Method and system of three-dimensional reconstruction of shape structure of trees in leaved state

Abstract

The invention discloses a method and a system of three-dimensional reconstruction of a shape structure of trees in a leaved state. The method comprises acquiring three-dimensional point cloud data of trees and carrying out preprocessing and simplifying processing to obtain simplified three-dimensional cloud data set of the trees, carrying out organ segmentation to the simplified three-dimensional point cloud data set of the trees to obtain the three-dimensional point cloud data of each organ, wherein the three-dimensional point cloud data of each organ comprise the three-dimensional point cloud data of a leaf organ, the three-dimensional point cloud data set of a main trunk, the three-dimensional point cloud data set of a main branch and the three-dimensional point cloud data set of a sprout, extracting the frameworks of limbs of the trees according to the three-dimensional point cloud data set of the main trunk, the three-dimensional point cloud data set of the main branch and the three-dimensional point cloud data set of the sprout and optimizing the frameworks of the limbs of the trees, carrying out meshing to the frameworks of the limbs of the trees to generate a three-dimensional mesh model of the limbs of the trees, classifying each limb of the frameworks of the limbs of the trees, and carrying out canopy three-dimensional reconstruction. The fast three-dimensional reconstruction of the shape structure of the trees in the leaved state is achieved, and therefore a method and a high-precision basic model support are provided for the structural analysis of the canopies of the trees, the evaluation of the physiological and ecological characteristics and the like.

Description

technical field [0001] The invention relates to the field of three-dimensional data processing of a leafy state tree, in particular to a method and system for three-dimensional reconstruction of the morphological structure of a leafy state tree. Background technique [0002] The 3D reconstruction and quantitative analysis of tree morphology are hot issues in the fields of agronomic research, graphic simulation, and popular science education. Compared with other plants such as field crops and flowers, trees not only have a taller shape, but also have a more complex canopy branch and leaf structure. , which brings great challenges to the information collection and automatic reconstruction of tree morphological structure in the leaf state. [0003] In the article "Evaluation of 3D Structure of Walnut Trees Based on Digitalization", a 3D digitizer is used to obtain spatial information of walnut trees, and based on these collected information, the 3D model of the tree is reconstr...

AI Technical Summary

Problems solved by technology

These methods all have a common disadvantage: due to the large number of branches and leaves in the tree canopy, it is often difficult to reconstruct twigs and leaves directly from the scan data, so these methods generate twigs and leaves by applying some random rules to achieve visual However, this kind of reconstruction has not reached the real sense of "reconstruction based on measurement data". The reconstructed three-dimensional tree canopy structure is still quite different from the real tree, especially the density of leaves, space Orientation, leaf area, etc. may have large errors from the actual situation, and it is difficult to apply to the research and analysis of tree canopy light distribution characteristics, spatial distribution of branches and leaves, plant type characteristics, etc.

However, this reconstruction method still has deficiencies. The main problems are as follows: first, the method does not segment the 3D point cloud when extracting tree trunk skeletons, so it needs to be extracted from the 3D point cloud data of the whole tree. The running speed will increase, and the accuracy of the extracted branch skeleton will also be affected due to the influence of canopy leaf information. It was added later by the canopy distribution model of the twigs of this type of tree, so it also reduced the accuracy of the final reconstructed tree 3D model

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