Application of content based image retrieval for E-commerce

V. Kodgirwar
{"title":"Application of content based image retrieval for E-commerce","authors":"V. Kodgirwar","doi":"10.1109/STARTUP.2016.7583906","DOIUrl":null,"url":null,"abstract":"E-purchase is being preferred by millions of consumers over traditional shop purchases, all over the world. So in this case we just focus on CBIR system that will be able to learn user's choices in clothing and help him or her to make the best choices of clothing during e-purchase. This work will emphasize on the images matching aspect of the system only to retrieve relevant clothing as per the user's liking. Now we are applying different texture features for detecting patterns. Texture features are Contrast, Coarsness, Entropy, Energy, Correlation.","PeriodicalId":355852,"journal":{"name":"2016 World Conference on Futuristic Trends in Research and Innovation for Social Welfare (Startup Conclave)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 World Conference on Futuristic Trends in Research and Innovation for Social Welfare (Startup Conclave)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/STARTUP.2016.7583906","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

E-purchase is being preferred by millions of consumers over traditional shop purchases, all over the world. So in this case we just focus on CBIR system that will be able to learn user's choices in clothing and help him or her to make the best choices of clothing during e-purchase. This work will emphasize on the images matching aspect of the system only to retrieve relevant clothing as per the user's liking. Now we are applying different texture features for detecting patterns. Texture features are Contrast, Coarsness, Entropy, Energy, Correlation.
基于内容的图像检索在电子商务中的应用
在世界各地,与传统的实体店购物相比,电子购物正受到数百万消费者的青睐。所以在这种情况下,我们只关注CBIR系统,它将能够学习用户对服装的选择,并帮助他或她在电子购买时做出最佳的服装选择。本工作将着重于系统的图像匹配方面,只根据用户的喜好检索相关的服装。现在我们正在应用不同的纹理特征来检测图案。纹理特征是对比度,粗度,熵,能量,相关性。
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