一种新的多查询图像检索方法

M. Taghizadeh, A. Chalechale
{"title":"一种新的多查询图像检索方法","authors":"M. Taghizadeh, A. Chalechale","doi":"10.1109/SPIS.2015.7422313","DOIUrl":null,"url":null,"abstract":"Multiple-query image retrieval is usually utilized in order to enhance performance of the image retrieval system with considering single semantic for a query set. So far, multiple-query image retrieval based on different queries has rarely studied. In this work, we intend to address this problem using a binary component vector. This vector indicates distinct components which exist in an image. The binary component vector is also generated utilizing low-level feature extraction techniques. The final image retrieval process is performed based on this vector. The experimental results show a better performance and less computation in contrary to previous proposed methods.","PeriodicalId":424434,"journal":{"name":"2015 Signal Processing and Intelligent Systems Conference (SPIS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A novel method for multiple-query image retrieval\",\"authors\":\"M. Taghizadeh, A. Chalechale\",\"doi\":\"10.1109/SPIS.2015.7422313\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Multiple-query image retrieval is usually utilized in order to enhance performance of the image retrieval system with considering single semantic for a query set. So far, multiple-query image retrieval based on different queries has rarely studied. In this work, we intend to address this problem using a binary component vector. This vector indicates distinct components which exist in an image. The binary component vector is also generated utilizing low-level feature extraction techniques. The final image retrieval process is performed based on this vector. The experimental results show a better performance and less computation in contrary to previous proposed methods.\",\"PeriodicalId\":424434,\"journal\":{\"name\":\"2015 Signal Processing and Intelligent Systems Conference (SPIS)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Signal Processing and Intelligent Systems Conference (SPIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPIS.2015.7422313\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Signal Processing and Intelligent Systems Conference (SPIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPIS.2015.7422313","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

为了提高图像检索系统的性能,通常采用多查询图像检索,同时考虑查询集的单一语义。到目前为止,基于不同查询的多查询图像检索的研究还很少。在这项工作中,我们打算使用二进制分量向量来解决这个问题。这个向量表示图像中存在的不同分量。利用低级特征提取技术生成二元分量向量。最终的图像检索过程是基于这个向量执行的。实验结果表明,该方法比以往提出的方法性能更好,计算量更少。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
A novel method for multiple-query image retrieval
Multiple-query image retrieval is usually utilized in order to enhance performance of the image retrieval system with considering single semantic for a query set. So far, multiple-query image retrieval based on different queries has rarely studied. In this work, we intend to address this problem using a binary component vector. This vector indicates distinct components which exist in an image. The binary component vector is also generated utilizing low-level feature extraction techniques. The final image retrieval process is performed based on this vector. The experimental results show a better performance and less computation in contrary to previous proposed methods.
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
期刊最新文献
User-friendly visual secret sharing based on random grids An adaptive single image method for super resolution An improved DV-Hop localization algorithm in wireless sensor networks Optimization of the low-cost INS/GPS navigation system using ANFIS for high speed vehicle application A novel compressed sensing DOA estimation using difference set codes
×
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