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Leaf Recognition and Disease Detection using Content based Image Retrieval

机译:基于内容的图像检索的叶识别和疾病检测

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The agricultural domain in past few decades has seen a decrease in its productivity. The main cause for this was found to be an increase in plant diseases. Having diseases in plants is quite common, but due to improper care there have been serious effects on plants. But we cannot keep inspecting each and every plant present in thousands. Hence, in this work an approach is developed which provides faster and more accurate results of the detected plant leaves and its corresponding diseases. The proposed work approach uses various image processing techniques for recognising the plant leaf type and detecting disease. The system uses two different classification methods namely, Support Vector Machine (SVM) and K-Nearest Neighbours (KNN) and their performances are compared.
机译:过去几十年的农业领域已达到生产力下降。 主要原因是植物疾病的增加。 在植物中患有疾病是非常常见的,但由于护理不当,对植物产生了严重影响。 但我们不能继续检查每一批现有数千的植物。 因此,在这项工作中,开发了一种方法,该方法提供了检测到的植物叶片及其相应疾病的更快和更准确的结果。 所提出的工作方法使用各种图像处理技术来识别植物叶片类型和检测疾病。 该系统使用两种不同的分类方法即,支持向量机(SVM)和K最近邻居(KNN)及其性能。

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