Content-based image retrieval by clustering

Yixin Chen, James Z. Wang, Robert Krovetz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

89 Scopus citations

Abstract

In a typical content-based image retrieval (CBIR) system, query results are a set of images sorted by feature similarities with respect to the query. However, images with high feature similarities to the query may be very different from the query in terms of semantics. This is known as the semantic gap. We introduce a novel image retrieval scheme, CLUster-based rEtrieval of images by unsupervised learning (CLUE), which tackles the semantic gap problem based on a hypothesis: semantically similar images tend to be clustered in some feature space. CLUE attempts to capture semantic concepts by learning the way that images of the same semantics are similar and retrieving image clusters instead of a set of ordered images. Clustering in CLUE is dynamic. In particular, clusters formed depend on which images are retrieved in response to the query. Therefore, the clusters give the algorithm as well as the users semantic relevant clues as to where to navigate. CLUE is a general approach that can be combined with any real-valued symmetric similarity measure (metric or nonmetric). Thus it may be embedded in many current CBIR systems. Experimental results based on a database of about 60,000 images from COREL demonstrate improved performance.

Original languageEnglish (US)
Title of host publicationProceedings of the 5th ACM SIGMM International Workshop on Multimedia Information Retrieval, MIR 2003
PublisherAssociation for Computing Machinery, Inc
Pages193-200
Number of pages8
ISBN (Electronic)1581137788, 9781581137781
DOIs
StatePublished - Nov 7 2003
Event5th ACM SIGMM International Workshop on Multimedia Information Retrieval, MIR 2003 - Berkeley, United States
Duration: Nov 7 2003 → …

Publication series

NameProceedings of the 5th ACM SIGMM International Workshop on Multimedia Information Retrieval, MIR 2003

Other

Other5th ACM SIGMM International Workshop on Multimedia Information Retrieval, MIR 2003
CountryUnited States
CityBerkeley
Period11/7/03 → …

All Science Journal Classification (ASJC) codes

  • Media Technology
  • Software
  • Information Systems
  • Computer Science Applications
  • Signal Processing

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  • Cite this

    Chen, Y., Wang, J. Z., & Krovetz, R. (2003). Content-based image retrieval by clustering. In Proceedings of the 5th ACM SIGMM International Workshop on Multimedia Information Retrieval, MIR 2003 (pp. 193-200). (Proceedings of the 5th ACM SIGMM International Workshop on Multimedia Information Retrieval, MIR 2003). Association for Computing Machinery, Inc. https://doi.org/10.1145/973264.973295