A Skeleton-Based Method of Root System 3D Reconstruction and Phenotypic Parameter Measurement from Multi-View Image Sequence

Chengjia Xu, Ting Huang, Ziang Niu, Xinyue Sun, Yong He and Zhengjun Qiu ()
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Chengjia Xu: College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
Ting Huang: College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
Ziang Niu: College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
Xinyue Sun: College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
Yong He: College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
Zhengjun Qiu: College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China

Agriculture, 2025, vol. 15, issue 3, 1-17

Abstract: The phenotypic parameters of root systems are vital in reflecting the influence of genes and the environment on plants, and three-dimensional (3D) reconstruction is an important method for obtaining phenotypic parameters. Based on the characteristics of root systems, being featureless, thin structures, this study proposed a skeleton-based 3D reconstruction and phenotypic parameter measurement method for root systems using multi-view images. An image acquisition system was designed to collect multi-view images for root system. The input images were binarized by the proposed OTSU-based adaptive threshold segmentation method. Vid2Curve was adopted to realize the 3D reconstruction of root systems and calibration objects, which was divided into four steps: skeleton curve extraction, initialization, skeleton curve estimation, and surface reconstruction. Then, to extract phenotypic parameters, a scale alignment method based on the skeleton was realized using DBSCAN and RANSAC. Furthermore, a small-sized root system point completion algorithm was proposed to achieve more complete root system 3D models. Based on the above-mentioned methods, a total of 30 root samples of three species were tested. The results showed that the proposed method achieved a skeleton projection error of 0.570 pixels and a surface projection error of 0.468 pixels. Root number measurement achieved a precision of 0.97 and a recall of 0.96, and root length measurement achieved an MAE of 1.06 cm, an MAPE of 2.37%, an RMSE of 1.35 cm, and an R 2 of 0.99. The whole process of reconstruction in the experiment was very fast, taking a maximum of 4.07 min. With high accuracy and high speed, the proposed methods make it possible to obtain the root phenotypic parameters quickly and accurately and promote the study of root phenotyping.

Keywords: root phenotyping; Vid2Curve; point completion; thin structure 3D reconstruction (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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