PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Meghini C., Sebastiani F., Straccia U. The Terminological Image Data Model. Technical report, 1996.
 
 
Abstract
(English)
This study addresses the problem of injecting semantics into image retrieval by presenting an image data model in which images are represented both at the form and at the content level. The data model is logic-based, in the sense that the representation of image content is based on a {em description logic} (DL). Features of images pertaining to form impact on retrieval through a mechanism of procedural attachments, which implements the connection between (logical) reasoning about content and (non-logical) reasoning about form. The DL-based query language of the model thus allows the expression of image retrieval requests addressing both visual and conceptual similarity, and its underlying logic permits, among other things, to bring to bear domain and contextual knowledge in the retrieval process. The model is extensible, in that the set of symbols representing similarity can be enriched at will.
Subject Data Model
H.3.3 Information Search and Retrieval: Retrieval models
I.2.4 Knowledge Representation Formalisms and Methods: Representation languages
I.4.10 Image Representation . Multidimensional


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