Method for detecting diseases of crop leaves

A detection method and crop technology, applied in the direction of measuring devices, material analysis through optical means, instruments, etc., can solve the problems of detection speed and accuracy to be improved, single image acquisition method, lack of practicability, etc., to achieve increase The effect of farmers' income, promotion of economic growth, and large market potential

Inactive Publication Date: 2012-10-31
SHAANXI UNIV OF SCI & TECH
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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 equipme

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  • Method for detecting diseases of crop leaves
  • Method for detecting diseases of crop leaves

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Embodiment Construction

[0028] The present invention will be described in further detail below in conjunction with the accompanying drawings.

[0029] Such as figure 1 As shown, the overall process of the disease detection process is as follows:

[0030] 1. The user directly uses mobile phones, digital cameras and other equipment to take pictures and save the leaves of the crops to be detected in the field, so as to obtain the original pictures.

[0031] 2. The user uploads the original picture to be detected to the online detection platform for crop leaf diseases through wireless transmission through the mobile phone network or online upload.

[0032] 3. The above-mentioned network online detection platform uses a visual programming language to implement a window operating platform system, which meets the requirements of friendly interface, easy operation, and convenience for non-professionals. It also has the functions of an automatic lesion image recognition system and an expert diagnosis system....

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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...

Claims

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Application Information

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IPC IPC(8): G01N21/84
Inventor 党宏社张芳田丽娜张新院姚勇郭楚佳
Owner SHAANXI UNIV OF SCI & TECH
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