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Crop growth detection method and system based on 5G transmission

A technology for crop growth and detection methods, applied in the field of agricultural machine vision, can solve problems such as poor timeliness and slow data processing, and achieve the effects of improving timeliness, improving timeliness, and reducing computational pressure.

Active Publication Date: 2021-08-13
SOUTH CHINA AGRI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Since hyperspectral imaging technology obtains more information data, the amount of data is dozens or even hundreds of times that of traditional imaging technology. When using traditional hyperspectral imaging technology to detect crops, the huge amount of data poses a huge burden on the computer. Calculation pressure, resulting in slow data processing and poor timeliness

Method used

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  • Crop growth detection method and system based on 5G transmission
  • Crop growth detection method and system based on 5G transmission
  • Crop growth detection method and system based on 5G transmission

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Experimental program
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Embodiment 1

[0061] In view of the above problems, the embodiment of the present application provides a crop growth detection method based on 5G transmission, which can reduce the amount of data to be processed and improve the data processing speed of crop growth detection.

[0062] The technical solutions of the embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0063] figure 1 It is a schematic flowchart of a method for detecting crop growth based on 5G transmission shown in the embodiment of the present application.

[0064] see figure 1 , the crop growth detection method based on 5G transmission, comprising:

[0065] 101. Collect hyperspectral images of crops;

[0066] In the embodiment of this application, a hyperspectral image of crops is collected by an intelligent hyperspectral camera. The intelligent hyperspectral camera is equipped with a crop identification model and a characteristic band database. Through the ...

Embodiment 2

[0086] The embodiment of the present application designs step 102 in the first embodiment above.

[0087] figure 2 It is a schematic flowchart of the crop variety type identification method shown in the embodiment of the present application.

[0088] See figure 2 , the identification method of described crop variety type, comprising:

[0089] 201. Using the image local center of gravity algorithm to segment the hyperspectral image to obtain a single crop image;

[0090] In the embodiment of the present application, the hyperspectral images include crop images collected under light in the 450nm, 550nm and 650nm bands.

[0091] In the embodiment of this application, the contour of the image is extracted by using the FindContour function in OpenCV, and then the centroid of the contour is obtained by using the first-order moment of the image to locate, and the hyperspectral image is segmented by combining the image contour and the contour centroid to obtain a single crop ima...

Embodiment 3

[0103] According to the acquisition process of characteristic band types described in the first embodiment above, before step 103, it is necessary to collect characteristic band types of different crops to establish a characteristic band database. The embodiment of the present application designs the establishment of the characteristic band database.

[0104] image 3 It is a schematic diagram of the establishment process of the characteristic band database shown in the embodiment of the present application.

[0105] see image 3 , the establishment process of the characteristic band database, including:

[0106] 301. Collect the spectral image of the crop;

[0107] In the embodiment of the present application, the spectral image of the crop is used as a sample for establishing the characteristic band database, which can be processed by standard normal variable transformation to reduce the influence of uneven particle size and non-specific scattering on the particle surface...

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Abstract

The invention relates to a crop growth detection method and system based on 5G transmission. The method comprises the steps of acquiring a hyperspectral image of a crop and identifying the variety type of the crop by using a crop identification model; finding out the type of the characteristic wave band according to the variety type; processing the hyperspectral image according to the type of the characteristic wave band to obtain a characteristic image under the characteristic wave band; and analyzing according to the characteristic image to obtain growth condition information of the crop. In addition, the system comprises an intelligent hyperspectral camera and a cloud server, and image acquisition and image preprocessing can be realized through the intelligent hyperspectral camera. According to the scheme provided by the invention, the data volume to be processed can be reduced on the premise of ensuring the data reliability, so that the calculation pressure of the cloud server is reduced, and the data transmission and processing speed is improved.

Description

technical field [0001] This application relates to the technical field of agricultural machine vision, in particular to a crop growth detection method and system based on 5G transmission. Background technique [0002] Facility horticulture is a highly cross-integrated industry of biological high-tech, environmental control technology and greenhouse engineering technology. It refers to a modern agricultural production method that uses engineering technology to efficiently produce crops under a relatively controllable environment. Intensive industries, characterized by high-tech content, high input, high output, high efficiency, and ease of intensive production, are one of the important symbols of the level of agricultural modernization and an important part of modern agriculture. With the wide application of information technology in the field of agriculture, the information volume and processing requirements of crop growth status information have far exceeded the traditional...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/27G06K9/62G06N20/10G06T7/00G06T7/11G06T7/13G08C17/02
CPCG01N21/25G06T7/0002G06T7/11G06T7/13G06N20/10G08C17/02G06T2207/10036G06T2207/20021G06T2207/30188G06F18/214Y02A40/10
Inventor 赵静刘禹龙拥兵刘厚诚龙腾
Owner SOUTH CHINA AGRI UNIV