Development of a two-stage method for segmenting the color images of urban terrain acquired from space optic-electronic observation systems based on the ant algorithm and the hough algorithm

Abstract

The object of this study is the high level of errors of the first and second kind in the segmentation of images of urbanized areas acquired from space optoelectronic surveillance systems. The method of image segmentation of urbanized areas implies two stages and, unlike known ones: – takes into account each channel of brightness of the color space of the original image; – at the first stage, an ant algorithm is used; – image segmentation at the first stage is reduced to the calculation of the objective function, the areas of movement of ants, and the concentration of pheromone on the routes of ant movement. – at the second stage, the brightness and geometric shape of the elements of objects are taken into account; – contours and geometric primitives are defined in the Hough parameter space; – the objects of interest of the urbanized area in the space of the original image are determined. An experimental study into the segmentation of images of urbanized terrain acquired from space optoelectronic observation systems was carried out based on the ant algorithm and the Hough algorithm. The quality of image segmentation of the urbanized area was assessed. It was found that the error of the first kind when using the improved method of segmentation is reduced by 2.75 %. The error of the second kind is reduced by 3.91 % when using the improved method of segmentation. This reduction became possible due to the use of an improved method of segmenting the image of an urbanized area by the ant algorithm at the first stage. Compared to Canny's algorithm, the error of the first kind decreased by 8.9 %, and the error of the second kind decreased by 11.0 %. Methods for segmenting images of urbanized areas acquired from space optoelectronic surveillance systems can be implemented in software and hardware systems of image processing