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A novel approach to classify and detect bean diseases based on image processing

机译:基于图像处理的豆类疾病分类检测新方法

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The early detection of plant diseases is one of the main reasons that can reduce the world crop losses. It requires a tremendous amount of effort, money, and time. Therefore, the algorithms used in image processing make it possible to detect plant leaf diseases automatically. This paper focuses on detecting two types of bean leaf diseases including bacterial brown spot and powdery mildew. The detecting process involves acquisition, preprocessing, segmentation, feature extraction, and classification. The training and testing images are taken from a public database. The developed methodology can successfully detect the two types of plant leaf diseases with an accuracy of 100%.
机译:早期发现植物病害是可以减少世界作物损失的主要原因之一。它需要大量的精力,金钱和时间。因此,图像处理中使用的算法使自动检测植物叶片病害成为可能。本文着重于检测两种类型的豆叶疾病,包括细菌性褐斑病和白粉病。检测过程涉及采集,预处理,分割,特征提取和分类。训练和测试图像取自公共数据库。所开发的方法可以成功地检测出两种类型的植物叶病,准确度为100%。

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