Anti-overlapping plant point cloud single-leaf segmentation method

A single blade and point cloud technology, applied in image analysis, image data processing, instruments, etc., can solve problems such as difficult to accurately segment a single blade, and achieve the effect of suppressing segmentation noise

Pending Publication Date: 2020-11-10
DONGHUA UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is: thoroughly solve the problem that it is difficult to accurately segment a single blade in a complex canopy

Method used

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  • Anti-overlapping plant point cloud single-leaf segmentation method
  • Anti-overlapping plant point cloud single-leaf segmentation method
  • Anti-overlapping plant point cloud single-leaf segmentation method

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Embodiment Construction

[0069] Below in conjunction with specific embodiment, further illustrate the present invention. It should be understood that these examples are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the teachings of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of the present application.

[0070] figure 1 It is a 3D point cloud imaging tool, where (a) is a binocular stereo vision imaging system, (b) is a Microsoft Kinect v2 variable structured light sensor, and (c) is a multi-view stereo vision imaging system. The binocular stereo vision imaging system consists of two network cameras, a tripod and a laptop computer. The binocular stereo vision imaging technology uses the cameras to obtain two-dimensional images ...

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Abstract

The invention relates to an anti-overlapping plant point cloud single-leaf segmentation method, which comprises the following steps of: preprocessing plant point cloud data, namely filtering out detection noise and non-plant leaf information (such as stems and surrounding backgrounds) existing in plant point clouds; performing a 3D joint filtering process on the obtained plant canopy point cloud;carrying out patch over-segmentation on the blade outer edge point cloud part removed by the joint filtering operator, then adding back the segmented blade center point cloud, and carrying out patch-based region growth outwards by using the marked blade center. The result after growth is a final segmentation result of a single leaf of a plant canopy. Compared with the prior art, single leaf segmentation can be carried out on point clouds obtained in various imaging modes, the problem that accurate, efficient and automatic single leaf segmentation is difficult to carry out due to the leaf overlapping phenomenon in the plant point clouds is solved, and the method has the advantages of being high in single leaf segmentation precision, high in universality and the like.

Description

technical field [0001] The invention relates to the fields of agricultural engineering, plant phenotype, and computer graphics, in particular to a plant point cloud single-leaf segmentation method resistant to leaf overlapping. Background technique [0002] Plant phenotype is determined or influenced by genes and environmental factors, reflecting all the physical, physiological, biochemical characteristics and traits of plant structure and composition, plant growth and development process and results. With the in-depth study of plant functional genomics and crop molecular breeding, traditional phenotypic observation has become the main bottleneck restricting its development, and high-throughput plant phenotyping research is an effective way to solve this dilemma. Plant phenotype research is a comprehensive evaluation of plant complex traits (plant growth, development, tolerance, resistance, structure, physiology, ecology, yield, etc.), and the basic parameters that constitut...

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Application Information

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IPC IPC(8): G06T7/11G06T5/00G06T5/30G06K9/62
CPCG06T7/11G06T5/30G06T2207/30188G06F18/23213G06T5/70
Inventor 李大威曹燕
Owner DONGHUA UNIV
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