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, PT II
Subtitle of host publication21st International Conference, Cagliari, Italy, September 13–16, 2021, Proceedings, Part II
EditorsO Gervasi, B Murgante, S Misra, C Garau, Blecic, D Taniar, BO Apduhan, AMAC Rocha, E Tarantino, CM Torre
PublisherSpringer Nature
Pages693-701
Number of pages9
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, ICCSA 2021 - Virtual, Online, Italy
Duration: 13 Sep 202116 Sep 2021

Publication series

NameLecture Notes in Computer Science
PublisherSPRINGER INTERNATIONAL PUBLISHING AG
Volume12950
ISSN (Print)0302-9743

Conference

Conference21st International Conference on Computational Science and Its Applications, ICCSA 2021
Abbreviated titleICCSA 2021
Country/TerritoryItaly
CityVirtual, Online
Period13/09/2116/09/21

    Research areas

  • Image processing, Machine vision, Contour analysis

ID: 86580936