Title :
A CBIR-framework: using both syntactical and semantical information for image description
Author :
Besson, Laurent ; Da Costa, Arnaud ; Leclercq, Eric ; Terrasse, Marie-Noëlle
Author_Institution :
Bourgogne Univ., France
Abstract :
Content-based image retrieval systems can use classification or indexing based on syntactical and/or semantic features of images. We aim at providing a framework, which can be instantiated for each specific application: a framework, which combines syntactical and semantic information for image description. We believe that a model, which integrates syntactical and semantic descriptions, together with its similarity measure between images, is the core of such a framework. In this paper, we propose an integrated model with two example applications on which expressiveness of our model have been tested.
Keywords :
content-based retrieval; data description; database indexing; image coding; programming language semantics; visual databases; CBIR; classification; content-based image retrieval system; image database; image description; image feature; image semantics; image similarity measure; image syntax; indexing; integrated model; semantic information; syntactical information; Application software; Content based retrieval; Data mining; Image databases; Image retrieval; Indexing; Information retrieval; Power system modeling; Shape; Testing;
Conference_Titel :
Database Engineering and Applications Symposium, 2003. Proceedings. Seventh International
Print_ISBN :
0-7695-1981-4
DOI :
10.1109/IDEAS.2003.1214961