ITM Web Conf.
Volume 59, 2024II International Workshop “Hybrid Methods of Modeling and Optimization in Complex Systems” (HMMOCS-II 2023)
|Number of page(s)
|Data Mining, Machine Learning and Patern Recognition
|25 January 2024
Algorithm for extracting contours of agricultural crops images
Tashkent Institute of Irrigation and Agricultural Mechanization Engineers - National Research University, Tashkent, Uzbekistan Sejong University,
2 Seoul , Korea
3 Tashkent University of Information Technology after named Muhammad al-Khwarizmi, Tashkent, Uzbekistan
* Corresponding author: m firstname.lastname@example.org
Abstract. Currently, identification of crop diseases and their prevention is one of the main problems in the field of agriculture. Conventional visual inspection is a time and money consuming process for farms. Therefore, images taken by unmanned aerial devices or satellites are used to assess the condition of crops, control them and identify diseases. In particular, when identifying crop diseases, it is necessary to first solve the problem of automatic recognition of their type through the image of crops. Usually contour separation algorithms are widely used in the segmentation of objects in the image. This work is aimed at solving the problem of separating the contour of the object, in which algorithms are formed based on Canny, Sobel and Robinson filters, which are considered to be popular and classical methods of contour separation, and their various combinations. In the computational experiments, a set of contour images, whose contours were separated by an expert, was used. Evaluation was performed by comparing the image obtained by applying the combination of filters to the original image and the corresponding contour image pixels separated by an expert. The proposed approach has been tested on a set of plant leaf images and shown to be effective.
© The Authors, published by EDP Sciences, 2024
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