基于MATLAB的黄瓜叶片病害等级识别系统设计

Identification System Design of Cucumber Leaf Disease Grade Based on MATLAB

为解决作物病害图像识别准确率低的问题,本研究以黄瓜叶片病害图像为研究对象,首先建立SVM模型,利用数据集训练取得模型并本地化,然后基于MATLAB平台搭建了黄瓜叶片病害等级识别系统。结果表明,通过输入图片,系统可自动识别黄瓜叶片病害等级并输出,平均预测准确率为91.25%。本研究可为农作物病害识别技术的发展提供参考。

In order to solve the problem of low accuracy in crop disease image recognition,this study took cucumber leaf disease image as the research object.Firstly,SVM model was established,the model was trained and localized by the dataset.Then,the identification system of cucumber leaf disease grade was built based on MATLAB platform.The results showed that by inputting images,the system could automatically identify the cucumber leaf disease grade and output it,with an average prediction accuracy of 91.25%.This study can provide reference for the development of crop disease identification technology.