MUSE: A content-based image search and retrieval system using relevance feedback

被引：11

作者：

Marques, O ^{[1
]}

Furht, B ^{[1
]}

机构：

[1] Florida Atlantic Univ, Dept Comp Sci & Engn, Boca Raton, FL 33431 USA

来源：

MULTIMEDIA TOOLS AND APPLICATIONS | 2002年 / 17卷 / 01期

关键词：

content-based image search and retrieval; relevance feedback; multimedia database systems; digital image processing;

D O I：

10.1023/A:1014679605305

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The field of Content-Based Visual Information Retrieval (CBVIR) has experienced tremendous growth in the recent years and many research groups are currently working on solutions to the problem of finding a desired image or video clip in a huge archive without resorting to metadata. This paper describes the ongoing development of a CBVIR system for image search and retrieval with relevance feedback capabilities. It supports browsing, query-by-example, and two different relevance feedback modes that allow users to refine their queries by indicating which images are good or bad at each iteration.

引用

页码：21 / 50

页数：30

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