Machine vision in poor visibility conditions

S.Yu. Vlasov, M.Kh. Kipov

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Abstract: Machine vision is a scientific digitization direction in the field of artificial intelligence, which allows technologies of various categories to obtain images of real objects, process them and use them in solving applied problems of various levels. A feature of this technology is the possibility of complete or partial object recognition without human participation. Machine vision in poor visibility conditions is a relatively new area of research and development. It has become especially relevant in recent years with the development of autonomous vehicles, outdoor video surveillance and other areas where poor visibility can cause serious problems for the safety and efficiency of systems. The article discusses the features of using machine vision based on camera and lidar technologies. The use of camerabased machine vision and lidar technology continues to develop, which determines the scientific novelty of this article. The purpose of the study is to study the use of machine vision technologies in conditions of poor visibility. The methodology of scientific research is based on the analysis of scientific data, comparative analysis, data synthesis, graphical interpretation. The result of the study is the identification of the features of the introduction of lidars into machine vision technology. In the article the prospects for development are determined and researches in this area are overviewed.

Keywords: machine vision, camera, radar, lidar, cloud, image, object recognition, field of artificial intelligence

For citation. Vlasov S.Yu., Kipov M.Kh. Machine vision in poor visibility conditions. News of the Kabardino-Balkarian Scientific Center of RAS. 2023. No. 5(115). Pp. 25–31. DOI: 10.35330/1991-6639-2023-5-115-25-31

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Information about the authors

Vlasov Sergey Yurevich, postgraduate student, Institute of Computer Science and Problems of Regional Management – branch of Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
360000, Russia, Nalchik, 37-a I. Armand street;
SergeoVlasov@gmail.com
Kipov Mukhamed Khusenovich, postgraduate student, Institute of Computer Science and Problems of Regional Management – branch of Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
360000, Russia, Nalchik, 37-a I. Armand street;
muhamed.kipov@icloud.com