Plant Leaf Disease Detection Using Image Processing: A Comprehensive Review

Malaysian Journal of Science and Advanced Technology Pub Date : 2022-10-16 DOI:10.56532/mjsat.v2i4.80

Md. Nabobi Hasan, Mufrad Mustavi, Md. Abu Jubaer, Md. Tanvir Shahriar, Tanvir Ahmed

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引用次数: 1

Abstract

In this review paper, previous and current works for plant leaf disease detection have been studied. The traditional manual visual quality inspection cannot be defined systematically as this method is unpredictable and inconsistent. Moreover, it involves a remarkable amount of expertise in the field of plant disease diagnostics (phytopathology) in addition to the disproportionate processing times. Hence, image processing has been applied for the recognition of plant diseases. This paper has been divided into three main parts. In the first part, a comprehensive review based on algorithms is provided were the major algorithms and works conducted using image processing and artificial intelligence algorithms have been compared. The second part discusses the frameworks and compared the previous works. Then, a comprehensive discussion based on the accuracy of the results was provided. Based on the review conducted, a detailed explanation of the illnesses detection and classification performance is provided. Finally, the findings and challenges in plant leaf detection using image processing are summarized and discussed.

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基于图像处理的植物叶片病害检测综述

本文对植物叶片病害检测的研究进展进行了综述。传统的人工目视质量检测方法具有不可预测性和不一致性，无法对其进行系统的定义。此外，除了处理时间不成比例外，它还涉及植物疾病诊断(植物病理学)领域的大量专业知识。因此，图像处理已被应用于植物病害的识别。本文主要分为三个部分。第一部分是基于算法的综合综述，比较了图像处理和人工智能算法的主要算法和工作。第二部分讨论了框架，并比较了前人的研究成果。然后，基于结果的准确性进行了全面的讨论。在综述的基础上，对疾病检测和分类性能进行了详细的说明。最后，对植物叶片图像检测的研究成果和面临的挑战进行了总结和讨论。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Malaysian Journal of Science and Advanced Technology

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