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Road extraction based on snakes and sophisticated line extraction / Ivan Laptev (1997)

Public Titre : Road extraction based on snakes and sophisticated line extraction Type de document : Mémoire Auteurs : Ivan Laptev, Auteur Editeur : Stockholm : Royal Institute of Technology Année de publication : 1997 Importance : 67 p. Format : 21 x 30 cm Note générale : bibliography Master of Science, Royal Institute of Technology, Stockholm Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] algorithme snake [Termes IGN] détection de contours [Termes IGN] extraction du réseau routier [Termes IGN] image aérienne [Termes IGN] image satellite [Termes IGN] reconnaissance de formes [Termes IGN] réseau routier [Termes IGN] saillance Résumé : (auteur) The extraction of roads from aerial and satellite images is an important task within cartography and planning of new road networks. The automation of this task is highly motivated by the expected increase of the speed and the precision of extraction. This work considers automatic road extraction from single aerial images of high resolution. It is based on two previously developed approaches: The first one is the differential geometric approach for extraction of linear features; The second - contour extraction based on Active Contour Models, also called snakes. Whereas the first approach is fully-automatic, the second was previously mostly used for semi-automatic tasks which require the control of a human operator. This work combines both techniques and adapt them in the method for fully-automatic road extraction. According to the used strategy, the hypotheses for most salient roads in images of rural scenes are generated and verified first. Then, based on the ends of extracted roads the hypotheses for other roads are stated. The developed snake-based technique for the verification of these hypotheses enables recognition of partially occluded and shadowed roads as well as some roads passing through road crossings. The presented results of the developed approach show that the reliable extraction of roads which images are disturbed by surrounding objects is in many cases possible without the explicit knowledge about these objects. This is a big advantage since the automatic recognition of buildings, vegetation etc., is a very complicated problem by itself. Note de contenu : Introduction 1 - Survey of Related Work 2 - Objectives and Limitations 3 - Theory of Snakes 4 - Road Extraction Loop 5 - Matching of the Road Model 6 - Results Conclusion Numéro de notice : 21689 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Mémoire DEA divers Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90926