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Leaf disease detection and grading using computer vision technology fuzzy logic

机译:使用计算机视觉技术和模糊逻辑对叶片疾病进行检测和分级

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In Agriculture, leaf diseases have grown to be a dilemma as it can cause significant diminution in both quality and quantity of agricultural yields. Thus, automated recognition of diseases on leaves plays a crucial role in agriculture sector. This paper imparts a simple and computationally proficient method used for leaf disease identification and grading using digital image processing and machine vision technology. The proposed system is divided into two phases, in first phase the plant is recognized on the basis of the features of leaf, it includes pre-processing of leaf images, and feature extraction followed by Artificial Neural Network based training and classification for recognition of leaf. In second phase the disease present in the leaf is classified, this process includes K-Means based segmentation of defected area, feature extraction of defected portion and the ANN based classification of disease. Then the disease grading is done on the basis of the amount of disease present in the leaf.
机译:在农业中,叶病已成为两难选择,因为它可能导致农业产量的质量和数量显着下降。因此,自动识别叶子上的疾病在农业领域起着至关重要的作用。本文介绍了一种使用数字图像处理和机器视觉技术进行叶病鉴定和分级的简单且计算能力强的方法。所提出的系统分为两个阶段,在第一阶段,根据叶片的特征识别植物,包括对叶片图像进行预处理和特征提取,然后进行基于人工神经网络的训练和分类以识别叶片。在第二阶段,对叶片中存在的疾病进行分类,该过程包括基于K均值的缺陷区域分割,缺陷部分的特征提取以及基于ANN的疾病分类。然后根据叶片中存在的疾病量对疾病进行分级。

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