An information technique for segmentation of military assets in conditions of uncertainty of initial data

Abstract

To solve the applied task of detecting military assets in aerospace images the presented paper investigates the processes of constructing segmented maps of the images. The goal is to develop an information technique for detecting military assets in conditions of uncertainty of initial data. To achieve the goal, the following tasks were formulated: 1) to analyze usability of the existing segmentation methods for automatic detection of military assets in the images; 2) if the existing methods are inapplicable, to develop a new algorithm to solve the problem. In the paper the following methods are used: the methods of digital image processing, the methods of Boolean algebra and fuzzy sets, the methods of statistical analysis. The following results are received. Analysis of the known segmentation methods showed that due to camouflage coloring of the military assets, similarity of their color characteristics to those of underlying surfaces and due to the presence of large number of textured fragments in the images those methods provide segmented maps of poor quality. Among the common problems arising when conventional methods are used there are wrong segmentation, when the received contours do not coincide with the borders of the objects of interest; oversegmentation, when there are a lot of minor segments which produce "litter" objects; undersegmentation, when potentially possible segments are missed etc. As the conventional methods are inapplicable, in the paper it is suggested using the fuzzy logic systems. For each pixel the probability of the fact that the pixel belongs to the object or to the background is calculated. For making decision whether a pixel belongs to the object the production rules based on the chosen most significant factors (probabilistic values of spectral sub-bands, belonging of the neighboring pixels to the object, jumps of brightness in spectral sub-bands on the object's borders) are constructed. Conclusion. The suggested technique ensures high-quality definition of objects' borders, thus considerably increasing the reliability of military assets recognition.