Automatic Tomato Harvesting System using Image Processing Techniques

Abstract: The efficiency of farming is increasingly dependent on precision farming. This is due to significant competition, the emergence of new pests and bacteria that spoil the crop, environmental problems, and many other factors from which products lose their value. One of such factors is the timeliness of harvesting. This is especially true in greenhouse complexes, where harvesting occurs regardless of the season, regularly after the ripening of products. The ripening of tomatoes is quite unpredictable, so it is necessary to identify the ripening process to harvest in time. Machine vision can solve this problem by highlighting a separate spectrum of color, which is characteristic of already-ripe tomatoes. Therefore, the article proposes a method for identifying the processes of tomato ripening using image processing methods based on color detectors. The OpenCV library was used for software implementation. A Rasbberry Pi unicameral computer was used to solve this problem.

Keywords: Harvesting, Image processing, Tomato