基于(特征、匹配测度和子空间)选择的高效图像检索系统

IF 0.3 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Mawloud Mosbah
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引用次数: 2

摘要

基于内容的图像检索(CBIR)系统作为一个研究领域出现以来,越来越受到人们的重视。文献综述表明,迄今为止,在该领域所做的努力要么是有效性,要么是效率。本文通过引入一种基于特征、匹配度量和子空间选择的高效图像检索方法,解决了检索的准确性和效率问题。选择依赖于用户注入的相关反馈信息。该方法在Corel-1Kimages数据库上进行了测试。所得结果是很有希望的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Efficient and Effective Image Retrieval System on the basis of (Feature, Matching Measure and sub-space) Selection
Since its appearance as a research field, Content-based Image Retrieval (CBIR) system has increasingly received an important attention. Review of literature reveals that the efforts put, up to now, in the field address either effectiveness or efficiency. In this paper, we address both accuracy and efficiencythrough introducing an efficient and an effective image retrieval approach based on feature, matching measure and sub-spaceselection. The selection relies on relevance feedback information injected by the user. The approach is tested on Corel-1Kimages database. The obtained results are very promising.
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来源期刊
Journal of Information and Organizational Sciences
Journal of Information and Organizational Sciences COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
1.10
自引率
0.00%
发文量
14
审稿时长
12 weeks
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