Identification of plant leaf diseases using image processing techniques

V. Pooja, Rahul Das, V. Kanchana
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引用次数: 92

Abstract

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. This paper proposes a disease detection and classification technique with the help of machine learning mechanisms and image processing tools. Initially, identifying and capturing the infected region is done and latter image preprocessing is performed. Further, the segments are obtained and the area of interest is recognized and the feature extraction is done on the same. Finally the obtained results are sent through SVM Classifiers to get the results. The Support Vector Machines outperforms the task of classification of diseases, results show that the methodology put forward in this paper provides considerably better results than the previously used disease detection techniques.
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利用图像处理技术识别植物叶片病害
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。本文提出了一种基于机器学习机制和图像处理工具的疾病检测与分类技术。首先,识别和捕获感染区域,然后进行图像预处理。在此基础上,对感兴趣的区域进行识别和特征提取。最后将得到的结果通过SVM分类器发送得到结果。支持向量机在疾病分类任务上表现优异,结果表明本文提出的方法比以前使用的疾病检测技术提供了明显更好的结果。
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