Evaluates an image processing method to enhance leaf-cutting automation in tomato cultivation, suggesting improved agricultural efficiency.
In recent years, labor shortages caused by the aging and declining workforce have become a serious issue in Japanese agriculture. To address this problem, agricultural robots for automating labor-intensive tasks have been developed. This paper is focused on automating the leaf-cutting task in tomato cultivation, which is essential for promoting growth and preventing disease, and is proposed an image-processing-based method to detect leaf-cutting points. The effectiveness of the proposed algorithm is evaluated through the quantitative analysis of detection accuracy.
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Moriwaki et al. (2026) studied this question.
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