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Study of digital image processing techniques for leaf disease detection and classification

机译:叶病检测与分类的数字图像处理技术研究

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摘要

In this paper, we address a comprehensive study on disease recognition and classification of plant leafs using image processing methods. 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. The paper has been divided into two main categories viz. detection and classification of leafs. A comprehensive discussion on the diseases detection and classification performance is presented based on analysis of previously proposed state of art techniques particularly from 1997 to 2016. Finally, discussed and classify the challenges and some prospects for future improvements in this space.
机译:在本文中,我们针对使用图像处理方法对植物叶片的疾病识别和分类进行了全面的研究。传统的手动视觉质量检查无法系统地定义,因为这种方法不可预测且不一致。此外,除了处理时间不成比例之外,它还涉及植物病害诊断(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。本文已分为两个主要类别。叶子的检测和分类。在分析先前提出的最新技术水平(尤其是1997年至2016年)的基础上,对疾病的检测和分类性能进行了全面的讨论。最后,讨论并分类了该领域中的挑战和未来改进的一些前景。

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