Research on Measurement Method of Leaf Length and Width Based on Point Cloud

Abstract

Leaf is an important organ for photosynthesis and transpiration associated with the plants’ growth. Through the study of leaf phenotype, it the physiological characteristics produced by the interaction of the morphological parameters with the environment can be understood. In order to realize the assessment of the spatial morphology of leaves, a method based on three-dimensional stereo vision was introduced to extract the shape information, including the length and width of the leaves. Firstly, a depth sensor was used to collect the point cloud of plant leaves. Then, the leaf coordinate system was adjusted by principal component analysis to extract the region of interest; and compared with a cross-sectional method, the geodesic distance method, we proposed a method based on the cutting plane to obtain the intersecting line of the three-dimensional leaf model. Eggplant leaves were used to compare the accuracy of these methods in the measurement of a single leaf.

Plant phenotyping relevance

三次元ステレオビジョンと点群処理により葉長・葉幅を抽出する測定法を開発し、既存手法と精度比較しており、植物フェノタイピング手法が研究の中心である。

Code and data availability

The paper describes eggplant leaf point cloud data collected with Kinect2.0 and custom PCA/cutting-plane measurement methods, but no public dataset, image, code, or model deposit is mentioned. The only URLs are generic documentation for the Point Cloud Library and MATLAB PCA, which are cited tools, not paper-specific资产

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