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Integrated Image Content and Metadata Search and Retrieval across Multiple Databases

  • Matthew Addis
  • Mike Boniface
  • S. Goodall
  • Paul Grimwood
  • Sanghee Kim
  • Paul Lewis
  • Kirk Martinez
  • Alison Stevenson
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2728)

Abstract

This paper presents an updated technical overview of an integrated content and metadata-based image retrieval system used by several major art galleries in Europe including the Louvre in Paris, the Victoria and Albert Museum in London, the Uffizi Gallery in Florence and the National Gallery in London. In our approach, the subjects of a query (e.g. images, textual metadata attributes), the operators used in a query (e.g. SimilarTo, Contains, Equals) and the rules that constrain the query (e.g. SimilarTo can only be applied to Images) are all explicitly defined and published for each gallery collection. In this way, cross-collection queries are dynamically constructed and executed in a way that is automatically constrained to the capabilities of the particular image collections being searched. The application of existing, standards based, technology to integrate metadata and content based queries underpins an open standards approach to extending interoperability across multiple image databases.

Keywords

Image Retrieval Digital Library Resource Description Framework Image Collection Artiste Project 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1]
    ARTISTE http://www.artisteweb.orgGoogle Scholar
  2. [2]
    Addis, M., Lewis, P., Martinez, K. “ARTISTE image retrieval system puts European galleries in the picture”, Cultivate Interactive http://www.cultivateint.org/issue7/artiste/Google Scholar
  3. [3]
    F. S. Abas and K. Martinez (2002) Craquelure Analysis for Content-Based Retrieval. IEEE DSP 2002 conference. July 2002Google Scholar
  4. [4]
    M.F.A. Fauzi and P.H. Lewis Query by Fax for Content Based Image Retrieval CIVR, Lecture Notes in Computer Science, vol2383, 91–99, 2002 Springer VerlagGoogle Scholar
  5. [5]
    S Chan, K Martinez, P Lewis, C. Lahanier & J. Stevenson Handling Sub-Image Queries in Content-Based Retrieval of High Resolution Art Images. International Cultural Heritage Informatics Meeting p.157–163. September 2001Google Scholar
  6. [6]
    Open Archives Initiative http://www.openarchives.org/Google Scholar
  7. [7]
    ZING Search and Retrieve Web service http://www.loc.gov/z3950/agency/zing/srw/Google Scholar
  8. [8]
    DublinCore metadata initiative http://www.dublincore.org/Google Scholar
  9. [9]
    Artiste User Interest Group. Contact: M. Cecil-Wright mcw@it-innovation.soton.ac.ukGoogle Scholar
  10. [10]
    “D6.2 Impact on World-Wide Metadata Standards” http://www.it-innovation.soton.ac.uk/artiste/documentation/D6.2.final.pdfGoogle Scholar
  11. [11]
    ARTISTE public dissemination system http://artiste.it-innovation.soton.ac.uk/Google Scholar
  12. [12]
    z39.50 http://lcweb.loc.gov/z3950/agency/Google Scholar
  13. [13]
    Resource Description Framework http://www.w3.org/RDF/Google Scholar
  14. [14]
    “D6.1 Distributed Query Layer and Metadata Report” http://www.itinnovation.soton.ac.uk/artiste/documentation/D6.1final.pdfGoogle Scholar
  15. [15]
    G Pass, R Zabih, & J Miller. Comparing Images Using Color Coherence Vectors. MultiMedia, p65–73. ACM, 1996Google Scholar
  16. [16]
    Artiste Core schema http://artiste.it-innovation. soton.ac.uk/rdf/ArtisteCore.rdfGoogle Scholar
  17. [17]
    S.G. Mallat, A theory for multiresolution signal decomposition: The Wavelet Representation, IEEE Transactions on Pattern Analysis and Machine Intelligence, 11, 674–693, July 1989zbMATHCrossRefGoogle Scholar
  18. [18]
    Daubechies, “The wavelet transform t-frequency localisation and signal Analysis”, IEEE Transactions on Information Theory, vol36, pp. 961–1005, 1990zbMATHCrossRefMathSciNetGoogle Scholar
  19. [19]
    J. Cupitt & K. Martinez, “VIPS: an image processing system for large images”, Proc. SPIE conference on Imaging Science and Technology, San Jose, Vol. 2663, 1996, pp 19–28Google Scholar
  20. [20]
    M.F.A. Fauzi, “Texture Based Image Retrieval using Multiscale sub-image Matching”, Image and Video Communications and Processing 2003 (to be published)Google Scholar
  21. [21]
    The Semantic Web http://www.semanticweb.org/Google Scholar
  22. [22]
    P. Allen, M. Boniface, P. Lewis, K. Martinez “Interoperability between Multimedia Collections for Content & Metadata-Based Searching”, 11th WWW Conference, Hawaii. 7–11 May 2002 http://www2002.org/CDROM/alternate/196/index.htmlGoogle Scholar
  23. [23]
    F. Salleh Abas and K. Martinez, “Classification of Painting Cracks for Content-Based Analysis”, Machine Vision Applications in Industrial Inspection XI, 2003 (to be published)Google Scholar
  24. [24]
    W. M. Smeulders, M. Worring, S. Santini, A. Gupta, & R. Jain. Content-Based Image Retrieval at the End of the Early Years. In Transactions On Pattern Analysis And Machine Intelligence, volume 22 of 12, pages 1349–1380. IEEE, December 2000CrossRefGoogle Scholar
  25. [25]
    ZING CQL specification http://www.loc.gov/z3950/agency/zing/cql/cql-syntax.htmlGoogle Scholar
  26. [26]
    ARTISTE SRW Service demonstration http://artiste.it-innovation.soton.ac.uk/srwGoogle Scholar
  27. [27]
    SCULPTEUR EC IST project number 35372 http://www.sculpteurweb.orgGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Matthew Addis
    • 1
  • Mike Boniface
    • 1
  • S. Goodall
    • 2
  • Paul Grimwood
    • 1
  • Sanghee Kim
    • 2
  • Paul Lewis
    • 2
  • Kirk Martinez
    • 2
  • Alison Stevenson
    • 1
  1. 1.IT InnovationUniversity of SouthamptonUK
  2. 2.Department of Electronics and Computer ScienceUniversity of SouthamptonUK

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