Soybean plant rapid three-dimensional reconstruction method based on phenotypic-oriented accurate identification

Abstract

The invention discloses a soybean plant rapid three-dimensional reconstruction method based on phenotype-oriented accurate identification, and the method comprises the steps of enabling a user to useKinect to scan a soybean plant, i.e., a soybean plant, at intervals of a set angle, and obtaining a plurality of frames of point cloud scenes where the soybean plant is placed on an automatic rotatingdisc; after removing a point cloud background through straight-through filtering, calculating a rough registration matrix by using a Rodrigs formula according to a rotation angle provided by a user,performing fine registration by using an ICP algorithm, performing hierarchical clustering on plant point clouds to obtain skeleton points, setting each point to be adjacent to nearest K points for the skeleton points to obtain a plurality of connected components, performing trunk Dijkstra path growth, branch growth point selection and branch communication component Dijkstra path growth on trunk communication components where root nodes are located, and finally performing three-dimensional visualization of a plant skeleton through a pyvista visualization library. According to the invention, the plant point cloud does not need to be processed in advance through software to obtain the parameters, the purchase expenditure of modeling software and the learning and using time cost of the modeling software are saved, and the invention is more efficient.

Description

technical field [0001] The invention relates to the technical field of computer graphics and three-dimensional point cloud reconstruction, in particular to a fast three-dimensional reconstruction method for bean plants based on accurate phenotype identification. Background technique [0002] 3D plant reconstruction is a research hotspot in the fields of computer graphics, computer vision, and digital agriculture. Real and accurate 3D plant shapes can be applied to the fields of game movie CG, virtual reality, and agricultural digital production. The realistic three-dimensional plant model is also the most representative natural landscape model in the network virtual scene, which is widely used in the fields of virtual tourism, virtual city and virtual ecological landscape simulation, and digital agricultural production. At the same time, digital plants are the basic research work of digital agriculture. It comprehensively uses digital technology to conduct quantitative and v...

AI Technical Summary

Problems solved by technology

The plant point cloud is usually composed of a trunk and many complex and dense plant stem branches and leaves. It is not easy to extract the skeleton of the plant from the point cloud scanned by the depth camera.

Due to the complexity of branches and leaves, the accuracy limitation of scanning equipment and the noisy or incomplete data, the extraction of skeleton points is more difficult.

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