Research on rapeseed plant modeling and optimization from 3D point cloud

As one of the most important oil crops, the high-accuracy rapeseed digital model contributes to agronomic horticulture, crop-breeding and plant genetics research. How to build a three-dimensional (3D) plant model, especially a high-quality leaf model, has great significance to the research on the rapeseed plant growth status. In this paper, we present a three-dimensional oilseed rape plant reconstruction method based on point cloud data. Firstly, we provide a novel approach to reconstruct 3D rapeseed shape model by utilizing the acquired 3D point clouds, and the original point cloud acquired via 3D laser scanning should be preprocessed, the main idea of processing includes de-noising and simplifying the original point clouds. Then the meshing method and mesh optimization process have been carried out to attain a high-quality 3D rapeseed plant mesh model. Thus the rapeseed plants can be non-destructively monitored by measuring the reconstructed rapeseed plant models, and we can obtain the needed parameters such as the leaf area. Experiments are implemented on real datasets, and the results indicate that the accuracy of the leaf area values are highly closed to the real values, which are measured by conventional digital processing methodology.