A Cucumber Disease Recognition Method Based on Cucumber Leaf Symptom Image Processing

An image processing and disease identification technology, applied in character and pattern recognition, instruments, computer parts, etc., can solve problems such as the rise of cucumber diseases

Inactive Publication Date: 2016-08-24
XIJING UNIV
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Problems solved by technology

But detecting cucumber diseases by leaf symptoms is not an easy task
The reasons are: (1) There are many kinds of cucumber diseases at present, resulting in a variety of symptoms on the diseased leaves; (2) With the promotion of new high-quality cucumber varieties and diversified planting in my country, there will be more opportunities for the occurrence of more cucumber diseases. Due to the lack of suitable conditions (such as greenhouse planting, etc.), the incidence of cucumber diseases is on the rise.
These conditions also bring challenges to the research of cucumber disease detection methods based on cucumber leaf symptoms.

Method used

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  • A Cucumber Disease Recognition Method Based on Cucumber Leaf Symptom Image Processing
  • A Cucumber Disease Recognition Method Based on Cucumber Leaf Symptom Image Processing
  • A Cucumber Disease Recognition Method Based on Cucumber Leaf Symptom Image Processing

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Embodiment Construction

[0049] The present invention will be described in detail below in conjunction with examples.

[0050] A method for identifying cucumber diseases based on image processing of cucumber leaf symptoms, including the following steps:

[0051] The first step is to segment the image of the diseased cucumber leaves: first, use the function'imread' in the Matlab software to convert all the images of the diseased cucumber leaves into a digital image matrix; then, design a 3×3 square structural element and use the closed The operation smoothes the leaf image boundary and fills in the gaps inside the leaf diseased spots, and then connects the separated parts of the leaf diseased spots together; then, the obtained diseased spot area is turned on to eliminate the noise around the diseased spot, and the leaf diseased area is obtained. Finally, the cucumber leaf diseased area image filtered by mathematical morphology is multiplied with the original cucumber leaf color image to obtain the cucumber ...

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Abstract

A cucumber disease recognition method based on cucumber leaf symptom image processing, first segment the cucumber disease leaf lesion image, then extract the image recognition features of cucumber disease leaf, then reduce the dimensionality of the feature vector, and finally identify the cucumber disease. The invention overcomes the existing methods and technologies for identifying cucumber diseases. Due to the complex image components of cucumber diseased leaves, the arrangement of diseased spots on cucumber diseased leaves is irregular, and the color is different, and the shapes and colors of leaf diseased spots of different disease types are not the same. The reason is that the recognition rate of cucumber diseases based on leaves is not high and the recognition effect is unstable. It has the advantages of fast feature extraction, high recognition rate, stable recognition effect and strong practicability.

Description

Technical field [0001] The invention relates to the technical field of the application of image processing and pattern recognition in cucumber disease recognition, in particular to a cucumber disease recognition method based on image processing of cucumber leaf symptoms. Background technique [0002] Cucumber is widely distributed in China and even in many parts of the world. It is one of the main vegetables eaten by residents of many countries and has many benefits to the human body. However, cucumber is a kind of susceptible cucumber, and there are more than ten kinds of common cucumber diseases. Accurately judging the types of cucumber diseases is the prerequisite for cucumber disease control. Traditional cucumber disease detection basically relies on the visual estimation of agricultural producers. This detection method has many shortcomings, such as strong subjectivity, slow recognition speed, high recognition intensity, high false recognition rate, poor real-time performan...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00
Inventor 张善文黄文准胡伟
Owner XIJING UNIV
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