The description logic handbook: theory, implementation, and applications
The description logic handbook: theory, implementation, and applications
The foundational model of anatomy in OWL: Experience and perspectives
Web Semantics: Science, Services and Agents on the World Wide Web
Fuzzy spatial relation ontology for image interpretation
Fuzzy Sets and Systems
COMM: designing a well-founded multimedia ontology for the web
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
A survey of semantic image and video annotation tools
Knowledge-driven multimedia information extraction and ontology evolution
M-OntoMat-Annotizer: image annotation linking ontologies and multimedia low-level features
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
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Ontologies provide a formal approach to knowledge representation suitable for digital content annotation. In the context of image annotation a variety of ontology-based tools has been proposed. Most of them enable manual annotation of the images with higher level concepts whereas many of them are capable of formally representing low-level features as well. However, they either consider specific, usually quantitative, representations of the low-level features, or spatial semantics limited to 2D/3D image spaces. In this paper we propose a novel ontology-based methodology for automatic image annotation that exploits generalized qualitative spatial relations between objects, given an image domain. To represent knowledge for the spatial arrangements, we have implemented an ontology that models spatial relations in multi-dimensional vector spaces. The application of the proposed methodology is demonstrated for automatic annotation of segmented objects in chest radiographs.