A method and system for detecting crop diseases and insect pests based on computer vision

A computer vision, pest and disease technology, applied in computer parts, computing, biological neural network models, etc., can solve the problems of low actual recognition rate, less training data, inconvenient acquisition of hyperspectral data, etc., to improve detection efficiency, improve Crop yield, effect of reducing planting risk

Active Publication Date: 2022-07-29
SINOCHEM AGRI HLDG
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] Computer vision disease, insect pest and weed monitoring technology is still in the early stage of development. It has not been used for a long time in agricultural application scenarios, and the training data is small and the classification is not balanced, resulting in a high recognition rate of the model self-test, but in actual application scenarios, the actual recognition rate is low.
Traditional hyperspectral pest identification requires the use of hyperspectral data, which is inconvenient to obtain and not very applicable
The current identification of diseases and insect pests is mostly based on the classification of pictures. It is impossible to accurately determine the location of disease and insect pests, and it is impossible to detect multiple diseases on the same plant at the same time.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A method and system for detecting crop diseases and insect pests based on computer vision
  • A method and system for detecting crop diseases and insect pests based on computer vision
  • A method and system for detecting crop diseases and insect pests based on computer vision

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0054] figure 1 It is a flow chart of crop pest detection method based on computer vision. like figure 1 As shown, the present invention provides a method for detecting crop diseases and insect pests based on computer vision, the method comprises the following steps:

[0055] S1: Obtain the picture of the crop, input the picture of the crop into the pre-classification model, identify the picture of the crop that is affected by diseases and insect pests, and use it as the target picture to be detected;

[0056] S2: Input the target image to be detected into a detection model for detection to obtain a target detection result;

[0057] S3: Output the target detection result, where the target detection result includes the type of pests and diseases and the locations where the pests occur in the target picture.

[0058] Preferably, the pre-classification model adopts a residual neural network model, which combines the IncoptionNet network structure with the ResNet residual block...

Embodiment 2

[0087] figure 2 It is a schematic diagram of a crop pest detection system based on computer vision. like figure 2 As shown, the present invention also provides a computer vision-based crop pest detection system, the system comprising:

[0088] The classification module is used to obtain the picture of the crop, input the picture of the crop into the pre-classification model, identify the picture of the crop with disease and insect damage, and use it as the target picture to be detected;

[0089] a detection module, configured to input the target image to be detected into a detection model for detection to obtain a target detection result;

[0090] The output module is configured to output the target detection result, where the target detection result includes the type of pests and diseases and the location where the pests occur in the target picture.

[0091] Preferably, the pre-classification model adopts a residual neural network model, which combines the IncoptionNet n...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to a method and system for detecting crop diseases and insect pests based on computer vision, and belongs to the technical field of computer applications. The method includes: S1: obtaining a picture of a crop, inputting the picture of the crop into a pre-classification model, identifying a picture of a crop that has suffered from diseases and insect pests, and using it as a target picture to be detected; S2: inputting the target picture to be detected The detection model performs detection to obtain a target detection result; S3: Output the target detection result, where the target detection result includes the type of pests and diseases and the locations where the pests occur in the target picture. The invention effectively improves the detection efficiency of pests and diseases, shortens the discovery time of pests and diseases, and reduces the planting risk of growers.

Description

technical field [0001] The invention belongs to the technical field of computer applications, in particular to a method and system for detecting crop diseases and insect pests based on computer vision. Background technique [0002] Computer vision refers to the machine vision that uses cameras and computers instead of human eyes to identify, track and measure targets, and further image processing, using computer processing to become images that are more suitable for human eyes to observe or transmit to instruments for detection. ; Computer vision is widely used in various fields, such as manufacturing, inspection, document analysis, medical diagnosis, and an integral part of various intelligent / autonomous systems in the military and other fields. [0003] The traditional detection of crop diseases and insect pests is time-consuming and complicated, and is usually limited to offline analysis in the laboratory. In 2016, Zhejiang University used hyperspectral imaging technolog...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): G06V20/52G06V10/774G06V10/764G06V10/82G06K9/62G06N3/04
CPCG06N3/048G06N3/045G06F18/24G06F18/214
Inventor 牛太阳
Owner SINOCHEM AGRI HLDG
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap