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Querying Web Images by Topic and Example Specification Methods

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Advanced Data Mining and Applications (ADMA 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3584))

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Abstract

Ever since the advent of Internet, there has been an immense growth in the amount of image data that is available on the World Wide Web. With such a magnitude of image availability, an efficient and effective image retrieval system is required to make use of this information. This research presents an image matching and indexing technique that improvises on existing integrated image retrieval methods. The proposed system integrates query by topic and query by example specification methods. The topic-based image retrieval uses the structured format of HTML documents to retrieve relevant pages and potential match images. The query by example specification performs content-based image match for the retrieval of smaller and relatively closer results of the example image. The main goal is to develop a functional image search and indexing system without using a database and to demonstrate that better retrieval results can be achieved with this proposed hybrid search technique.

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Author information

Authors and Affiliations

  1. Mathematics and Computer Science Dept, California State Univ, East Bay, 25800 Carlos Bee Blvd, Hayward, CA, 94542, USA

    Ching-Cheng Lee & Rashmi Prabhakara

Authors
  1. Ching-Cheng Lee
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  2. Rashmi Prabhakara
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Editor information

Editors and Affiliations

  1. School of Information Technology and Electrical Engineering, The University of Queensland, 4072, Brisbane, Queensland, Australia

    Xue Li

  2. The State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 430072, Wuhan, China

    Shuliang Wang

  3. School of ITEE, The Univ of Queensland, St. Lucia, 4072, QLD, Australia

    Zhao Yang Dong

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© 2005 Springer-Verlag Berlin Heidelberg

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Lee, CC., Prabhakara, R. (2005). Querying Web Images by Topic and Example Specification Methods. In: Li, X., Wang, S., Dong, Z.Y. (eds) Advanced Data Mining and Applications. ADMA 2005. Lecture Notes in Computer Science(), vol 3584. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527503_62

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  • DOI: https://doi.org/10.1007/11527503_62

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-27894-8

  • Online ISBN: 978-3-540-31877-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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