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. 2022 Apr 27;12(1):6852.
doi: 10.1038/s41598-022-10921-6.

Point cloud registration method for maize plants based on conical surface fitting-ICP

Kai'xing Zhang  1 , He Chen  1 , Hao Wu  1 , Xiu'yan Zhao  2 , Chang'an Zhou  3
Affiliations

Point cloud registration method for maize plants based on conical surface fitting-ICP

Kai'xing Zhang et al. Sci Rep. .

Abstract

Reconstructing three-dimensional (3D) point cloud model of maize plants can provide reliable data for its growth observation and agricultural machinery research. The existing data collection systems and registration methods have low collection efficiency and poor registration accuracy. A point cloud registration method for maize plants based on conical surface fitting-iterative closest point (ICP) with automatic point cloud collection platform was proposed in this paper. Firstly, a Kinect V2 was selected to cooperate with an automatic point cloud collection platform to collect multi-angle point clouds. Then, the conical surface fitting algorithm was employed to fit the point clouds of the flowerpot wall to acquire the fitted rotation axis for coarse registration. Finally, the interval ICP registration algorithm was used for precise registration, and the Delaunay triangle meshing algorithm was chosen to triangulate the point clouds of maize plants. The maize plant at the flowering and kernel stage was selected for reconstruction experiments, the results show that: the full-angle registration takes 57.32 s, and the registration mean distance error is 1.98 mm. The measured value's relative errors between the reconstructed model and the material object of maize plant are controlled within 5%, the reconstructed model can replace maize plants for research.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Schematic diagram of data collection platform.
Figure 2
Figure 2
Experimental object and environment.
Figure 3
Figure 3
Flow chart of data collection process.
Figure 4
Figure 4
Flow chart of registration process.
Figure 5
Figure 5
Distance function model of conical surface.
Figure 6
Figure 6
Schematic diagram of single-view point cloud registration target.
Figure 7
Figure 7
Depth map generates point cloud image.
Figure 8
Figure 8
Point clouds from all angles.
Figure 9
Figure 9
Effect diagrams of conical surface fitting of flowerpot wall.
Figure 10
Figure 10
3D reconstruction model after coarse registration.
Figure 11
Figure 11
Remove the point clouds of flowerpot.
Figure 12
Figure 12
Effect diagrams of precise registration.
Figure 13
Figure 13
Comparison of registration results of three methods.
Figure 14
Figure 14
3D reconstruction results of maize plants.
Figure 15
Figure 15
Triangular mesh results of leaf.
Figure 16
Figure 16
Triangular mesh results of ear.
See this image and copyright information in PMC

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