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Automatic extraction of building statistics from digital orthophotos / A. Stassopoulou in International journal of geographical information science IJGIS, vol 14 n° 8 (december 2000)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 14 n° 8 (december 2000) . - pp 795 - 814 Titre : Automatic extraction of building statistics from digital orthophotos Type de document : Article/Communication Auteurs : A. Stassopoulou, Auteur ; T. Caelli, Auteur ; R. Ramirez, Auteur Année de publication : 2000 Article en page(s) : pp 795 - 814 Note générale : Bibliographie 2 pages Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] bâtiment [Termes IGN] extraction automatique [Termes IGN] orthoimage [Termes IGN] segmentation d'image Résumé : (Auteur) In this paper we discuss uses of image segmentation, feature extraction and Bayesian networks for identifying buildings in digital orthophotos and the utilisation of the results for the automated computation of building statistics. Our work differs from previous attempts in a number of ways. Firstly, image segmentation is accomplished using an adaptive multi-scale method which brings together region and edge information to segment the image into regions. Secondly, automated building feature extraction is optimised to fit with expert human annotation performance. The third aspect of this work is the exploration of Bayesian networks as a method fot fusing available information (ranging from corner information to solar angles as indicators of shadow location) to classify segmented regions as corresponding to buildings or not. Such processes then permit the automatic compilation of building statistics. Numéro de notice : A2000-177 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/136588100750022796 En ligne : https://doi.org/10.1080/136588100750022796 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21593 [article]

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