Leaf disease spot identification method and device

A recognition method and lesion technology, applied in the direction of character and pattern recognition, instruments, computer parts, etc., can solve problems that are not general, and achieve the effect of accurate recognition, fast and efficient recognition

Inactive Publication Date: 2011-10-12
CHINA AGRI UNIV
View PDF2 Cites 22 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The above research belongs to the treatment of special circumstances under specific circumstances, and is not general

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
  • Leaf disease spot identification method and device
  • Leaf disease spot identification method and device
  • Leaf disease spot identification method and device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0046] The present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.

[0047] figure 1 It is a flow chart of image processing and recognition by the leaf disease spot recognition method according to the embodiment of the present invention. In this embodiment, tomato infected with late blight and complex background is taken as an example to illustrate the processing identification process of the present invention, wherein the obtained tomato leaf image size infected with late blight and complex background is M×N. Image processing and identification includes the following steps:

[0048] S1: First analyze the distribution characteristics of the R component, G component and B component of the overall image in the RGB color space, and simplify the complex background. The steps described to simplify complex backgrounds are as follows figure 2 shown, including:

[0049] S11: Analyze the fluctuation characteristics of the ...

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 leaf disease spot identification method and a leaf disease spot identification device. The leaf disease spot identification method comprises the following steps of: acquiring an image which contains leaf disease spot information under a complex background; analyzing the color characteristic of the overall image and simplifying the background; extracting the intramembranous areas of a plurality of disease spot areas and a background area in a certain color channel component, extracting the grain characteristics of each intramembranous area, and forming candidate characteristic vectors by using the extracted grain characteristics and color characteristic components in different areas together; optimizing the weight values of the candidate characteristic vectors; selecting the characteristic dimensions of the optimized characteristic vectors; and clustering optimized characteristic spaces. The leaf disease spot identification device comprises an image acquisition unit, an image processing and identification unit and a display unit. By the leaf disease spot identification method and the leaf disease spot identification device, parts outside disease spots in the image can be more precisely removed, and an optimal identification effect can be achieved.

Description

technical field [0001] The invention relates to the technical field of vegetable leaf disease spot identification, in particular to a method and device for identifying leaf disease spot. Background technique [0002] During the production of greenhouse vegetables, they are often affected by various adverse environmental organisms and abiotics, which lead to diseases and affect the yield and quality of vegetables. Traditional disease diagnosis methods mainly rely on professionals to carry out pathogen identification and infectivity determination in the laboratory, or rely on manual visual inspection to obtain disease information. The disadvantages of the former are slow speed, high cost, and poor real-time performance; the disadvantages of the latter are high labor intensity, low efficiency, and strong subjectivity, so the diagnosis results are often biased. In the study of intelligent prevention and control of diseases, image processing technology, as an intelligent means, ...

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): G06K9/62G06K9/36
Inventor 刘刚冯娟王圣伟任雯
Owner CHINA AGRI UNIV
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