A method of leaf disease identification based on machine learning algorithm

Abstract

The invention discloses a leaf disease identification method based on a machine learning algorithm, belonging to the technical field of image processing. The invention firstly performs preprocessing operations such as grayscale transformation, image enhancement and denoising on the collected leaf sample image; Then the preprocessed image is segmented by adaptive threshold algorithm to represent the texture information of the sample image effectively. The RGB color space is selected to extract the color features of the sample image, and the texture features of the segmented image are extractedaccording to the gray level co-occurrence matrix. Finally, support vector machine model is selected to classify and recognize the sample images by cross-validation algorithm. Firstly, the main parameters of SVM model are optimized by grid optimization method, and then the parameters with the best recognition accuracy are selected to establish SVM classification and recognition model. The inventioncan enable the computer to automatically identify the diseases and pests of the leaves through training, greatly reducing the space and time overhead, and improving the identification accuracy, and has the characteristics of fast, accurate and strong robustness.

Description

technical field [0001] The invention relates to the technical field of computer information image processing, and more specifically, to a method for identifying leaf diseases based on machine learning algorithms. Background technique [0002] With the continuous rapid development of my country's economy and the rapid growth of population, my country's agriculture has also developed accordingly. Fruit has become a must-have food for ordinary people. Due to the great demand for fruit, its planting area is also expanding. With the increase of fruit production area, its disease problem has gradually attracted the attention and attention of experts. Correctly and efficiently identifying the disease type of fruit trees can make fruit trees get timely treatment, thereby reducing unnecessary losses and increasing the output of orchards. [0003] At present, image processing technology is developing rapidly, and its application in life and production is gradually becoming popular. T...

AI Technical Summary

Problems solved by technology

However, the disadvantage of this application is that it is impossible to distinguish between different pests and diseases

However, the spectral images used in this application need to be obtained by professionals and the equipment is expensive, which is not conducive to popularization and application

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