基于2/ sp1次/2 DCT和IDS压缩的医学图像索引与检索

K. A. Saadi, A. Zemouri, Z. Brahimi, H. Meraoubi
{"title":"基于2/ sp1次/2 DCT和IDS压缩的医学图像索引与检索","authors":"K. A. Saadi, A. Zemouri, Z. Brahimi, H. Meraoubi","doi":"10.1109/ISDA.2005.56","DOIUrl":null,"url":null,"abstract":"Although digital images indexing and querying techniques have extensively been studied for the last years, few systems are dedicated to medical images today while the need for content-based analysis and retrieval tools increases with the growth of digital medical image databases. In this paper, we present a content based medical images indexing and retrieval technique (CBIR) using the 2/spl times/2 discrete cosine transform and information dominance strategy (IDS) compression. The extraction of the feature vectors is based on a 4/spl times/4 DCT model proposed in the literature. These features are directly generated from the 2/spl times/2 DCT coefficients reorganized in subbands and the search process is carried out: by' calculating cosine distance measure between the signatures of the query image and those stored in the database. The developed 2/spl times/2 DCT approach is expected to be very useful for a targeted seeking.","PeriodicalId":345842,"journal":{"name":"5th International Conference on Intelligent Systems Design and Applications (ISDA'05)","volume":"338 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Indexing and retrieval medical images based on 2/spl times/2 DCT and IDS compression\",\"authors\":\"K. A. Saadi, A. Zemouri, Z. Brahimi, H. Meraoubi\",\"doi\":\"10.1109/ISDA.2005.56\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Although digital images indexing and querying techniques have extensively been studied for the last years, few systems are dedicated to medical images today while the need for content-based analysis and retrieval tools increases with the growth of digital medical image databases. In this paper, we present a content based medical images indexing and retrieval technique (CBIR) using the 2/spl times/2 discrete cosine transform and information dominance strategy (IDS) compression. The extraction of the feature vectors is based on a 4/spl times/4 DCT model proposed in the literature. These features are directly generated from the 2/spl times/2 DCT coefficients reorganized in subbands and the search process is carried out: by' calculating cosine distance measure between the signatures of the query image and those stored in the database. The developed 2/spl times/2 DCT approach is expected to be very useful for a targeted seeking.\",\"PeriodicalId\":345842,\"journal\":{\"name\":\"5th International Conference on Intelligent Systems Design and Applications (ISDA'05)\",\"volume\":\"338 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-09-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"5th International Conference on Intelligent Systems Design and Applications (ISDA'05)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISDA.2005.56\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"5th International Conference on Intelligent Systems Design and Applications (ISDA'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISDA.2005.56","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

尽管数字图像索引和查询技术在过去几年中得到了广泛的研究,但今天很少有系统专门用于医学图像,而随着数字医学图像数据库的增长,对基于内容的分析和检索工具的需求也在增加。本文提出了一种基于内容的医学图像索引与检索技术(CBIR),该技术采用2/ sp1次/2离散余弦变换和信息优势策略(IDS)压缩。特征向量的提取基于文献中提出的4/spl times/4 DCT模型。这些特征是由在子带中重组的2/spl times/2 DCT系数直接生成的,并通过计算查询图像的特征与数据库中存储的特征之间的余弦距离度量来进行搜索过程。开发的2/ sp1次/2 DCT方法预计对目标找井非常有用。
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
Indexing and retrieval medical images based on 2/spl times/2 DCT and IDS compression
Although digital images indexing and querying techniques have extensively been studied for the last years, few systems are dedicated to medical images today while the need for content-based analysis and retrieval tools increases with the growth of digital medical image databases. In this paper, we present a content based medical images indexing and retrieval technique (CBIR) using the 2/spl times/2 discrete cosine transform and information dominance strategy (IDS) compression. The extraction of the feature vectors is based on a 4/spl times/4 DCT model proposed in the literature. These features are directly generated from the 2/spl times/2 DCT coefficients reorganized in subbands and the search process is carried out: by' calculating cosine distance measure between the signatures of the query image and those stored in the database. The developed 2/spl times/2 DCT approach is expected to be very useful for a targeted seeking.
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
Distributed service-oriented architecture for information extraction system "Semanta" HAUNT-24: 24-bit hierarchical, application-confined unique naming technique The verification's criterion of learning algorithm New evolutionary approach to the GCP: a premature convergence and an evolution process character A summary-attainment-surface plotting method for visualizing the performance of stochastic multiobjective optimizers
×
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