基于图像处理的植物攻击识别

B. D. D. Nayomi, Ipshitha Charles, S. Krishna, Sandip Swarnakar
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引用次数: 0

摘要

图像处理是一个新兴的领域,在农业领域的研究和进展正取得几何级数的进展。植物病害检测的各种研究正在蓬勃发展。植物病害的识别不仅可以最大限度地提高产量,而且可以为各种农业实践提供支持。植物病害分类对支撑农业至关重要。对植物病害进行人工监测和治疗是非常困难的。由于工作量大,处理时间长,因此采用图像处理技术对植物病害进行检测。植物病害分类包括加载图像、预处理、分割、特征提取、svm分类等步骤。检测疾病可能是阻止农业损失的关键。这个项目的目的是开发一个软件系统回答机械地发现和分类疾病。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
IDENTIFYING THE ATTACKS ON GROWING PLANTS BASED ON IMAGE PROCESSING
Image processing is a diverging area where researches and advancements are taking a geometrical progress in the agricultural field. Various researches are going on vigorously in plant disease detection. Identification of plant diseases can not only maximize the yield production but also can be supportive for varied types of agricultural practices. Disease classification on plant is very critical for supportable agriculture. It is very difficult to monitor or treat the plant diseases manually. It requires huge amount of work, and also need the excessive processing time, therefore image processing is used for the detection of plant diseases. Plant disease classification involves the steps like Load image, preprocessing, segmentation, feature extraction, svmClassifer. Detecting disease may be a key to stop agricultural losses. The aim of this project is to develop a software system answer that mechanically find and classify disease.
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