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Review of image processing approaches for detecting plant diseases

机译：检测植物疾病的图像处理方法综述

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摘要

There is intense pressure on agricultural productivity due to the ever-growing population. Several diseases affect crop yield and thus, effective control of these can significantly improve the production of food for all. In this regard, detection of diseases at an early stage and quantification of the severity, in general, has acquired urgent attention of the researchers. In this study, a summary of prevalent techniques and methodologies used for the detection, quantification and classification of diseases is presented to understand the scope of improvement. The study pays attention to critical gaps that exist in available approaches and enhance them for the early prediction of diseases. Diseases affect almost all parts of plants, e.g. root, stem, flower, leaf; a manifestation in different ways for different parts of the plant of the same disease presents a challenge for researchers. This study extends the review work published by JGA Barbedo in 2013, as there have been significant advances and numerous new techniques introduced since then. A novel approach of classifying and categorisation of the existing techniques based on pathogen types is a significant contribution by the authors in this study.
机译：由于人口不断增长，农业生产率存在强烈的压力。几种疾病影响作物产量，从而有效地控制这些可以显着改善所有食物的生产。在这方面，一般来说，在早期的阶段检测疾病，一般严重程度地获得了研究人员的紧急关注。在本研究中，提出了用于检测，定量和分类的普遍技术和方法的概述，以了解改善的范围。该研究对现有方法中存在的临界差距提请注意，并增强它们的早期预测疾病。疾病影响植物的几乎所有部分，例如根，茎，花，叶;同类疾病植物不同部位的不同方式的表现为研究人员提出了挑战。本研究延长了JGA Barbedo于2013年发布的审查工作，因为自那时出现了显着的进展和许多新技术。基于病原体类型的现有技术进行分类和分类的新方法是本研究中作者的重大贡献。

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