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Detection and vectorization of roads from lidar data / S. Clode in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 5 (May 2007)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 73 n° 5 (May 2007) . - pp 517 - 535 Titre : Detection and vectorization of roads from lidar data Type de document : Article/Communication Auteurs : S. Clode, Auteur ; Franz Rottensteiner, Auteur ; P. Kootsookos, Auteur ; E. Zelniker, Auteur Année de publication : 2007 Article en page(s) : pp 517 - 535 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] Australie [Termes IGN] axe médian [Termes IGN] convolution (signal) [Termes IGN] détection automatique [Termes IGN] détection de contours [Termes IGN] données lidar [Termes IGN] extraction du réseau routier [Termes IGN] lasergrammétrie [Termes IGN] milieu urbain [Termes IGN] réseau routier [Termes IGN] semis de points [Termes IGN] vectorisation Résumé : (Auteur) A method for the automatic detection and vectorization of roads from lidar data is presented. To extract roads from a lidar point cloud, a hierarchical classification technique is used to classify the lidar points progressively into road and non-road points. During the classification process, both intensity and height values are initially used. Due to the homogeneous and consistent nature of roads, a local point density is introduced to finalize the classification. The resultant binary classification is then vectorized by convolving a complex-valued disk named the Phase Coded Disk (PCD) with the image to provide three separate pieces of information about the road. The centerline and width of the road are obtained from the resultant magnitude image while the direction is determined from the corresponding phase image, thus completing the vectorized road model. All algorithms used are described and applied to two urban test sites. Completeness values of 0.88 and 0.79 and correctness values of 0.67 and 0.80 were achieved for the classification phase of the process. The vectorization of the classified results yielded RMS values of 1.56 m and 1.66 m, completeness values of 0.84 and 0.81 and correctness values of 0.75 and 0.80 for two different data sets. Copyright ASPRS Numéro de notice : A2007-244 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.73.5.517 En ligne : https://doi.org/10.14358/PERS.73.5.517 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28607 [article]