Method for detecting diseases of crop leaves

Abstract

The invention discloses a method for detecting diseases of crop leaves. The method comprises the following steps: acquiring a leaf image of a crop to be detected, uploading the leaf image to an on-line detection platform with a disease image automatic identification function and a professional diagnosis system function, performing scab image partitioning and identification on the leaf of the crop to be detected, outputting a detection result, and giving a control suggestion, wherein the scab image partitioning is as followings: converting an original image from a red, green and blue (RGB) model space to a horizontal situation index (HSI) space, respectively extracting an H component image and an I component image in the HIS space, and performing dynamic threshold value partitioning on the H component image by using a maximum between-cluster variance method to preliminarily obtain a scab region image; superimposing the I component image on the partitioning result of the H component image to eliminate misjudgment caused by a background region on the scab partitioning, thus obtaining a binary image only comprising the scab region; and performing subsequent treatment on the partitioning result by using a morphological method, and finally obtaining a complete scab image of the leaf of the crop to be detected.

Description

technical field [0001] The invention belongs to the field of agricultural modernization and relates to the diagnosis and identification of the health status of crops, in particular to a method for detecting crop leaf diseases. Background technique [0002] my country is a large agricultural country. Due to the comprehensive influence of many types of crops, large planting area, complex and diverse climatic conditions, and fragile ecological foundation, there are many types of diseases, which are widely distributed and occur frequently. Accurate and rapid disease detection is the key technology for the comprehensive control of crop diseases. Only on the premise of correctly diagnosing the disease type can we adopt timely and correct strategies and quickly take control measures. [0003] With the rapid development of computer technology and image processing technology, researchers at home and abroad have begun to apply computer vision theory to agricultural production and agri...

AI Technical Summary

Problems solved by technology

However, in the existing crop disease detection methods, the way of image acquisition is fixed, and all adopt a single definite image acquisition method, which can only be processed for specific types and quality of crop images, and some image acquisition equipment requires high cost, not widely available

In addition, due to the complexity and diversity of crop disease images, coupled with the limitations of the actual system environment and methods themselves, the speed and accuracy of detection also need to be improved

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