Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
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 contribution | Автоматическое распознавание засеянных полей на спутниковых снимках с использованием машинного зрения и контурного анализа |
---|---|
Original language | English |
Title of host publication | COMPUTATIONAL SCIENCE AND ITS APPLICATIONS, ICCSA 2021, PT II |
Subtitle of host publication | 21st International Conference, Cagliari, Italy, September 13–16, 2021, Proceedings, Part II |
Editors | O Gervasi, B Murgante, S Misra, C Garau, Blecic, D Taniar, BO Apduhan, AMAC Rocha, E Tarantino, CM Torre |
Publisher | Springer Nature |
Pages | 693-701 |
Number of pages | 9 |
ISBN (Electronic) | 978-3-030-86960-1 |
ISBN (Print) | 978-3-030-86959-5 |
DOIs | |
State | Published - 11 Sep 2021 |
Event | 21st International Conference on Computational Science and Its Applications, ICCSA 2021 - Virtual, Online, Italy Duration: 13 Sep 2021 → 16 Sep 2021 |
Name | Lecture Notes in Computer Science |
---|---|
Publisher | SPRINGER INTERNATIONAL PUBLISHING AG |
Volume | 12950 |
ISSN (Print) | 0302-9743 |
Conference | 21st International Conference on Computational Science and Its Applications, ICCSA 2021 |
---|---|
Abbreviated title | ICCSA 2021 |
Country/Territory | Italy |
City | Virtual, Online |
Period | 13/09/21 → 16/09/21 |
ID: 86580936