Coconut Point Cloud Generation from CT Images

After obtaining the CT image of the coconut, the next goal was to convert them into a point cloud model [15 ]. In MATLAB (MATLAB version: R2020b), the program first calls the ID of the target coconut, which is compressed and reconstructed into an array of 512

*

512

*

6. According to the Definition 1, the 6 columns are

⟨ x, y, z, r, g, b ⟩

. The converted data of each image are stacked, the points are drawn according to the corresponding coordinate information values, and the 3D point cloud is displayed (Fig. 2c).

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Zhang Y., Liu Q., Chen J., Sun C., Lin S., Cao H., Xiao Z, & Huang M. (2023). Developing non-invasive 3D quantificational imaging for intelligent coconut analysis system with X-ray. Plant Methods, 19, 24.

Publication 2023

Coconut

Corresponding Organization :

Other organizations : Hainan University, Central South University, Coconut Research Institute, Chinese Academy of Tropical Agricultural Sciences, Xi'an University of Technology

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Variable analysis

independent variables

ID of the target coconut

dependent variables

Point cloud model

control variables

Dependent variables not explicitly mentioned.
Control variables not explicitly mentioned.

controls

No positive or negative controls were mentioned in the given information.

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