The invention provides a
plant point cloud blade segmentation and phenotypic characteristic measurement method, comprising the steps: firstly, performing accurate
point cloud three-dimensional reconstruction on potted plants by using a multi-view stereoscopic vision
algorithm; secondly, removing non-blade parts in the
plant point cloud by using a region and color-based filter and a normal vector difference
algorithm; and then realizing single-blade segmentation on the
canopy with the blade overlapping phenomenon by means of curvature information and a multi-feature region growth
algorithm. Foreach single blade, a 3D bounding box of the blade is estimated by utilizing PCA, and the blade inclination angle can be calculated as an included angle between the height direction of the bounding box and the Z axis of a
crop coordinate
system, and the blade length and the blade width are the length and the width of the bounding box. The
plant point cloud blade segmentation and phenotypic characteristic measurement method can realize automatic blade segmentation of potted plants with overlapped and clustered blades, has high precision and real-time performance for extracting phenotypic information such as blade area, blade length, blade width, blade inclination angle and the like, and is suitable for high-
throughput blade
phenotypic analysis.