Clustering Methods Analysis for Terrain Colors Characteristics Determination

Abstract

This paper considers one of the stages of designing camouflage concealment means - the identification of characteristic colors of the terrain. Color is an integral part of the visual characteristic of camouflage means intended to conceal personnel, material resources, weapons and military equipment from enemy reconnaissance and destruction means. It is proposed to identify characteristic colors using cluster analysis, which refers to unsupervised machine learning methods. The number of clusters obtained determines the number of colors that will be displayed on the camouflage coating. As a result of the research, mathematical clustering algorithms were analyzed to determine the characteristic colors of the terrain. The need to conduct these studies is due to the lack of a universal way to determine the number of clusters, and is based on the research of other scientists who have determined that for each subject terrain only a certain clustering algorithm works most effectively, which must be determined experimentally. According to the results of the research, it was determined that the optimal algorithm for determining the characteristic colors of the terrain was the k-means++ clustering algorithm. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). CEUR Workshop Proceedings (CEUR-WS.org)