A Support Vector Model of Pruning Trees Evaluation Based on OTSU Algorithm
Yuefei Chen, Xinli Zheng, Chunhua Ju, Fuguang Bao

TL;DR
This paper introduces OTSU-SVM, a novel model combining OTSU algorithm and SVM to evaluate tree pruning performance based on branch and leaf shadows, aiming to reduce reliance on human judgment.
Contribution
The paper presents a new pruning evaluation model that integrates OTSU algorithm with SVM for more robust and accurate assessment of pruning quality.
Findings
Achieved 80% accuracy in pruning evaluation.
Demonstrated improved evaluation robustness with OTSU integration.
Potential to enhance fruit production through better pruning assessment.
Abstract
The tree pruning process is the key to promoting fruits' growth and improving their productions due to effects on the photosynthesis efficiency of fruits and nutrition transportation in branches. Currently, pruning is still highly dependent on human labor. The workers' experience will strongly affect the robustness of the performance of the tree pruning. Thus, it is a challenge for workers and farmers to evaluate the pruning performance. Intended for a better solution to the problem, this paper presents a novel pruning classification strategy model called "OTSU-SVM" to evaluate the pruning performance based on the shadows of branches and leaves. This model considers not only the available illuminated area of the tree but also the uniformity of the illuminated area of the tree. More importantly, our group implements OTSU algorithm into the model, which highly reinforces robustness of the…
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Taxonomy
TopicsPlant Physiology and Cultivation Studies · Leaf Properties and Growth Measurement · Horticultural and Viticultural Research
MethodsPruning
