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An application of image processing techniques for detection of diseases on brinjal leaves using k-means clustering method

机译:图像处理技术在k均值聚类法检测茄子叶病害中的应用

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This work presents a method for identifying plant leaf disease and an approach for careful detection of diseases. The goal of proposed work is to diagnose the disease of brinjal leaf using image processing and artificial neural techniques. The diseases on the brinjal are critical issue which makes the sharp decrease in the production of brinjal. The study of interest is the leaf rather than whole brinjal plant because about 85-95 % of diseases occurred on the brinjal leaf like, Bacterial Wilt, Cercospora Leaf Spot, Tobacco mosaic virus (TMV). The methodology to detect brinjal leaf disease in this work includes K-means clustering algorithm for segmentation and Neural-network for classification. The proposed detection model based artiifical neural networks are very effective in recognizing leaf diseases.
机译:这项工作提出了一种识别植物叶片疾病的方法和一种仔细检测疾病的方法。拟议工作的目标是使用图像处理和人工神经技术诊断茄子叶的病害。茄子上的疾病是关键问题,这使得茄子的产量急剧下降。有趣的研究是叶而不是整个茄子植物,因为大约有85%至95%的疾病发生在茄子叶子上,如细菌枯萎病,鹿角菌斑病,烟草花叶病毒(TMV)。在这项工作中检测茄子叶病的方法包括用于分割的K-means聚类算法和用于分类的神经网络。所提出的基于人工神经网络的检测模型在识别叶片疾病方面非常有效。

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