INFORMATIONAL SWARM TECHNOLOGY OF THE THEMATIC IMAGES SEGMENTATION OBTAINED FROM ON-BOARD SYSTEMS OF OPTICAL-ELECTRONIC OBSERVATION

Abstract

The subject matter of the article is the method of thematic segmentation of a color image of an on-board opticalelectronic surveillance system. The goal is the development of a thematic segmentation method based on the artificial bee colony method. The tasks are: analysis of the properties of meta-heuristic optimization methods, analysis of the basic operations of meta-heuristic optimization methods, formulation of the optimization problem of selecting the thematic segmentation threshold for optical-electronic imaging using the swarm method of artificial bee colony, developing a scheme for thematic segmentation of optical-electronic imaging systems optoelectronic observation, obtaining histograms of the distribution of brightness in each channel of the brightness of a color image, presentation of the essence the method of thematic segmentation of the color isobarbation of the on-board optical-electronic surveillance system, the analysis of the iterative process of finding the optimal thresholds for the thematic segmentation in the brightness channels of the optical-electronic image, determining the optimal value of the threshold level for each channel of the brightness - electronic image, visual assessment of the quality of the segmented image. The methods used are: methods of probability theory, mathematical statistics, swarm intelligence, data clustering, evolutionary computing, optimization methods, mathematical modeling and digital image processing. The following results were obtained. It has been established that for thematic segmentation of an image of an onboard system of optical-to-electronic observation, it is advisable to use metaheuristic optimization methods. It has been established that the method of thematic segmentation of a color image is based on the swarm method of an artificial bee colony, the sum of variances of the thematic segments is used as the target function, and the optimization problem is to minimize the objective function. It is established that the optimal value of the threshold level for each brightness channel corresponds to the minimum of the objective function for each brightness channel. The methods used are: methods of probability theory, mathematical statistics, swarm intelligence, data clustering, evolutionary calculations, optimization methods, mathematical modeling and digital image processing. The following results were obtained. It has been established that for thematic segmentation of an image of an onboard system of optical-electronic observation it is expedient to use metaheuristic optimization methods. It has been established that the method of thematic segmentation of a color image is based on the swarm method of an artificial bee colony, the sum of variances of the thematic segments is used as the objective function, and the optimization problem is to minimize the objective function. It has been established that the optimal value of the threshold level for each brightness channel corresponds to the minimum of the objective function for each brightness channel. Conclusions. The scientific novelty of the results obtained is as follows: an increase in the visual quality of the segmented image, which subsequently significantly affects the solution of the problem of image decoding.