Distribution optimization method of pixel density by surveillance area

The task of optimizing the parameters of the video camera matrix to reduce the redundancy of the generated video signal is considered. The relevance of the topic is due to the existing redundancy of video signals generated by matrices in different parts of the observation zone and, as a result, exce...

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Main Authors: Vladimir V. Volkhonskiy, Vladislav A. Kovalevskiy
Format: Article
Language:English
Published: Saint Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO University) 2022-12-01
Series:Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki
Subjects:
Online Access:https://ntv.ifmo.ru/file/article/21634.pdf
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author Vladimir V. Volkhonskiy
Vladislav A. Kovalevskiy
author_facet Vladimir V. Volkhonskiy
Vladislav A. Kovalevskiy
author_sort Vladimir V. Volkhonskiy
collection DOAJ
description The task of optimizing the parameters of the video camera matrix to reduce the redundancy of the generated video signal is considered. The relevance of the topic is due to the existing redundancy of video signals generated by matrices in different parts of the observation zone and, as a result, excessive loading of signal transmission, storage and processing devices. The problem is solved by achieving a uniform distribution of pixel density over the observation area. The methodology is based on solving the problem programmatically, unlike existing solutions using hardware methods. It is based on the representation of the view area as a set of subsets of the observation task space with its subsequent fragmentation in accordance with the observation tasks being solved which determine the required minimum pixel density in different fragments. To solve the problem, the matrix is segmented in according to the size of the fragments of the observation area and the specified allowable range of changes in the distribution of pixel density in the viewing area of the camera. Mandatory and additional distribution optimization criteria are proposed. The optimization technique is formulated. In according to the redundancy coefficient of the pixel density distribution in different segments, pixels are combined into groups that are different in different segments. Examples of solving optimization problems according to different criteria are given. The proposed approach makes it possible to minimize the pixel density redundancy and thereby reduce the load on communication channels, the amount of memory in video information storage devices, and the performance requirements for video signal processing devices. In this case, the problem of forming a continuous image of the observation zone is also solved. Results could be used for video signal processing and design of new cameras for video surveillance systems.
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spelling doaj.art-0842d0bd57984aac99d5e519d86eeb492022-12-22T03:55:03ZengSaint Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO University)Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki2226-14942500-03732022-12-012261055106210.17586/2226-1494-2022-22-6-1055-1062Distribution optimization method of pixel density by surveillance areaVladimir V. Volkhonskiy0https://orcid.org/0000-0001-9628-2046Vladislav A. Kovalevskiy1https://orcid.org/0000-0001-7042-7905D. Sc., Associate Professor, Associate Professor, ITMO University, Saint Petersburg, 197101, Russian Federation, sc 6507100798PhD Student, ITMO University, Saint Petersburg, 197101, Russian FederationThe task of optimizing the parameters of the video camera matrix to reduce the redundancy of the generated video signal is considered. The relevance of the topic is due to the existing redundancy of video signals generated by matrices in different parts of the observation zone and, as a result, excessive loading of signal transmission, storage and processing devices. The problem is solved by achieving a uniform distribution of pixel density over the observation area. The methodology is based on solving the problem programmatically, unlike existing solutions using hardware methods. It is based on the representation of the view area as a set of subsets of the observation task space with its subsequent fragmentation in accordance with the observation tasks being solved which determine the required minimum pixel density in different fragments. To solve the problem, the matrix is segmented in according to the size of the fragments of the observation area and the specified allowable range of changes in the distribution of pixel density in the viewing area of the camera. Mandatory and additional distribution optimization criteria are proposed. The optimization technique is formulated. In according to the redundancy coefficient of the pixel density distribution in different segments, pixels are combined into groups that are different in different segments. Examples of solving optimization problems according to different criteria are given. The proposed approach makes it possible to minimize the pixel density redundancy and thereby reduce the load on communication channels, the amount of memory in video information storage devices, and the performance requirements for video signal processing devices. In this case, the problem of forming a continuous image of the observation zone is also solved. Results could be used for video signal processing and design of new cameras for video surveillance systems.https://ntv.ifmo.ru/file/article/21634.pdfpixel density distributionpixel densityobservation taskcamera matrixview area
spellingShingle Vladimir V. Volkhonskiy
Vladislav A. Kovalevskiy
Distribution optimization method of pixel density by surveillance area
Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki
pixel density distribution
pixel density
observation task
camera matrix
view area
title Distribution optimization method of pixel density by surveillance area
title_full Distribution optimization method of pixel density by surveillance area
title_fullStr Distribution optimization method of pixel density by surveillance area
title_full_unstemmed Distribution optimization method of pixel density by surveillance area
title_short Distribution optimization method of pixel density by surveillance area
title_sort distribution optimization method of pixel density by surveillance area
topic pixel density distribution
pixel density
observation task
camera matrix
view area
url https://ntv.ifmo.ru/file/article/21634.pdf
work_keys_str_mv AT vladimirvvolkhonskiy distributionoptimizationmethodofpixeldensitybysurveillancearea
AT vladislavakovalevskiy distributionoptimizationmethodofpixeldensitybysurveillancearea