Expert system for color image retrieval
- Authors
- Yoo, HW; Park, HS; Jang, DS
- Issue Date
- Feb-2005
- Publisher
- PERGAMON-ELSEVIER SCIENCE LTD
- Keywords
- MCS (major colors' set) signature; DBS (distribution block signature); QM (quad modeling); CBIR (content-based image retrieval); relevance feedback
- Citation
- EXPERT SYSTEMS WITH APPLICATIONS, v.28, no.2, pp.347 - 357
- Indexed
- SCIE
SCOPUS
- Journal Title
- EXPERT SYSTEMS WITH APPLICATIONS
- Volume
- 28
- Number
- 2
- Start Page
- 347
- End Page
- 357
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/123257
- DOI
- 10.1016/j.eswa.2004.10.018
- ISSN
- 0957-4174
- Abstract
- Recently, as Web and various databases contain a large number of images, content-based image retrieval (CBIR) applications are greatly needed. This paper proposes a new image retrieval system using color-spatial information from those applications. First, this paper suggests two kinds of indexing keys to prune away irrelevant images to a given query image: major colors' set (MCS) signature related with color information and distribution block signature (DBS) related with spatial information. After successively applying these filters to a large database, we get only small amount of high potential candidates that are somewhat similar to a query image. Then we make use of the quad modeling (QM) method to set the initial weights of two-dimensional cell in a query image according to each major color. Finally, we retrieve more similar images from the database by comparing a query image with candidate images through a similarity measuring function associated with the weights. In that procedure, we use a new relevance feedback mechanism. This feedback enhances the retrieval effectiveness by dynamically modulating the weights of color-spatial information. Experiments show that the proposed system is not only efficient but also effective. (C) 2004 Elsevier Ltd. All rights reserved.
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Collections - College of Engineering > School of Industrial and Management Engineering > 1. Journal Articles
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