The terminological image retrieval model

  • Carlo Meghini
  • Fabrizio Sebastiani
  • Umberto Straccia
Poster Session C: Compression, Hardware & Software, Image Databases, Neural Networks, Object Recognition & Reconstruction
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1311)


We present a model for image retrieval in which images are represented both at the form level, as sets of physical features of the representing objects, and at the content level, as sets of logical assertions about the represented entities as well as about facts of the subject matter that are deemed as relevant for retrieval. A uniform and powerful query language allows queries to be issued that transparently combine features pertaining to form and content. Queries are expressions of a fuzzy logical language. While that part of the query that pertains to (medium-independent) content is “directly” processed by an inferential engine, that part that pertains to (medium-dependent) form is entrusted to specialised signal processing procedures linked to the logical language by a procedural attachment mechanism.


Image Retrieval Description Logic Content Description Atomic Region Content Dimension 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Carlo Meghini
    • 1
  • Fabrizio Sebastiani
    • 1
  • Umberto Straccia
    • 1
  1. 1.Consiglio Nazionale delle RicercheIstituto di Elaborazione dell'InformazionePisaItaly

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