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Automatic recognition of plant leaves diseases based on serial combination of two SVM classifiers

机译:基于两个SVM分类器的序列组合自动识别植物叶片病害

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This paper presents a machine vision system for automatic recognition of plant leaves diseases from images. The proposed system is based on serial combination technique of two SVM classifiers. The first classifier uses the color to classify the images; it considers, at this phase, that the diseases with similar or nearest color belonging to the same class. Then, the second classifier is used to differentiate between the classes with similar color according to the shape and texture features. The tests of this study are carried out on six classes of diseases including three types of pest insects damages (Leaf miners, Thrips and Tuta absoluta) and three forms of pathogens symptoms (Early blight, Late blight and Powdery mildew). The results of the study show the advantages of the proposed method compared to the other existing methods.
机译:本文提出了一种机器视觉系统,用于从图像中自动识别植物叶片的病害。所提出的系统基于两个SVM分类器的串行组合技术。第一个分类器使用颜色对图像进行分类。它认为在这一阶段,颜色相似或最接近的疾病属于同一类别。然后,使用第二个分类器根据形状和纹理特征区分具有相似颜色的类。这项研究的测试针对六种疾病进行,包括三种害虫危害(叶农,蓟马和塔塔绝对霉菌)和三种病原体症状(早疫病,晚疫病和白粉病)。研究结果表明,与其他现有方法相比,该方法具有优势。

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