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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的叶疾病检测和分级

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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,叶片疾病已经生长为困境,因为它可以在农业产量的质量和数量中造成显着减少。因此,自动识别叶子上的疾病在农业部门发挥着至关重要的作用。本文赋予了使用数字图像处理和机器视觉技术的叶疾病识别和分级的简单和计算熟练的方法。所提出的系统分为两个阶段,在第一阶段的基础上识别出叶子的特征,它包括叶片图像的预处理,以及特征提取,然后是人工神经网络的基于人工网络的训练和分类识别叶子。在第二阶段,叶片中存在的疾病被分类,该方法包括基于K-Means的缺陷区域的分段,特征提取部分和基于ANN的疾病分类。然后根据叶中存在的疾病量来完成疾病分级。

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