Method for grading wheat scab disease

Abstract

The invention particularly relates to a method for grade wheat scab disease, which comprises that follow steps: (A) acquiring an original image; B) carrying out grayscale processing, binarization processing, and opening and closing operation on that original image in turn, and obtaining a binary image; (c) combining that original image and the binary image; (D) Convertting to Lab color space, using IABC-K-PCNN method to process the a-channel gray scale image to obtain binary single-spike scab lesion pattern. (e) calculating a single ear area S1 and a lesion area S2, and then calculating a ratio R of that single ear area S1 and the lesion area S2; (F) according to the national standard, the ratio R, grading the disease of the single ear and outputting the disease grade; A grading device isalso disclosed. The disease grade grading method provided by the invention is tested by a large number of samples and is not destructive in sampling in field investigation of wheat scab, and has the advantages of reliable grading accuracy and high popularization value.

Description

technical field [0001] The invention relates to the technical field of wheat scab diagnosis, in particular to a method and device for grading wheat scab disease. Background technique [0002] As a traditional agricultural country, wheat occupies a very important position in my country's food security. As one of the main diseases of wheat, head blight is particularly serious in the Jianghuai River Basin in my country. Due to the inability to accurately judge the severity of the disease, it often leads to excessive application of pesticides, which causes great harm to the agricultural ecological environment and seriously affects the national grain. Safety and food safety, therefore, it is particularly important to study wheat scab disease classification methods and diagnostic devices. [0003] At present, the diagnosis of wheat head blight mostly adopts artificial visual judgment, spectral diagnosis, conventional image processing and other methods. These methods have some shor...

AI Technical Summary

Problems solved by technology

As one of the main diseases of wheat, head blight is particularly serious in the Jianghuai River Basin in my country. Due to the inability to accurately judge the severity of the disease, it often leads to excessive application of pesticides, which causes great harm to the agricultural ecological environment and seriously affects the national grain. Safety and food safety, therefore, it is particularly important to study wheat scab disease classification methods and diagnostic devices

[0003] At present, the diagnosis of wheat head blight mostly adopts artificial visual judgment, spectral diagnosis, conventional image processing and other methods. These methods have some shortcomings: artificial visual judgment is greatly affected by human subjectivity; The requirements are relatively high, which is not suitable for ordinary plant protection personnel or farmers; conventional image processing techniques for diagnosing wheat head blight are few and most of them are traditional methods, and most of them are in the theoretical stage and have not been applied in the field

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