Plant Leaf Disease Detection and Classification using Image Processing

Yin Min Oo, N. Htun
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引用次数: 84

Abstract

Myanmar is an agricultural country and then crop production is one of the major sources of earning. So, more than half of our population depends on agriculture for livelihood. Due to the factors like diseases, pest attacks and sudden change in the weather condition, the productivity of the crop decreases. Automatic detection of plant diseases is essential to automatically detect the symptoms of diseases as early as they appear on the growing stage. This paper proposed a methodology for the analysis and detection of plant leaf diseases using digital image processing techniques. The experimental results demonstrate that the proposed system can successfully detect and classify four major plant leaves diseases: Bacterial Blight and Cercospora Leaf Spot, Powdery Mildew and Rust.
基于图像处理的植物叶片病害检测与分类
缅甸是一个农业国家,农作物生产是主要的收入来源之一。因此,我国一半以上的人口以农业为生。由于疾病、害虫袭击和天气条件的突然变化等因素,作物的产量下降。植物病害自动检测是在生长阶段就自动发现病害症状的关键。提出了一种利用数字图像处理技术对植物叶片病害进行分析和检测的方法。实验结果表明,该系统能够成功地检测和分类4种主要的植物叶片病害:白叶枯病和斑叶病、白粉病和锈病。
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