Urban Ontology for Semantic Interpretation of Multi-Source Images
Résumé
The multiplication of High or Very High Resolution (spatial and spectral) remotely sensed images is an opportunity to characterize and identify urban objects. Image analyses methods using object-oriented approaches, based on the use of domain knowledge, are necessary to classify these data. A major issue in these approaches is domain knowledge formalization and exploitation. In this paper, we present a methodology to build an urban ontology adapted to the multi-level interpretation of multi-source images. Domain knowledge is stored independently in the urban ontology which contains a set of pre-defined terms characterizing urban domain concepts. The ontology is then used in a classification method in order to assign segmented regions into semantic objects. A matching process between the regions and the concepts of the ontology is proposed. The method is tested on Very High Resolution images (0.7m) on the urban area of Strasbourg (France).
Origine : Fichiers produits par l'(les) auteur(s)
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