{"title":"Visual image retrieval on compressed domain with Q-distance","authors":"Hong Yu","doi":"10.1109/ICCIMA.1999.798544","DOIUrl":null,"url":null,"abstract":"This paper proposes a new image retrieval scheme that works directly on compressed image (JPEG) databases. As we know, a large percentage of the image databases are stored in compressed image format, such as JPEG format. In addition, about half of the images on the Internet are also in JPEG format. Thus, image retrieval systems that require JPEG decompression greatly limit the speed of image searching. Subsequently, new methodologies for retrieving of images without JPEG decoding is needed for Web image search and compressed image database retrieval. We propose a new metric, Q-distance, that can be utilized to measure the distance between two compressed images. A system that uses Q-distance for fast image retrieval is also presented. Experiment results show that Q-distance is robust against variation and this new retrieval scheme, which directly works in the compressed image domain, is fast to execute and suitable for Web image searching and retrieval.","PeriodicalId":110736,"journal":{"name":"Proceedings Third International Conference on Computational Intelligence and Multimedia Applications. ICCIMA'99 (Cat. No.PR00300)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Third International Conference on Computational Intelligence and Multimedia Applications. ICCIMA'99 (Cat. No.PR00300)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIMA.1999.798544","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

This paper proposes a new image retrieval scheme that works directly on compressed image (JPEG) databases. As we know, a large percentage of the image databases are stored in compressed image format, such as JPEG format. In addition, about half of the images on the Internet are also in JPEG format. Thus, image retrieval systems that require JPEG decompression greatly limit the speed of image searching. Subsequently, new methodologies for retrieving of images without JPEG decoding is needed for Web image search and compressed image database retrieval. We propose a new metric, Q-distance, that can be utilized to measure the distance between two compressed images. A system that uses Q-distance for fast image retrieval is also presented. Experiment results show that Q-distance is robust against variation and this new retrieval scheme, which directly works in the compressed image domain, is fast to execute and suitable for Web image searching and retrieval.
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
基于q距离的压缩域视觉图像检索
本文提出了一种直接在压缩图像(JPEG)数据库上工作的新的图像检索方案。我们知道,很大比例的图像数据库是以压缩图像格式存储的,例如JPEG格式。此外,互联网上大约一半的图像也是JPEG格式的。因此,需要JPEG解压缩的图像检索系统极大地限制了图像搜索的速度。因此,在Web图像搜索和压缩图像数据库检索中需要新的不需要JPEG解码的图像检索方法。我们提出了一个新的度量,Q-distance,它可以用来测量两个压缩图像之间的距离。提出了一种基于q距离的图像快速检索系统。实验结果表明,该方法具有较强的抗变异鲁棒性,且直接在压缩图像域中工作,执行速度快,适用于Web图像搜索和检索。
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
Modular rough fuzzy MLP: evolutionary design Indian language multimedia and information retrieval An image understanding system for various images based on multi-agent architecture End-to-end simulation of VBR traffic over ATM networks using CIPP network traffic model Fuzzy approach to recognize handwritten Tamil characters
×
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