article

Retrieve images by understanding semantic links and clustering image fragments

Author:

Hai ZhugeAuthors Info & Claims

Journal of Systems and Software, Volume 73, Issue 3

Pages 455 - 466

https://doi.org/10.1016/j.jss.2003.08.243

Published: 01 November 2004 Publication History

Abstract

The main obstacle to realize real semantic-based image retrieval is that semantic description of versatile images is difficult. The basic ideas of this paper are that the semantics of an object can be refined through top-down orthogonal semantic classification and that the semantics of an object can be reflected by the semantics of relevant objects and the semantic relationships between them. To reflect the semantic relationships between images, we propose a set of primitive semantic links as the enhancement of the hyperlinks connecting Web pages. The semantic link network is the natural extension of the hyperlink network so it can inherit the existing theory and method on hyperlink network. Based on the single semantic image established upon the orthogonal semantic space and the semantic link space, the proposed image retrieval approach enables users to obtain the semantic clustering of relevant images rather than a list of isolated images as the output of the current search engine and to browse images along semantic paths with the support of semantic link reasoning. Semantic matching and reasoning for realizing intelligent semantic image retrieval is based on graph operation and matrix operation.

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Cited By

García-Crespo ÁColomo-Palacios RGómez-Berbís JGarcía-Sánchez F(2010)SOLARFuture Generation Computer Systems10.1016/j.future.2009.07.00826:3(374-380)Online publication date: 1-Mar-2010
https://dl.acm.org/doi/10.1016/j.future.2009.07.008
Pons A(2006)Object prefetching using semantic linksACM SIGMIS Database: the DATABASE for Advances in Information Systems10.1145/1120501.112050837:1(97-109)Online publication date: 31-Jan-2006
https://dl.acm.org/doi/10.1145/1120501.1120508
Zhuge HLuo X(2006)Automatic generation of document semantics for the e-science Knowledge GridJournal of Systems and Software10.1016/j.jss.2005.08.02279:7(969-983)Online publication date: 1-Jul-2006
https://dl.acm.org/doi/10.1016/j.jss.2005.08.022
Show More Cited By

Index Terms

Retrieve images by understanding semantic links and clustering image fragments
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision representations
        Hierarchical representations
    2. Knowledge representation and reasoning
      1. Semantic networks
  2. Machine learning
    1. Learning paradigms
      1. Unsupervised learning
        Cluster analysis

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Information & Contributors

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Published In

cover image Journal of Systems and Software

Journal of Systems and Software Volume 73, Issue 3

November-December 2004

187 pages

ISSN:0164-1212

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Elsevier Science Inc.

United States

Publication History

Published: 01 November 2004

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Cited By

García-Crespo ÁColomo-Palacios RGómez-Berbís JGarcía-Sánchez F(2010)SOLARFuture Generation Computer Systems10.1016/j.future.2009.07.00826:3(374-380)Online publication date: 1-Mar-2010
https://dl.acm.org/doi/10.1016/j.future.2009.07.008
Pons A(2006)Object prefetching using semantic linksACM SIGMIS Database: the DATABASE for Advances in Information Systems10.1145/1120501.112050837:1(97-109)Online publication date: 31-Jan-2006
https://dl.acm.org/doi/10.1145/1120501.1120508
Zhuge HLuo X(2006)Automatic generation of document semantics for the e-science Knowledge GridJournal of Systems and Software10.1016/j.jss.2005.08.02279:7(969-983)Online publication date: 1-Jul-2006
https://dl.acm.org/doi/10.1016/j.jss.2005.08.022
Vassiliadis BStefani ADrossos LIoannou K(2005)Knowledge discovery in multimedia repositoriesProceedings of the 7th WSEAS International Conference on Mathematical Methods and Computational Techniques In Electrical Engineering10.5555/1366645.1366701(330-335)Online publication date: 27-Oct-2005
https://dl.acm.org/doi/10.5555/1366645.1366701

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