Vision-Based Crop Trait Analysis System 


Vol. 46,  No. 12, pp. 2419-2428, Dec.  2021
10.7840/kics.2021.46.12.2419


PDF Full-Text
  Abstract

In this paper, a vision-based crop trait analysis system was implemented. The proposed system consists of an input part, a machine vision part, and an output part. The input part receives user commands and image files using the mouse and keyboard and transmits them to the system, the machine vision part processes the input image files according to the user commands to extract data, and the output part outputs the extracted data to the monitor and saves it as an excel file and an image file. For the robustness of system production, it was implemented using the Python-based OpenCV library, and in order to compensate for the limitations of the open source library, some of the system algorithms were directly implemented. The system of this paper consists of quit, open file, delete file, save image/data, image binarization, image size filtering, marker setting, analysis area setting, align, rotation, edit color, measurement point setting, traits description, etc. By combining the configured functions, eight quantitative traits of crop - area, width, height, height 1, height 2, center length, center thickness, and line length - can be measured quickly compared to the existing manual measurement method. As a result of evaluating the performance of the system, measurement accuracy of 0.15mm and analysis speed 37% faster than the existing analysis program can be obtained.

  Statistics
Cumulative Counts from November, 2022
Multiple requests among the same browser session are counted as one view. If you mouse over a chart, the values of data points will be shown.


  Cite this article

[IEEE Style]

K. Park, K. Choi, S. Kim, H. Ahn, S. Jeong, "Vision-Based Crop Trait Analysis System," The Journal of Korean Institute of Communications and Information Sciences, vol. 46, no. 12, pp. 2419-2428, 2021. DOI: 10.7840/kics.2021.46.12.2419.

[ACM Style]

Keunho Park, Kang-in Choi, Seo-jeong Kim, Hyung-Geun Ahn, and Sung-Hwan Jeong. 2021. Vision-Based Crop Trait Analysis System. The Journal of Korean Institute of Communications and Information Sciences, 46, 12, (2021), 2419-2428. DOI: 10.7840/kics.2021.46.12.2419.

[KICS Style]

Keunho Park, Kang-in Choi, Seo-jeong Kim, Hyung-Geun Ahn, Sung-Hwan Jeong, "Vision-Based Crop Trait Analysis System," The Journal of Korean Institute of Communications and Information Sciences, vol. 46, no. 12, pp. 2419-2428, 12. 2021. (https://doi.org/10.7840/kics.2021.46.12.2419)

Search
(IN TITLE, AUTHOR, ABSTRACT,KEYWORDS)

Advanced Search ▼

POPULAR KEYWORDS
(TOP 10 KEYWORDS)

Recent Publications
(LAST 3 YEARS)






pISSN : 1226 - 4717
eISSN : 2287 - 3880