Fuzzy c-means clustering algorithm for quality inspection of fruits based on image sensors data

Ebrahim Aghajari, D. Gharpure
{"title":"Fuzzy c-means clustering algorithm for quality inspection of fruits based on image sensors data","authors":"Ebrahim Aghajari, D. Gharpure","doi":"10.1109/ISPTS.2012.6260927","DOIUrl":null,"url":null,"abstract":"Use of FCM for inspection of fruits is proposed in this paper. In this method, an image of fruits is firstly taken in RGB color model. The output of imaging sensors is preprocessed in order to get proper image for evaluation purpose. An algorithm based on fuzzy c-means theory was developed for quality inspection of fruits. Discrete Wavelet Transform (DWT) is applied in order to extract the features. The DWT features are used as input data to FCM algorithm to get clusters and segment the image. An evaluation method based on image processing techniques was developed for the purpose of evaluation quality of fruits. The experimental result of proposed method shows that fuzzy evaluation is a viable way for quality inspection of fruits.","PeriodicalId":6431,"journal":{"name":"2012 1st International Symposium on Physics and Technology of Sensors (ISPTS-1)","volume":"29 1","pages":"216-219"},"PeriodicalIF":0.0000,"publicationDate":"2012-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 1st International Symposium on Physics and Technology of Sensors (ISPTS-1)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPTS.2012.6260927","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

Use of FCM for inspection of fruits is proposed in this paper. In this method, an image of fruits is firstly taken in RGB color model. The output of imaging sensors is preprocessed in order to get proper image for evaluation purpose. An algorithm based on fuzzy c-means theory was developed for quality inspection of fruits. Discrete Wavelet Transform (DWT) is applied in order to extract the features. The DWT features are used as input data to FCM algorithm to get clusters and segment the image. An evaluation method based on image processing techniques was developed for the purpose of evaluation quality of fruits. The experimental result of proposed method shows that fuzzy evaluation is a viable way for quality inspection of fruits.
基于图像传感器数据的水果质量检测模糊c均值聚类算法
本文提出了用流式细胞仪检测水果的方法。该方法首先采用RGB颜色模型提取水果图像。对成像传感器的输出进行预处理,得到适合评价的图像。提出了一种基于模糊c均值理论的水果质量检测算法。采用离散小波变换(DWT)提取特征。将DWT特征作为FCM算法的输入数据进行聚类和分割。提出了一种基于图像处理技术的水果品质评价方法。实验结果表明,模糊评价是一种可行的水果质量检验方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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