Expert system for color image retrieval

Hun Woo Yoo, Han Soo Park, Dong Sik Jang

    Research output: Contribution to journalArticlepeer-review

    28 Citations (Scopus)

    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.

    Original languageEnglish
    Pages (from-to)347-357
    Number of pages11
    JournalExpert Systems With Applications
    Volume28
    Issue number2
    DOIs
    Publication statusPublished - 2005 Feb

    Bibliographical note

    Copyright:
    Copyright 2011 Elsevier B.V., All rights reserved.

    Keywords

    • CBIR (content-based image retrieval)
    • DBS (distribution block signature)
    • MCS (major colors' set) signature
    • QM (quad modeling)
    • Relevance feedback

    ASJC Scopus subject areas

    • General Engineering
    • Computer Science Applications
    • Artificial Intelligence

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