Greenhouse Chinese cabbage pest type detection method

A detection method and cabbage technology, applied in the field of pattern recognition, can solve the problem of low accuracy rate, and achieve the effects of improving the accuracy rate, protecting income, and improving the recognition effect

Pending Publication Date: 2022-05-31
吴凡
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The object of the present invention is to provide a method for detecting pest types of cabbage in greenhouses, to solve the problem of low accuracy of pest type detection and improve the accuracy of pest type detection

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
  • Greenhouse Chinese cabbage pest type detection method
  • Greenhouse Chinese cabbage pest type detection method
  • Greenhouse Chinese cabbage pest type detection method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0083] Such as Figure 4 As shown, the present embodiment provides a method for detecting pest types of cabbage in greenhouses, comprising the following steps:

[0084] Step 1, collecting images of cabbage leaves in greenhouses;

[0085] The images include images of normal cabbage leaves in greenhouses and images of cabbage leaves in greenhouses with pests. The images of cabbage leaves in pests include four kinds of pest images: aphids, snails, cabbage worms, and diamondback moths. There are 20 images of cabbage leaves in normal greenhouses, and 20 images of each of the four pests of aphids, snails, cabbage worms and diamondback moths.

[0086] Step 2, preprocessing the collected images;

[0087] The leaves of greenhouse cabbage infested by insects are quite different from normal greenhouse cabbage leaves in color, texture, and shape, and the existence of the background will inevitably affect image processing. The present invention adopts denoising, image enhancement, image ...

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 the field of mode recognition, in particular to a greenhouse Chinese cabbage pest type detection method. The problem that the accuracy of pest type detection is not high is solved. The method comprises the following steps: step 1, collecting images of leaves of greenhouse Chinese cabbages; step 2, preprocessing the acquired image; step 3, confirming features to be extracted, and performing feature extraction; 4, classifying the three extracted features by adopting a support vector machine; and step 5, performing weighted decision voting on classification results of the three features to obtain a final detection result of the insect pest types of the greenhouse Chinese cabbages. By extracting the color features, the texture features and the shape features of the greenhouse Chinese cabbage leaves, the description of the features of the greenhouse Chinese cabbage leaves is more sufficient; sVM classification is carried out on each feature, different weights are given to output results of the classifiers by utilizing complementarity among the multiple classifiers, a final classification result is obtained, certain robustness is achieved, and the recognition effect is effectively improved.

Description

technical field [0001] The invention relates to the field of pattern recognition, in particular to a method for detecting pest types of cabbage in greenhouses. Background technique [0002] The traditional detection tasks of cabbage pests in greenhouses are mostly judged according to the professional experience. The detection efficiency is low, it takes a long time, and it is easily affected by the subjective influence of the detection personnel. At the same time, it requires high professional quality. Once the judgment is wrong, it may bring huge economic losses to farmers. The detection of cabbage pest types in greenhouses should borrow the development achievements of computer vision technology, and use more efficient processing methods to improve the work efficiency of greenhouse cabbage pest type detection. The study found that different types of cabbage pests in greenhouses lead to different shapes and colors of lesion areas on cabbage leaves. Moreover, the texture cha...

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): G06V10/764G06V10/56G06V10/50G06V10/30G06V10/26G06K9/62G06V10/54
CPCG06F18/2411Y02A40/25
Inventor 吴凡
Owner 吴凡
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