Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Crop disease identification method based on remote sensing image

A remote sensing image and image recognition technology, applied in the field of image recognition, can solve the problems of time-consuming, labor-intensive, real-time, poor accuracy, etc., and achieve the effect of improving the accuracy and improving the early warning of crop diseases.

Inactive Publication Date: 2020-07-14
JILIN AGRICULTURAL UNIV
View PDF1 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, the traditional identification of crop diseases mainly relies on the experience accumulated by farmers in the past dynasties in the agricultural production process to make judgments, which is time-consuming and laborious, and the real-time and accuracy are poor.

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
  • Crop disease identification method based on remote sensing image
  • Crop disease identification method based on remote sensing image
  • Crop disease identification method based on remote sensing image

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0028] Such as figure 1 As shown, a method for identifying crop diseases based on remote sensing images includes the following steps:

[0029] S1. Realize the detection of crop targets in remote sensing images based on the YOLT model;

[0030] S2. Mining out the crop image area corresponding to the crop target in the remote sensing image based on the detection result, and generating the crop image;

[0031] S3. The disease image de-occlusion algorithm based on the heat map removes the crop occlusion information in the crop image; first, obtain the heat map of the crop image; the main steps are:

[0032] The first step is to calculate the thermal value information of the four vertices of the crop image, that is, the basic thermal value information;

[0033] In the second step, the bilinear interpolation operation is performed according to the basic thermal value information to obtain the thermal value information corresponding to all pixels of the crop image;

[0034] The th...

Embodiment 2

[0042] Such as figure 1 As shown, a method for identifying crop diseases based on remote sensing images includes the following steps:

[0043] S1. Realize the detection of crop targets in remote sensing images based on the YOLT model;

[0044] S2. Mining out the crop image area corresponding to the crop target in the remote sensing image based on the detection result, and generating the crop image;

[0045] S3. The disease image de-occlusion algorithm based on the heat map removes the crop occlusion information in the crop image; first, obtain the heat map of the crop image; the main steps are:

[0046] The first step is to calculate the thermal value information of the four vertices of the crop image, that is, the basic thermal value information;

[0047] In the second step, the bilinear interpolation operation is performed according to the basic thermal value information to obtain the thermal value information corresponding to all pixels of the crop image;

[0048] The th...

Embodiment 3

[0059] Such as figure 1 As shown, a method for identifying crop diseases based on remote sensing images includes the following steps:

[0060] S1. Realize the detection of crop targets in remote sensing images based on the YOLT model;

[0061] S2. Based on the detection results, dig out the crop image area corresponding to the crop target in the remote sensing image, generate a crop image, and read the geographic location parameters of each remote sensing image, and mark the geographic location parameters for each crop image in a hyperlink mode ;

[0062] S3. The disease image de-occlusion algorithm based on the heat map removes the crop occlusion information in the crop image; first, obtain the heat map of the crop image; the main steps are:

[0063] The first step is to calculate the thermal value information of the four vertices of the crop image, that is, the basic thermal value information;

[0064] In the second step, the bilinear interpolation operation is performed ...

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 discloses a crop disease identification method based on a remote sensing image. The method comprises the following steps: S1, realizing detection of a crop target in the remote sensing image based on a YOLT model; S2, digging a crop image area corresponding to the crop target in the remote sensing image based on a detection result, and generating a crop image; S3, removing crop occlusion information in the crop image based on a disease image occlusion removal algorithm of the thermodynamic diagram; S4, acquiring the saliency map of the crop image by using a saliency map detectionstrategy based on a saliency map disease image segmentation method, and performing complex background segmentation on the crop image by taking the saliency map as a mask image; and S5, realizing detection and identification of holes, spots, pest tracks and the like in the crop image based on the DSSD_Inception-V2_co model. According to the invention, rapid identification and statistical analysisof crop diseases can be realized.

Description

technical field [0001] The invention relates to the field of image recognition, in particular to a method for recognizing crop diseases based on remote sensing images. Background technique [0002] Crop disease is one of the main agricultural disasters in my country. It has the characteristics of various types, great impact and frequent outbreaks. It not only causes losses to crop production, but also poses a threat to food safety. Therefore, the diagnosis and identification of crop diseases play an important role in ensuring crop yield and preventing food safety. At the same time, realizing accurate detection of crop diseases and the determination of the degree of disease is the key to the prevention and control of crop diseases. At present, the traditional crop disease identification mainly relies on the experience accumulated by farmers in the agricultural production process to make judgments, which is time-consuming and labor-intensive, and the real-time and accuracy a...

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 Applications(China)
IPC IPC(8): G06K9/00G06K9/34G06Q50/02G06T7/194G06T7/62
CPCG06Q50/02G06T7/194G06T7/62G06T2207/10032G06T2207/30188G06V20/188G06V10/267
Inventor 曹丽英胡楠于合龙李东明马丽刘鹤
Owner JILIN AGRICULTURAL UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com