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	Distribution optimization method of pixel density by surveillance area</div>

Volkhonskiy Vladimir V., Kovalevskiy Vladislav A.

2022 , VOLUME 22, NUMBER 6 ( november-december )

ISSN 2226-1494 (print), ISSN 2500-0373 (online)

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Nikiforov
Vladimir O.
D.Sc., Prof.

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doi: 10.17586/2226-1494-2022-22-6-1055-1062

Distribution optimization method of pixel density by surveillance area

V. V. Volkhonskiy, V. A. Kovalevskiy

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Article in Russian

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Volkhonskiy V.V., Kovalevskiy V.A. Distribution optimization method of pixel density by surveillance area. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2022, vol. 22, no. 6, pp. 1055–1062

(in Russian). doi: 10.17586/2226-1494-2022-22-6-1055-1062

Abstract

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.

Keywords: pixel density distribution, pixel density, observation task, camera matrix, view area

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