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Image processing Based Detection of Fungal Diseases in Plants

机译:基于图像处理的植物真菌疾病的检测

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This paper presents a study on the image processing techniques used to identify and classify fungal disease symptoms affected on different agriculture/horticulture crops. Computers have been used to mechanization, automation, and to develop decision support system for taking strategic decision on the agricultural production and protection research. The plant disease diagnosis is limited by the human visual capabilities because most of the first symptoms are microscopic. As plant health monitoring is still carried out by humans due to the visual nature of the plant monitoring task, computer vision techniques seem to be well adapted. One of the areas considered here is the processing of images of disease affected agriculture/horticulture crops. The quantity and quality of plant products gets rcduced by plant diseases. The goal is to detect, to identify, and to accurately quantify the first symptoms of diseases. Plant diseases are caused by bacteria, fungi, virus, nematodes, etc., of which fungi is the main disease causing organism. Focus has been done on the early detection of fungal disease based on the symptoms.
机译:本文介绍了用于识别和分类对不同农业/园艺作物影响的真菌疾病症状的图像处理技术的研究。计算机已被用于机械化,自动化和制定决策支持系统,以对农业生产和保护研究进行战略决策。植物疾病诊断受人类视觉能力的限制,因为大多数最初的症状是显微镜。由于植物健康监测仍然是由于植物监测任务的视觉性质而被人类进行的,但计算机视觉技术似乎很好。这里考虑的领域之一是处理受影响的农业/园艺作物的疾病图像。植物疾病的植物产品的数量和质量得到了植物疾病。目标是检测,识别,并准确量化疾病的第一个症状。植物疾病是由细菌,真菌,病毒,线虫等引起的,其中真菌是导致生物体的主要疾病。基于症状,对真菌病的早期检测进行了重点。

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