An integrated fuzzy-rough set model for identification of tea leaf diseases

IF 0.7 4区 农林科学 Q3 AGRICULTURE, MULTIDISCIPLINARY Pakistan Journal of Agricultural Sciences Pub Date : 2022-11-01 DOI:10.21162/pakjas/22.1403
J. S. Krishnan
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引用次数: 1

Abstract

Tea is one of the major economic crops of India. People use tiny tea leaves to make beverages. The diseases in tea leaves affect the quality and yield of this cultivation. This paper proposes a disease classification model to prevent the major loss in crop yield.Tea leaf images are captured using a camera, and various image processing techniques are applied to the images to identify which disease is affected. The proposed model works for three major tea leaf diseases: blister blight, scab, and spot. The model extracts the Haralick features using Gray Level Co-occurrence Matrix (GLCM), and the most relevant features are selected with the help of the metaheuristic optimization technique. Fuzzy Rough Nearest Neighbor (FRNN) is used for classification techniques, and the model gave better accuracy than other existing techniques
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茶叶病害识别的模糊-粗糙集综合模型
茶是印度的主要经济作物之一。人们用微小的茶叶制作饮料。茶叶中的病害影响了茶叶的品质和产量。本文提出了一种防止作物产量重大损失的病害分类模型。使用相机拍摄茶叶图像,并将各种图像处理技术应用于图像,以识别哪些疾病受到影响。该模型适用于三种主要的茶叶病害:水泡病、赤霉病和斑点病。该模型使用灰度共生矩阵(GLCM)提取Haralick特征,并借助元启发式优化技术选择最相关的特征。模糊粗糙最近邻(FRNN)用于分类技术,该模型比现有的其他技术具有更好的精度
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来源期刊
Pakistan Journal of Agricultural Sciences
Pakistan Journal of Agricultural Sciences AGRICULTURE, MULTIDISCIPLINARY-
CiteScore
1.80
自引率
25.00%
发文量
18
审稿时长
6-12 weeks
期刊介绍: Pakistan Journal of Agricultural Sciences is published in English four times a year. The journal publishes original articles on all aspects of agriculture and allied fields.
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