An Improved Image Retrieval Algorithm

Guangwen Zhang, Lei Yang, Jun Zhai, Hui Li, Yueping Lian
{"title":"An Improved Image Retrieval Algorithm","authors":"Guangwen Zhang, Lei Yang, Jun Zhai, Hui Li, Yueping Lian","doi":"10.1115/1.859810.paper114","DOIUrl":null,"url":null,"abstract":"This paper introduces the whole process of retrieval based on color characteristics.First of all,this article presents the HSV color model in brief,then HSV color model is selected to verify other links to the choice of methods.Next,the color space is quantized and the quantization standard can be divided into two kinds:equidistant quantification and non-equidistant quantification.Then it is choosing proper feature extraction method.General color histogram can only express the global statistical information of the image without the color space,so this article adopts the method of local cumulative histogram,and in the choice of similarity measure,this paper compares Euclidean distance and the weighted distance,and then concludes the more effective retrieval results.Finally,through the contrast,this paper chooses the optimal image retrieval algorithm:HSV color model-Local accumulate histogram-Euclidean distance-Equidistant quantification.","PeriodicalId":127233,"journal":{"name":"Journal of Communication University of China","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Communication University of China","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/1.859810.paper114","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

This paper introduces the whole process of retrieval based on color characteristics.First of all,this article presents the HSV color model in brief,then HSV color model is selected to verify other links to the choice of methods.Next,the color space is quantized and the quantization standard can be divided into two kinds:equidistant quantification and non-equidistant quantification.Then it is choosing proper feature extraction method.General color histogram can only express the global statistical information of the image without the color space,so this article adopts the method of local cumulative histogram,and in the choice of similarity measure,this paper compares Euclidean distance and the weighted distance,and then concludes the more effective retrieval results.Finally,through the contrast,this paper chooses the optimal image retrieval algorithm:HSV color model-Local accumulate histogram-Euclidean distance-Equidistant quantification.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
一种改进的图像检索算法
本文介绍了基于颜色特征的图像检索的全过程。本文首先对HSV颜色模型进行了简要介绍,然后对HSV颜色模型的选择进行了验证,以其他环节来选择方法。其次,对色彩空间进行量化,量化标准分为等距量化和非等距量化两种。其次是选择合适的特征提取方法。一般的颜色直方图在没有颜色空间的情况下,只能表达图像的全局统计信息,因此本文采用局部累积直方图的方法,并在相似性测度的选择上,比较了欧几里得距离和加权距离,从而得出更有效的检索结果。最后,通过对比,选择了最优的图像检索算法:HSV颜色模型-局部累积直方图-欧几里得距离-等距量化。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
An Improved Image Retrieval Algorithm Systems Thinking(I)
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1