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Tibetan highland barley leaf lesion identification method

A kind of identification method, highland barley technology

Inactive Publication Date: 2019-10-29
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] At present, net spot disease of highland barley is in the stage of visual judgment by experienced growers. Inexperienced growers may make mistakes in judgment, resulting in wrong treatment methods, delaying the condition of highland barley, and affecting production.

Method used

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  • Tibetan highland barley leaf lesion identification method
  • Tibetan highland barley leaf lesion identification method
  • Tibetan highland barley leaf lesion identification method

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Embodiment Construction

[0084] A method for identifying net spot disease of highland barley, the method comprising:

[0085] Step 1: Obtain normal image samples of highland barley and image samples of net spot disease of highland barley;

[0086] Step 2: The image obtained in step 1 is denoised by means of filtering in each channel of RGB;

[0087] The mean filtering method in the step 2 is:

[0088]

[0089] Where: S xy Indicates that the center point is at (x, y), and the size of the filter window is m×n; h(s, t) represents the original image, and d(x, y) represents the image obtained after mean filtering.

[0090] Perform denoising preprocessing on the input image, and use mean filtering to remove uniform noise and Gaussian noise. Although it will bring some blur to the image, the feature of stripe rust is more obvious. Mean filtering There is no significant impact on feature expression while denoising. The arithmetic mean filter simply calculates the mean value of each RGB channel in the w...

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Abstract

The invention discloses a Tibetan highland barley leaf lesion identification method, and belongs to the field of image processing. The method comprises the following steps of converting a preprocessedimage into an HSV color space; performing threshold processing on the image in an HSV color gamut; wherein a color is light brown and dark brown, and the color in the middle is dark brown; remainingcolor setting to white, merging with an original image, setting H and S classification grades and change ranges; and counting H and S component data in the image according to a setting result, creating a histogram, normalizing the histogram height of the image, training a KNN classifier by taking the normalized histogram height and the corresponding abscissa as image features and labels, performing the same processing on an image sample for testing, and inputting the image sample into the KNN classifier to obtain a prediction result. According to the highland barley lesion identification method, images of normal highland barley leaves and lesion highland barley leaves can be well classified by filtering and denoising the images, extracting and normalizing color space features and classifying the images by a support vector machine, and the highland barley lesion identification efficiency and accuracy are improved.

Description

technical field [0001] The invention belongs to the field of image processing, and in particular relates to a method for recognizing barley leaf lesions. Background technique [0002] Net spot disease is an important disease of highland barley. In recent years, due to climate, soil and other factors, the local area where the disease has occurred has caused serious damage to the susceptible varieties. When it occurs seriously, it will cause the leaves to die and the grains to fail. Mainly damages leaves, but also infects leaf sheaths and ears. The yield of diseased plants is reduced by 20% to 30%, and the yield of high-susceptibility varieties can be reduced by more than 50%. The quality of diseased wheat is also reduced. Diseased leaves have yellowish-brown to light-brown patches with unclear boundaries between disease and health, and there are criss-crossed thin lines inside, which are dark brown. When there are many lesions, they will form dark brown stripes. The variety...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06K9/40G06K9/46
CPCG06V10/30G06V10/56G06F18/2411
Inventor 唐樟春金涛薛琦刘杰夏艳君余明东何达魏晨竹
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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