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A Chinese wolfberry identification counting method based on PointNet + + Network

A counting method and wolfberry technology, applied in the field of image recognition, can solve problems such as difficulty in accurate recognition by two-dimensional image recognition methods

Active Publication Date: 2019-03-01
HEFEI INSTITUTES OF PHYSICAL SCIENCE - CHINESE ACAD OF SCI
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Problems solved by technology

[0005] The purpose of the present invention is to solve the defect that the two-dimensional image recognition method is difficult to accurately identify in order to solve the occlusion overlap before the Lycium fruit picking in the prior art, provide a kind of Lycium barbarum recognition and counting method based on PointNet++ network to solve the above problems

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  • A Chinese wolfberry identification counting method based on PointNet + + Network
  • A Chinese wolfberry identification counting method based on PointNet + + Network
  • A Chinese wolfberry identification counting method based on PointNet + + Network

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Embodiment Construction

[0076] In order to have a further understanding and understanding of the structural features of the present invention and the achieved effects, a detailed description will be provided in conjunction with preferred embodiments and accompanying drawings, as follows:

[0077] Such as figure 1 Shown, a kind of Lycium barbarum identification and counting method based on PointNet++ network of the present invention, comprises the following steps:

[0078] The first step is the collection and preprocessing of PointNet++ network training samples.

[0079] Obtain 18 pictures of each wolfberry tree and the corresponding context information. The context information includes time, space, temperature and phenological period information. According to the existing method, 18 pictures are used to construct a 3D model to obtain a 3D point cloud, and the context information is used as a training data.

[0080] The second step is to obtain the PointNet++ model based on PointNet++ network fusion...

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Abstract

The invention relates to a Chinese wolfberry identification counting method based on PointNet + + network, which solves the defect that the two-dimensional image identification method is difficult toaccurately identify due to the overlapping of the shielding before picking of the Chinese wolfberry fruit compared with the prior art. The invention comprises the following steps: collection and pretreatment of a PointNet + + network training sample; Obtaining PointNet + + Model Based on PointNet + + Network Fusion Context Information; acquisition and Preprocessing of Point Cloud Data to be Identified; identification and enumeration of the quantity of Lycium barbarum L. The invention integrates PointNet + + network based on context information and optimal threshold watershed segmentation algorithm based on distance transformation to realize precise segmentation and counting of Chinese wolfberry.

Description

technical field [0001] The invention relates to the technical field of image recognition, in particular to a method for recognizing and counting Chinese wolfberry based on the PointNet++ network. Background technique [0002] During the planting process of wolfberry, by accurately predicting the yield of wolfberry, it is possible to carry out targeted rectification of low-yielding areas, adjust factors such as soil, variety, or moisture content, and rationally arrange the manpower, material resources, and storage resources required for harvesting. . [0003] At present, when performing fruit target recognition and estimating yield, most of them use two-dimensional images as data input for yield measurement. However, in practical applications, due to the small size of wolfberry fruit, and the occlusion and overlapping problems of most wolfberry fruits before picking, it is difficult to guarantee the accuracy of yield measurement using the deep learning method based on two-di...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/136G06K9/62
CPCG06T7/136G06T2207/30242G06T2207/30188G06T2207/20152G06T2207/10028G06F18/23213
Inventor 贾秀芳王儒敬李伟谢成军孙丙宇黄河王雪李娇娥徐玲玲
Owner HEFEI INSTITUTES OF PHYSICAL SCIENCE - CHINESE ACAD OF SCI
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