RECURSIVE ANALYSIS ALGORITHM AND RESTORATION OF CONTOURS IN NAVIGATION AND GUIDANCE SYSTEMS

Abstract

In order to develop an object detection algorithm for embedded computing systems of opticalelectronic
complexes, an analysis of the existing world scientific and technical experience was carried out,
aimed at improving the process of identifying contours. Based on the analysis, the authors of the article
developed a new method for correcting contour images. This method implements an approach that allows
you to merge broken contours and apply filtering based on various parameters for optimal contour analysis.
The first step of the algorithm is to apply blur to the image, followed by the application of the Kenny
edge detection algorithm. Then the contours are thinned and the contour image is filtered to remove the
weakest contours. The next steps are the creation and processing of each individual contour, as well as
filtering outliers. The final stage is to connect and search for inflection points of the contour. The work
highlights both the advantages and disadvantages of classical edge extraction methods in the context of
their use in object detection algorithms. The authors of the study analyzed two classical morphological
operators - dilatation and erosion, as well as the existing basic variations of their use, such as opening
and closing, as methods for combining contours. As a result of a comparative analysis of the results of the
work of morphological operators of dilatation and erosion, as well as the main variations of their application,
with a recursive algorithm for analyzing and restoring contours, the advantage of the latter in terms
of preserving the integrity of the morphological characteristics of objects was revealed. The authors also
proposed ideas for further development of a recursive algorithm for analysis and restoration of contours,
as well as its further application in problems of detecting objects in images.