Pine crown density determination using local binary patterns | Научно-инновационный портал СФУ

Pine crown density determination using local binary patterns

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: 6th International Conference Information Technology and Nanotechnology. Session Image Processing and Earth Remote Sensing, ITNT-IPERS 2020

Год издания: 2020

Ключевые слова: classification, forest health, image processinggenius, texture analysis

Аннотация: Competent assessment of the plantation sanitary condition allows you to plan various forest health protection measures. Automation of the tree state category assessment process could be implemented by fuzzy logic. The key role in this process plays such characteristic as the crown density degree. The paper proposes an algorithm for automatic estimating of the crown density degree using local binary patterns. Histograms of crown fragments of various densities are built on the basis of uniform patterns; the Kullback-Leibler distance is used as a measure of the difference between the two histograms. Experimental studies conducted on 1636 images of crown fragments confirm the effectiveness of applying local binary patterns to the task of the crown density degree estimation. Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)

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Издание

Журнал: CEUR Workshop Proceedings

Выпуск журнала: Vol. 2665

Номера страниц: 41-43

ISSN журнала: 16130073

Авторы

  • Pyataev A. (Reshetnev Siberian State University of Science and Technology, Brunch of FBI “Russian Centre of Forest Health”, “Centre of Forest Health of Krasnoyarsk Krai”, Krasnoyarsk, Russian Federation)
  • Pyataeva A. (Reshetnev Siberian State University of Science and Technology, Siberian Federal University, Krasnoyarsk, Russian Federation)
  • Brezhnev R. (Siberian Federal University, Krasnoyarsk, Russian Federation)

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