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Communication Dans Un Congrès Année : 2009

Spatio-temporal multi-modality ontology for indexing and retrieving satellite images

Résumé

This paper presents spatio-temporal multi-modality ontology for indexing and retrieving satellite images in the high level to improve the quality of the system retrieval and to perform semantic in the retrieval process.Our approach is based on three modules: (1) regions and features extraction, (2) ontological indexing and (3) semantic image retrieval. The first module allows extracting regions from the satellite image using the fuzzy c-means FCM) segmentation algorithm. The second module allows indexing the satellite image by a spatio-temporal ontology which represents sensors, spatial objects, visual features (spectral signature, texture, shape, etc.), spatial relation between objects, temporal variation and semantic relation between terms. The last module allows retrieving satellite images by comparing the ontological model f the requested satellite image with the ontological model base. We adopted several algorithms for measuring the lexical and the structural similarity degree between ontological models.Our approach attempts to fully describe the semantic content of the satellite image and to perform the quality of the retrieval system.
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Dates et versions

hal-00954240 , version 1 (03-03-2014)

Identifiants

  • HAL Id : hal-00954240 , version 1

Citer

Wassim Messoudi, Imed Riadh Farah, Karim Saheb Ettabaa, Henda Ben Ghezala, Basel Solaiman. Spatio-temporal multi-modality ontology for indexing and retrieving satellite images. COSI 2009 : colloque sur l'optimisation et les systèmes d'information, May 2009, Annaba, Algeria. 15 p. ⟨hal-00954240⟩
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