The object of this research is the process of segmentation of camouflaged military equipment in images from space surveillance systems.
The method of segmentation of camouflaged military equipment in images from space surveillance systems has been improved using a genetic algorithm. Unlike known methods, the method of segmentation of camouflaged military equipment using a genetic algorithm involves the following:
– highlighting brightness channels in the Red-Green-Blue color space;
– the use of a genetic algorithm in the image in each channel of brightness of the RGB color space;
– image segmentation is reduced to the formation of generations and populations of chromosomes, the calculation of the objective function, selection, crossing, mutation, and decoding of chromosomes in each brightness channel of the Red-Green-Blue color space.
Experimental studies were conducted on the segmentation of camouflaged military equipment using a genetic algorithm. It is established that the improved method of segmentation using a genetic algorithm makes it possible to segment images from space surveillance systems.
A comparison of the quality of segmentation was carried out. It is established that the improved method of segmentation using a genetic algorithm reduces segmentation errors in the following way:
– compared to the known k-means method, by an average of 15 % of errors of the first kind and an average of 7 % of errors of the second kind;
– compared to the method of segmentation based on the algorithm of swarm of particles, by an average of 3.8 % of errors of the first kind and an average of 2.9 % of errors of the second kind.
The improved segmentation method using a genetic algorithm can be implemented in software and hardware imaging systems from space surveillance systems
The object of this study is the process of making a management decision based on the analysis of information from space surveillance systems.
Unlike the well-known ones, the method of making a management decision based on the analysis of information from space surveillance systems involves:
– segmentation of an optoelectronic image;
– determination and prediction of a priori probabilities of possible environmental states;
– an application for making a management decision of a combination of Bayes criteria and a minimum of variance.
Experimental studies have been carried out on making a management decision based on the analysis of information from space surveillance systems. To conduct experimental research on making a management decision based on the analysis of information from space surveillance systems, a model problem has been stated. As images from space surveillance systems, images obtained from the WorldView-2 spacecraft (USA) with a difference of four days were considered. The vegetation index was calculated, and the probabilities of degradation dynamics of plant segments were determined. It was established that the maximum value of the estimated functional is achieved when choosing a solution φ1, which is optimal according to the Bayesian criterion and the criterion of minimum variance.
The quality of management decision-making was assessed by the well-known and developed methods. To assess the quality of management decision-making, the concepts of objectivity of the decision-making method and the selectivity of the decision-making method by known and developed method were introduced. It has been established that both methods are objective, and the improved method is more selective (the gain is 2.6 times). This becomes possible through the use of information from space surveillance systems.
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