Method for distinguishing male and female cotton bollworm adults based on computer vision technology

A technology of computer vision and discriminant methods, which is applied in computer parts, calculation, character and pattern recognition, etc., can solve the problems of heavy workload, prone to human errors, high time and manpower requirements of manual recognition methods, and achieve high computing speed and recognition accuracy, accurate and efficient extraction, and fast classification

Inactive Publication Date: 2018-12-18
NORTH CHINA UNIV OF WATER RESOURCES & ELECTRIC POWER
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Problems solved by technology

[0003] At present, the methods used to distinguish the sex of insects at home and abroad mainly include artificial identification method, biological information discrimination method, near-infrared spectral analysis method, image recognition method, etc. The requirements are too high, human errors are prone to occur, and inaccurate or even wrong information is provided for control measures. The bioinfo

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  • Method for distinguishing male and female cotton bollworm adults based on computer vision technology
  • Method for distinguishing male and female cotton bollworm adults based on computer vision technology
  • Method for distinguishing male and female cotton bollworm adults based on computer vision technology

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Embodiment Construction

[0052] The invention discloses a method for discriminating male and female adults of cotton bollworm based on computer vision technology, comprising the following steps: A, training and establishing a support vector machine classifier model in a support vector machine SVM: specifically comprising the following steps:

[0053] a1: Establish a training set: select a number of male and female adult cotton bollworms as training samples, define females as negative samples, and males as positive samples, and collect color images of each training sample to form a training set;

[0054] a2: Image preprocessing: perform image preprocessing on the color image of each training sample in the training set;

[0055] a3: Image feature extraction: feature data extraction is performed on the preprocessed training sample color image, and the extracted feature data includes color moment features, texture features and shape invariant moment features;

[0056] a4: Dimensionality reduction optimiza...

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Abstract

The invention discloses a method for distinguishing female and male adults of cotton bollworm based on computer vision technology, after pre-processing the collected images of cotton bollworm of different sexes, the images with feet and antennae removed are obtained, and the color, shape and texture of the images are extracted respectively. The simulated annealing algorithm is used to optimize thedimensionality reduction process. The obtained feature data is trained and tested by the support vector machine classifier, and finally the automatic classification and recognition are realized. Theinvention has the advantages of simple operation, strong robustness and high identification accuracy, and has ideal time performance, and can remarkably improve the identification efficiency of insectsex classification.

Description

technical field [0001] The invention relates to the technical field of agricultural and forestry insect pest control, in particular to a method for discriminating male and female adults of cotton bollworm based on computer vision technology. Background technique [0002] Cotton bollworm is found in all climatic zones of the world. It hosts more than 200 species of more than 30 families. It likes to eat cotton, corn and other crops. It is one of the world's major pests. my country's total cotton output ranks first in the world, and the loss caused by cotton bollworms reaches 15%-20% every year, and some areas with serious losses are as high as more than 50%. There was only a major pest outbreak in the cotton area of ​​North China in 1992. According to estimates, its direct economic The loss was as high as 10 billion yuan. Although transgenic Bt cotton has gone through more than 20 years of research on insect resistance and large-scale planting applications, it has saved huge ...

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Application Information

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IPC IPC(8): G06K9/62G06K9/36
CPCG06V10/20G06F18/213G06F18/2411G06F18/214
Inventor 张红涛胡玉霞谭联刘新宇顾波胡昊张晓东刘迦南许帅涛裴震宇常艳
Owner NORTH CHINA UNIV OF WATER RESOURCES & ELECTRIC POWER
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