ACCURACY RESEARCH METHOD OF THE MODIFIED ALGORITHM FOR DETECTING LINEAR LANDMARKS

Authors

  • M. P. Mukhina National Aviation University, Kyiv
  • O. Yu. Tkachenko National Aviation University, Kyiv
  • I. V. Barkulova National Aviation University, Kyiv

DOI:

https://doi.org/10.18372/1990-5548.56.12940

Keywords:

Houghline transform method, Canny detector, linear landmarks, aided navigation

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.

Author Biographies

M. P. Mukhina, National Aviation University, Kyiv

Aviation Computer-Integrated Complexes Department, Educational & Research Institute of Information and Diagnostic Systems

Doctor of Engineering Science. Professor

O. Yu. Tkachenko, National Aviation University, Kyiv

Aviation Computer-Integrated Complexes Department, Educational & Research Institute of Information and Diagnostic Systems

Master’s

I. V. Barkulova, National Aviation University, Kyiv

Aviation Computer-Integrated Complexes Department, Educational & Research Institute of Information and Diagnostic Systems

Post-graduate student

References

Kusainov A. A. Development of control system un-manned aerial vehicle along a predetermined path. – Novosibirsk, 2013. – 60 p.

Hartley R., Zisserman A. Multiple view geometry in computer vision. – Australian National University, Canberra, Australia. – Cambridge University Press 2000, 2003. – 673 p.

В.О. Рогожин, В.М. Синєглазов, М.К. Філяшкін. Пілотажно-навігаційнйкомплексиповітрянихсуден: Підручник – К.: НАУ, 2005.

Javed, and M. Shah, “Tracking and object classification for automated surveillance,” in European Conference on Computer Vision, Springer, Berlin, Heidelberg, 2002, pp. 343–357.

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Issue

Vol. 2 No. 56 (2018)

Section

TRANSPORT SYSTEMS

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