Abstract
A search algorithm for the most extended landmark by which unmanned aerial vehicle can be followed by and implemented flight correction was proposed. The software was developed based on the Python language. The functionality of this software is to detect the linear landmarks from images of geophysical field, received from unmanned aerial vehicle in real time. Images were processed by Hough Line Transform method. As a result, obtained visualization of the object detection with the greatest length, as linear landmark, which allows to estimate unmanned aerial vehicle location. The visual analysis of the effectiveness of this algorithm for inertial navigation system correction shown that the algorithmic software is appropriate for use on unmanned aerial vehicle board and due to applying computer vision systems, gives as correct results of location determining as possible.
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