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Weed detection method and device based on crop growth characteristics

A detection method and crop technology, applied in neural learning methods, character and pattern recognition, biological neural network models, etc., can solve the problem of ignoring the differences in physiology and growth of crops and weeds, and achieve the effect of improving recognition accuracy

Pending Publication Date: 2022-07-29
北大荒信息有限公司 +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, the identification of weeds is based on the collection of image information of different types of weeds, ignoring the inherent physiological and growth differences between crops and weeds, such as plant structure (root, stem and leaf), plant height, leaf length, and leaf width. , leaf area, leaf color, leaf green content

Method used

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  • Weed detection method and device based on crop growth characteristics
  • Weed detection method and device based on crop growth characteristics

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Embodiment 1

[0050] figure 1 It is a flowchart of a weed detection method based on crop growth characteristics. In the embodiment of the present invention, a weed detection method based on crop growth characteristics includes:

[0051] Obtain the images of each plant in the field and the growth period of the crop, and obtain the image library to be inspected;

[0052] Inputting the image library to be inspected into the trained first classifier, performing content recognition on the image, and obtaining a weed image according to the content recognition result;

[0053] Upload the weed image to the detection image and manually mark it, and classify and store the images in the first sample library and the third sample library according to the manual marking results;

[0054] Input the weed image into the trained second classifier, perform feature recognition on the image, remove the crop image in the weed image according to the feature recognition result, and report the detection result; the ...

Embodiment 2

[0096] In the embodiment of the present invention, a weed detection device based on crop growth characteristics is provided, and the device includes:

[0097] The image library generation module is used to obtain the images of each plant in the field and the growth period of the crops, and obtain the image library to be inspected;

[0098] a content recognition module, configured to input the image library to be inspected into the trained first classifier, perform content recognition on the image, and obtain a weed image according to the content recognition result;

[0099] The manual marking module is used to upload the weed image to the detection image and manually mark it, and classify and store the images in the first sample library and the third sample library according to the manual marking result;

[0100] The feature recognition module is used to input the weed image into the trained second classifier, perform feature recognition on the image, remove the crop image in ...

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Abstract

The invention relates to the technical field of weed detection, and particularly discloses a weed detection method and device based on crop growth characteristics, and the method comprises the steps: obtaining images of all plants in a field and the growth period of crops, and obtaining a to-be-detected image library; inputting the to-be-detected image library into a trained first classifier, carrying out content identification on the images, and obtaining a weed image according to a content identification result; uploading the weed image to a detection image, manually marking the detection image, and storing the image in a first sample library and a third sample library in a classified manner according to a manual marking result; and inputting the weed image into a trained second classifier, performing feature recognition on the image, removing a crop image in the weed image according to a feature recognition result, and reporting a detection result. According to the method, growth characteristics of crops in each growth period are learned through a neural network algorithm, weeds are detected through a reverse weed detection and recognition method for recognizing non-crops, and the recognition accuracy is greatly improved.

Description

technical field [0001] The invention relates to the technical field of weed detection, in particular to a weed detection method and device based on crop growth characteristics. Background technique [0002] In my country's agricultural planting management system, how to effectively identify weeds during the crop growth period is a very important agricultural management link. Identify weeds quickly, efficiently and accurately, and effectively predict the spread of weeds to form the distribution of weeds. It will lay a solid foundation for the subsequent precise implementation of pesticide weeding and pesticide dosage control, so as to avoid the waste of pesticides and excessive residues of soil pesticides, and then meet the standard requirements of green agriculture proposed by the state. [0003] At present, whether it is dry field crops such as corn, wheat or paddy field crops such as rice, there are many kinds of weeds in the field, such as crabgrass, sedge, barnyardgrass, ...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06V10/764G06V10/82G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06F18/24Y02A40/10
Inventor 柯善风吴国龙
Owner 北大荒信息有限公司
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