics, as well as on the desired object size and the distance from it to the observer. Examples of object detection in images are given, taking into account the digital video camera characteristics.

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Author Biographies

Denis V. Petrov, Limited Liability Company "Manatechs"

Candidate of Technical Sciences, Chief Technical Officer, Limited Liability Company "Manateks",
Belgorod, Russia

Evgeny G. Zhilyakov, Belgorod National Research University

Doctor of Technical Sciences, Professor, Professor of the Department of Information and Telecommunication Systems and Technologies, Belgorod National Research University,
Belgorod, Russia

Daria A. Chernomorets, Belgorod National Research University

Postgraduate student of the Department of Information and Telecommunication Systems and Technologies of Belgorod National Research University,
Belgorod, Russia

Evgeniya V. Bolgova, Belgorod National Research University

Candidate of Technical Sciences, Associate Professor of the Department of Applied Informatics and Information Technologies of the Belgorod National Research University,
Belgorod, Russia

Andrey A. Chernomorets, Belgorod National Research University

Doctor of Technical Sciences, Associate Professor, Professor of the Department of Applied Informatics and Information Technologies of the Belgorod National Research University,
Belgorod, Russia

References

Алпатов Б.А., Бабаян П.В., Балашов О.Е, Степашкин А.И. 2008. Методы автоматического обнаружения и сопровождения объектов. Обработка изображений и управление. М.: Радиотехника, 176.

Бакулев П.А., Степин В.М. 1986. Методы и устройства селекции движущихся целей. М.: Радио и связь, 286.

Вагнер В., Вагнер А. 2016. Способы параметризации движения в системах видеонаблюдения. LAP LAMBERT Academic Publishing, 52.

Васин Н.Н., Баранов А.М., Дворянинов П.Ю. 2007. Метод межкадровой разности для измерительных систем. Радиотехника и связь: материалы четвертой междунар. науч.-техн. конф., Саратов, 27–28 июня 2007 г. М-во образования и науки Рос. Федерации, Сарат. гос. техн. ун-т; отв. ред. В.А. Коломейцев. Саратов, 67–71.

Гонсалес Р., Вудс Р. 2012. Цифровая обработка изображений. Издание 3-е, исправленное и дополненное. Москва: Техносфера, 1104 с.

Зубец А.М. 2008. Патент на изобретение RU 2319188 C2, Способ и устройство для панорамной фотосъемки. 10.03.2008. Заявка № 2005138891/28 от 14.12.2005.

Иванкин Е.Ф. 2008. Информационные системы с апостериорной обработкой результатов наблюдений. М., Горячая Линия – Телеком, 168.

Понин О.В., Галявов И.Р., Симонов М.А., Симонов П.В. 2020. Патент на изобретение 2731526 C1, Способ измерения фокусного расстояния объектива. 03.09.2020. Заявка № 2020100024 от 09.01.2020.

Черноморец А.А., Болгова Е.В., Заливин А.Н., Олейник И.И. 2019. О комплексной обработке оптических сигналов в задаче обнаружения объектов. Научные ведомости Белгородского государственного университета. Серия: Экономика. Информатика. 46 (4): 764–773. DOI 10.18413/2411-3808-2019-46-4-764-773

Черноморец А.А., Кунгурцев С.А., Болгова Е.В. 2020. О геометрии области поиска объектов на основе радиолокационных измерений. Сборник материалов VIII Международной научно-технической конференции Информационные технологии в науке, образовании и производстве (ИТНОП – 2020). Белгород. 130–136.

Шитова О.В., Пухляк А.Н., Дроб Е.М. 2014. Анализ методов сегментации текстурных областей изображений в системах обработки изображений. Научные ведомости Белгородского государственного университета. Серия: История. Политология. Экономика. Информатика. 8(179). 182–188.

Schindler K., Förstner W. 2021. Photogrammetry. In: Ikeuchi K. (eds) Computer Vision. Springer, Cham. https://doi.org/10.1007/978-3-030-63416-2_139

Voronin, E.G. 2022. Numerical differentiation in photogrammetry equalization tasks. Geodesy and Cartography. 981. 44–55. 10.22389/0016-7126-2022-981-3-44-55.


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Published

2022-06-30

How to Cite

Petrov, D. V., Zhilyakov, E. G., Chernomorets, D. A., Bolgova, E. V., & Chernomorets, A. A. (2022). On Choosing the Precedent Size in the Problem of Objects Detecting in Digital Images. Economics. Information Technologies, 49(2), 339-348. https://doi.org/10.52575/2687-0932-2022-49-2-339-348

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COMPUTER SIMULATION HISTORY

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