Standard
Automatic Sown Field Detection Using Machine Vision and Contour Analysis. / Shirobokov, Mikhail ; Grishkin, Valeriy ; Kayumova, Diana .
COMPUTATIONAL SCIENCE AND ITS APPLICATIONS, ICCSA 2021, PT II: 21st International Conference, Cagliari, Italy, September 13–16, 2021, Proceedings, Part II. ed. / O Gervasi; B Murgante; S Misra; C Garau; Blecic; D Taniar; BO Apduhan; AMAC Rocha; E Tarantino; CM Torre. Springer Nature, 2021. p. 693-701 (Lecture Notes in Computer Science; Vol. 12950).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
Harvard
Shirobokov, M, Grishkin, V & Kayumova, D 2021,
Automatic Sown Field Detection Using Machine Vision and Contour Analysis. in O Gervasi, B Murgante, S Misra, C Garau, Blecic, D Taniar, BO Apduhan, AMAC Rocha, E Tarantino & CM Torre (eds),
COMPUTATIONAL SCIENCE AND ITS APPLICATIONS, ICCSA 2021, PT II: 21st International Conference, Cagliari, Italy, September 13–16, 2021, Proceedings, Part II. Lecture Notes in Computer Science, vol. 12950, Springer Nature, pp. 693-701, 21st International Conference on Computational Science and Its Applications, ICCSA 2021, Virtual, Online, Italy,
13/09/21.
https://doi.org/10.1007/978-3-030-86960-1_53
APA
Shirobokov, M., Grishkin, V., & Kayumova, D. (2021).
Automatic Sown Field Detection Using Machine Vision and Contour Analysis. In O. Gervasi, B. Murgante, S. Misra, C. Garau, Blecic, D. Taniar, BO. Apduhan, AMAC. Rocha, E. Tarantino, & CM. Torre (Eds.),
COMPUTATIONAL SCIENCE AND ITS APPLICATIONS, ICCSA 2021, PT II: 21st International Conference, Cagliari, Italy, September 13–16, 2021, Proceedings, Part II (pp. 693-701). (Lecture Notes in Computer Science; Vol. 12950). Springer Nature.
https://doi.org/10.1007/978-3-030-86960-1_53
Vancouver
Shirobokov M, Grishkin V, Kayumova D.
Automatic Sown Field Detection Using Machine Vision and Contour Analysis. In Gervasi O, Murgante B, Misra S, Garau C, Blecic, Taniar D, Apduhan BO, Rocha AMAC, Tarantino E, Torre CM, editors, COMPUTATIONAL SCIENCE AND ITS APPLICATIONS, ICCSA 2021, PT II: 21st International Conference, Cagliari, Italy, September 13–16, 2021, Proceedings, Part II. Springer Nature. 2021. p. 693-701. (Lecture Notes in Computer Science).
https://doi.org/10.1007/978-3-030-86960-1_53
Author
Shirobokov, Mikhail ; Grishkin, Valeriy ; Kayumova, Diana . /
Automatic Sown Field Detection Using Machine Vision and Contour Analysis. COMPUTATIONAL SCIENCE AND ITS APPLICATIONS, ICCSA 2021, PT II: 21st International Conference, Cagliari, Italy, September 13–16, 2021, Proceedings, Part II. editor / O Gervasi ; B Murgante ; S Misra ; C Garau ; Blecic ; D Taniar ; BO Apduhan ; AMAC Rocha ; E Tarantino ; CM Torre. Springer Nature, 2021. pp. 693-701 (Lecture Notes in Computer Science).
BibTeX
@inproceedings{b7d4d078cc234b44beeb05115c6878d1,
title = "Automatic Sown Field Detection Using Machine Vision and Contour Analysis",
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.",
keywords = "обработка изображений, контурный анализ, машинное зрение, Image processing, Machine vision, Contour analysis",
author = "Mikhail Shirobokov and Valeriy Grishkin and Diana Kayumova",
note = "Shirobokov M., Grishkin V., Kayumova D. (2021) Automatic Sown Field Detection Using Machine Vision and Contour Analysis. In: Gervasi O. et al. (eds) Computational Science and Its Applications – ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science, vol 12950. Springer, Cham. https://proxy.library.spbu.ru:2060/10.1007/978-3-030-86960-1_53; 21st International Conference on Computational Science and Its Applications, ICCSA 2021, ICCSA 2021 ; Conference date: 13-09-2021 Through 16-09-2021",
year = "2021",
month = sep,
day = "11",
doi = "10.1007/978-3-030-86960-1_53",
language = "English",
isbn = "978-3-030-86959-5",
series = "Lecture Notes in Computer Science",
publisher = "Springer Nature",
pages = "693--701",
editor = "O Gervasi and B Murgante and S Misra and C Garau and Blecic and D Taniar and BO Apduhan and AMAC Rocha and E Tarantino and CM Torre",
booktitle = "COMPUTATIONAL SCIENCE AND ITS APPLICATIONS, ICCSA 2021, PT II",
address = "Germany",
}
RIS
TY - GEN
T1 - Automatic Sown Field Detection Using Machine Vision and Contour Analysis
AU - Shirobokov, Mikhail
AU - Grishkin, Valeriy
AU - Kayumova, Diana
N1 - Shirobokov M., Grishkin V., Kayumova D. (2021) Automatic Sown Field Detection Using Machine Vision and Contour Analysis. In: Gervasi O. et al. (eds) Computational Science and Its Applications – ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science, vol 12950. Springer, Cham. https://proxy.library.spbu.ru:2060/10.1007/978-3-030-86960-1_53
PY - 2021/9/11
Y1 - 2021/9/11
N2 - 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.
AB - 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.
KW - обработка изображений
KW - контурный анализ
KW - машинное зрение
KW - Image processing
KW - Machine vision
KW - Contour analysis
UR - https://www.mendeley.com/catalogue/123a6a69-5148-3c4f-b00f-2f2540befe99/
U2 - 10.1007/978-3-030-86960-1_53
DO - 10.1007/978-3-030-86960-1_53
M3 - Conference contribution
SN - 978-3-030-86959-5
T3 - Lecture Notes in Computer Science
SP - 693
EP - 701
BT - COMPUTATIONAL SCIENCE AND ITS APPLICATIONS, ICCSA 2021, PT II
A2 - Gervasi, O
A2 - Murgante, B
A2 - Misra, S
A2 - Garau, C
A2 - Blecic, null
A2 - Taniar, D
A2 - Apduhan, BO
A2 - Rocha, AMAC
A2 - Tarantino, E
A2 - Torre, CM
PB - Springer Nature
T2 - 21st International Conference on Computational Science and Its Applications, ICCSA 2021
Y2 - 13 September 2021 through 16 September 2021
ER -
