THE METHOD OF SEGMENTATION OF THE IMAGES IN THE REMOTE VIDEO MONITORING SYSTEM BASED ON THE K-MEANS ALGORITHM

Abstract

The configuration of the video monitoring system, which is widely used in the protection systems of objects and positions of units, is given. Examples of the collision line video monitoring system are given, namely: the video monitoring system of the special monitoring mission of the Organization for Security and Cooperation in Europe and the battalion video surveillance complex. An analysis of known methods of image segmentation in video monitoring systems has been carried out. The analysis showed that these methods do not meet the requirements for the quality of image segmentation in the video monitoring system. The image segmentation method in the remote video monitoring system has been improved, in which, unlike the known ones: the source image is divided into RGB brightness channels; determination of the Euclidean distance between pixels; division of the entire set of image pixels into subsets; recalculation of “centers” of each subset; reassignment of new “centers” of each subset; minimization of total intra-cluster variance. Experimental studies of image segmentation from the remote video monitoring system were conducted. The image from the video monitoring system on the contact line during hostilities during the russian-ukrainian war is used as the source image. The segmentation results of this source image are given. It was established that there is a visual possibility of identifying objects of interest on segmented images. At the same time, it is possible to visually determine the elements of the protective cape only at k=4, while at k=2 and k=3 this possibility is complicated. The directions of further research are the determination of the optimal value of the value k when using the k-means algorithm and the evaluation of the quality of image segmentation in the remote video monitoring system.