Tree skeleton extraction method based on 3D point cloud

A skeleton extraction and 3D technology, which is applied in the field of big data processing and tree 3D modeling, can solve the problems that the skeleton cannot guarantee the neutrality and accuracy, and the root node of the point cloud data is not properly selected, so as to achieve accurate tree skeleton results and reduce the effect of influence

Pending Publication Date: 2022-02-15
YANGTZE NORMAL UNIVERSITY
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Problems solved by technology

[0005] The object of the present invention is to provide a tree skeleton extraction method based on 3D point cloud, to solve the existing problems: the tree skeleton extraction

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  • Tree skeleton extraction method based on 3D point cloud
  • Tree skeleton extraction method based on 3D point cloud
  • Tree skeleton extraction method based on 3D point cloud

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Embodiment Construction

[0046] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0047] For details, please refer to figure 1 , figure 1 It is a flowchart of a tree skeleton extraction method based on 3D point cloud.

[0048] The tree skeleton extraction method based on 3D point cloud of the present invention comprises the following steps:

[0049] step 1:

[0050] Using octree and L1-median point method to reduce the scale of 3D point cloud data.

[0051] refer to figure 2 , in one embodiment, this step 1 includes the following steps: ...

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Abstract

The invention discloses a tree skeleton extraction method based on 3D point clouds, and relates to the technical field of big data processing and tree 3D modeling. The method comprises the following steps: reducing a scale of 3D point cloud data by using an octree method and an L1-median point method; constructing a ground root node; constructing a K-nearest neighbor graph, and dividing horizontal hierarchy sets; performing clustering to obtain point cloud data of different branches in the same horizontal hierarchy set; performing division by using the octree method, and calculating an L1-median point of each division to obtain skeleton points; and determining whether two class clusters are adjacent or not according to whether K-neighbors of members in the two class clusters have intersections or not, connecting the skeleton points of the adjacent class clusters to obtain an initial skeleton, and calculating a B-spline curve of the initial skeleton to obtain an optimized skeleton. Through the steps, influences of uneven 3D point cloud distribution on skeleton extraction can be effectively reduced, so that an extracted tree skeleton result is more accurate.

Description

technical field [0001] The invention belongs to the technical field of big data processing and tree 3D modeling, in particular to a tree skeleton extraction method based on 3D point cloud. Background technique [0002] As a "compact" representation of 3D models, skeletons can abstractly reflect the topological structure and body characteristics of plant models. Due to its simple topological structure and easy operation, the skeleton information is widely used in the fields of plant modeling, 3D animation design, medical imaging and surveying and mapping images, etc. [0003] Tree modeling has wide-ranging applications in computational forestry, functional structural plant modeling, urban planning, and many other fields. Tree skeletons are the basis for reconstructing biological and structural models of trees, and are of great significance in three-dimensional tree modeling and forestry research. Now, many tree skeleton extraction methods have been proposed. Verroust and L...

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Application Information

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IPC IPC(8): G06T7/50G06T17/00G06V10/762G06K9/62
CPCG06T7/50G06T17/00G06T2200/04G06T2207/10028G06T2207/20081G06F18/23
Inventor 程东东黄驰原黄金龙张素兰胡新桂俊
Owner YANGTZE NORMAL UNIVERSITY
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