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Trudy SPIIRAN, 2018, Issue 61, Pages 172–196
DOI: https://doi.org/10.15622/sp.61.7
(Mi trspy1036)
 

This article is cited in 3 scientific papers (total in 3 papers)

Artificial Intelligence, Knowledge and Data Engineering

Hough transform application to digitize rectangular spatial objects on aerospace imagery

S. Yu. Miroshnichenko, V. S. Titov, E. N. Dremov, S. A. Mosin

Southwest State University (SWSU)
Abstract: The paper describes the method of development for the remote sensing data processing to speed up the digitizing workflow. The method is designed to digitize rectangular objects using their approximate spatial positions and provides an automatic estimation of the orientation and aspect ratio.
The paper contains a formal statement of the problem of digitizing an object with the desired geometric shape using it’s apriori known spatial position on a source image. The method creates polygonal representations of rectangular spatial objects from one or a few reference points set by an operator. It is based on source image’s pixels clustering using spectral bands as a feature space. The following Hough transform incorporates local direction of intensity gradient to estimate object’s orientation and reduce computational complexity together with low-pass filtering within an accumulation process to improve robustness. It is shown that the developed method can be modified to digitize objects of any analytically described shape.
The method is designed to allow easy user interaction without any significant delays and to provide transparent and predictable control of an output object’s polygon size.
To investigate the developed method a test dataset with more than 700 rectangular objects was used. The root-mean-square error of object’s points positioning, mean rotation error in polar coordinates and a Jaccard index were used to measure a precision of the digitized objects. The experiment results demonstrate that digitizing workflow is accelerated by 25–40% using the software implementing the developed method without a significant precision loss.
Keywords: remote sensing data, automated digitizing, image processing, hough transform.
Funding agency Grant number
Ministry of Education and Science of the Russian Federation 2.9102.2017/БЧ
This research is supported by the state assignment (project №2.9102.2017/BCh).
Received: 13.03.2018
Document Type: Article
UDC: 004.92
Language: English
Citation: S. Yu. Miroshnichenko, V. S. Titov, E. N. Dremov, S. A. Mosin, “Hough transform application to digitize rectangular spatial objects on aerospace imagery”, Tr. SPIIRAN, 61 (2018), 172–196
Citation in format AMSBIB
\Bibitem{MirTitDre18}
\by S.~Yu.~Miroshnichenko, V.~S.~Titov, E.~N.~Dremov, S.~A.~Mosin
\paper Hough transform application to digitize rectangular spatial objects on aerospace imagery
\jour Tr. SPIIRAN
\yr 2018
\vol 61
\pages 172--196
\mathnet{http://mi.mathnet.ru/trspy1036}
\crossref{https://doi.org/10.15622/sp.61.7}
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  • https://www.mathnet.ru/eng/trspy/v61/p172
  • This publication is cited in the following 3 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Informatics and Automation
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