Automatic Sown Field Detection Using Machine Vision and Contour Analysis

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Abstract

The paper proposes a prototype of an algorithm based on the use of machine vision methods, which allows automatic identification and selection of fields sown with agricultural crops on images. The algorithm works with satellite images and consists of two stages. At the first stage, the image undergoes initial processing, after which edge detection and contour finding algorithms are applied to it. At the second stage, the obtained image areas enclosed within the contours are represented as a set of numerical and logical parameters which are used for filtering and classification of the areas.
Translated title of the contributionАвтоматическое распознавание засеянных полей на спутниковых снимках с использованием машинного зрения и контурного анализа
Original languageEnglish
Title of host publicationComputational Science and Its Applications – ICCSA 2021
Subtitle of host publication21st International Conference, Cagliari, Italy, September 13–16, 2021, Proceedings, Part II
PublisherSpringer Nature
Pages693-701
ISBN (Electronic)978-3-030-86960-1
ISBN (Print)978-3-030-86959-5
DOIs
StatePublished - 11 Sep 2021
Event21st International Conference on Computational Science and Its Applications - Cagliari, Italy
Duration: 13 Sep 202116 Sep 2021

Publication series

NameLecture Notes in Computer Science
Volume12950

Conference

Conference21st International Conference on Computational Science and Its Applications
Abbreviated titleICCSA 2021
Country/TerritoryItaly
CityCagliari
Period13/09/2116/09/21

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