Classification Of Plant Leaf Diseases Using Machine Learning And Image Preprocessing Techniques

Pushkar Sharma, P. Hans, Subhash Chand Gupta
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引用次数: 49

Abstract

Agriculture is one of the main factor that decides the growth of any country. In India itself around 65% of the population is based on agriculture. Due to various seasonal conditions the crops get infected by various kind of diseases. These diseases firstly affect the leaves of the plant and later infected the whole plant which in turn affect the quality and quantity of crop cultivated. As there are large number of plants in the farm, it becomes very difficult for the human eye to detect and classify the disease of each plant in the field. And it is very important to diagnose each plant because these diseases may spread. Hence in this paper we are introducing the artificial intelligence based automatic plant leaf disease detection and classification for quick and easy detection of disease and then classifying it and performing required remedies to cure that disease. This approach of ours goals towards increasing the productivity of crops in agriculture. In this approach we have follow several steps i.e. image collection, image preprocessing, segmentation and classification.
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基于机器学习和图像预处理技术的植物叶片病害分类
农业是决定任何国家发展的主要因素之一。在印度,大约65%的人口以农业为生。由于不同的季节条件,农作物会感染各种疾病。这些病害首先影响植株的叶片,然后感染整个植株,进而影响栽培作物的质量和数量。由于农场中植物数量众多,人眼很难对田间每一种植物的病害进行检测和分类。对每一种植物进行诊断是非常重要的,因为这些疾病可能会传播。因此,本文介绍了一种基于人工智能的植物叶片病害自动检测和分类方法,以便快速简便地检测病害,并对病害进行分类和治疗。我们的目标是提高农业作物的生产力。在这种方法中,我们遵循了几个步骤,即图像采集,图像预处理,分割和分类。
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