用SVM分类器检测蓝莓叶片图像中的红斑

M. Latha, S. Jaya
{"title":"用SVM分类器检测蓝莓叶片图像中的红斑","authors":"M. Latha, S. Jaya","doi":"10.21917/ijivp.2019.0286","DOIUrl":null,"url":null,"abstract":"Identification and classification of the plant leaf is efficient way to preventing loss occurred in agricultural field. The Septoria leaf spot is mainly affect the leaves which caused by a fungus, flu, bacteria. The Production of blueberry fruit is decreasing due to the disease affected on its stem and leaf. Small brown spots are frequently visible on blueberry leaves at specific period in the year. The spots, generally surrounded by bright yellow halos, start on the lower leaves and slowly appear on upper leaves over time. Image processing technology has been proved to be an efficient analysis to identify and detect the disease on a leaf. This proposed paper intends to focus to detect and classify a Septoria leaf spot on blueberry using Image Processing techniques such as, k-means clustering (k-nearest neighbor) for Segmentation, Gray-Level Co-occurrence Matrix for feature extraction and Support Vector Machine classifier to detect the leaf stage whether it is affected by Septoria spot or not. Totally 13 features have been extracted from each Blueberry leaf images where dataset of 40 images were taken for training and testing process partially and obtained the accuracy level was 96.77% using F-measure.","PeriodicalId":30615,"journal":{"name":"ICTACT Journal on Image and Video Processing","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"DETECTION OF SEPTORIA SPOT ON BLUEBERRY LEAF IMAGES USING SVM CLASSIFIER\",\"authors\":\"M. Latha, S. Jaya\",\"doi\":\"10.21917/ijivp.2019.0286\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Identification and classification of the plant leaf is efficient way to preventing loss occurred in agricultural field. The Septoria leaf spot is mainly affect the leaves which caused by a fungus, flu, bacteria. The Production of blueberry fruit is decreasing due to the disease affected on its stem and leaf. Small brown spots are frequently visible on blueberry leaves at specific period in the year. The spots, generally surrounded by bright yellow halos, start on the lower leaves and slowly appear on upper leaves over time. Image processing technology has been proved to be an efficient analysis to identify and detect the disease on a leaf. This proposed paper intends to focus to detect and classify a Septoria leaf spot on blueberry using Image Processing techniques such as, k-means clustering (k-nearest neighbor) for Segmentation, Gray-Level Co-occurrence Matrix for feature extraction and Support Vector Machine classifier to detect the leaf stage whether it is affected by Septoria spot or not. Totally 13 features have been extracted from each Blueberry leaf images where dataset of 40 images were taken for training and testing process partially and obtained the accuracy level was 96.77% using F-measure.\",\"PeriodicalId\":30615,\"journal\":{\"name\":\"ICTACT Journal on Image and Video Processing\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ICTACT Journal on Image and Video Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21917/ijivp.2019.0286\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ICTACT Journal on Image and Video Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21917/ijivp.2019.0286","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

植物叶片的鉴定和分类是防止农田发生损失的有效途径。Septoria叶斑病主要是由真菌、流感、细菌引起的。蓝莓果实的产量正在下降,因为它的茎和叶受到了疾病的影响。在一年中的特定时期,蓝莓叶片上经常可见小的棕色斑点。斑点通常被明亮的黄色光晕包围,从下部叶片开始,随着时间的推移慢慢出现在上部叶片上。图像处理技术已被证明是识别和检测叶片疾病的有效分析方法。本文旨在利用图像处理技术,如用于分割的k-均值聚类(k-最近邻)、用于特征提取的灰度共生矩阵和用于检测叶期是否受Septoria斑点影响的支持向量机分类器,对蓝莓上的Septoria叶斑进行检测和分类。从每幅蓝莓叶图像中提取了13个特征,其中40幅图像的数据集部分用于训练和测试过程,使用F-measure获得的准确率为96.77%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DETECTION OF SEPTORIA SPOT ON BLUEBERRY LEAF IMAGES USING SVM CLASSIFIER
Identification and classification of the plant leaf is efficient way to preventing loss occurred in agricultural field. The Septoria leaf spot is mainly affect the leaves which caused by a fungus, flu, bacteria. The Production of blueberry fruit is decreasing due to the disease affected on its stem and leaf. Small brown spots are frequently visible on blueberry leaves at specific period in the year. The spots, generally surrounded by bright yellow halos, start on the lower leaves and slowly appear on upper leaves over time. Image processing technology has been proved to be an efficient analysis to identify and detect the disease on a leaf. This proposed paper intends to focus to detect and classify a Septoria leaf spot on blueberry using Image Processing techniques such as, k-means clustering (k-nearest neighbor) for Segmentation, Gray-Level Co-occurrence Matrix for feature extraction and Support Vector Machine classifier to detect the leaf stage whether it is affected by Septoria spot or not. Totally 13 features have been extracted from each Blueberry leaf images where dataset of 40 images were taken for training and testing process partially and obtained the accuracy level was 96.77% using F-measure.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
审稿时长
8 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信