Winter jujube disease identification method based on deep convolutional neural network and disease image

Abstract

The invention relates to a winter jujube disease identification method based on a deep convolutional neural network and a disease image. The method includes the following steps that: an original winter jujube diseased fruit RGB color image collected by an Internet of Things is converted into a YUV color model, and preprocessing is performed; the a rectangular region of interest of disease spots which contains a disease image is extracted, the rectangular region of interest is segmented through using a K-means clustering algorithm, so that a YUV color disease spot image can be obtained; and a three-channel layered convolutional neural network model is constructed and is trained by using training data, and a jujube disease image to be recognized is inputted into the trained model so as to be subjected to disease category identification. The method of the invention can be applied to an Internet of Things-based greenhouse winter jujube disease monitoring system and can obtain accurate disease identification results.

Description

Technical field [0001] The invention relates to the technical field of fruit disease image processing and machine learning, in particular to a winter jujube disease recognition method based on a deep convolutional neural network and disease images. Background technique [0002] Since winter jujube is grown in a large shed, the greenhouse environment in the large shed provides suitable conditions for the occurrence of winter jujube diseases, which makes the types of diseases occur frequently. The main diseases include jujube rust, jujube anthracnose, jujube fruit shrinking, and jujube scorching leaf disease. The disease of winter jujube seriously affected the yield and quality of winter jujube. There are many ways to prevent and control winter jujube diseases. Liu Tonghai and others designed a WebGIS-based winter jujube disease information service platform [Liu Tonghai, Gao Meixiu, Wang Liang. Research on the construction of winter jujube disease and pest information service pla...

AI Technical Summary

Problems solved by technology

The Internet of Things can collect winter jujube disease images in real time, and deep learning can automatically learn representative features from the collected massive and complex disease images. These features can be used to quickly and accurately identify disease types, but so far no combination of the above technologies has been found Fusion identification method of winter jujube disease

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