Automatic road network extraction in suburban areas from high resolution aerial images

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dc.identifier.uri http://dx.doi.org/10.15488/1123
dc.identifier.uri http://www.repo.uni-hannover.de/handle/123456789/1147
dc.contributor.author Grote, Anne
dc.contributor.author Rottensteiner, Franz
dc.date.accessioned 2017-02-03T11:49:08Z
dc.date.available 2017-02-03T11:49:08Z
dc.date.issued 2010
dc.identifier.citation Grote, Anne; Rottensteiner, Franz: Automatic road network extraction in suburban areas from high resolution aerial images. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences: [PCV 2010 - Photogrammetric Computer Vision And Image Analysis, Pt I] 38 (2010), Nr. Part 3A, S. 299-304
dc.description.abstract In this paper a road network extraction algorithm for suburban areas is presented. The algorithm uses colour infrared (CIR) images and digital surface models (DSM). The CIR data allow a good separation between vegetation and roads. The image is first segmented in two steps: an initial segmentation using the normalized cuts algorithm and a subsequent grouping of the segments. Road parts are extracted from the segments and then first connected locally to form subgraphs, because roads are often not extracted as a whole due to disturbances in their appearance. Subgraphs can contain several branches, which are resolved by a subsequent optimisation. The optimisation uses criteria describing the relations between the road parts as well as context objects such as trees, vehicles and buildings. The resulting road strings, represented by their centre lines, are then connected to a road network by searching for junctions at the ends of the roads. Small isolated roads are eliminated because they are likely to be false extractions. Results are presented for three image subsets coming from two different data sets, and a quantitative analysis of the completeness and correctness is shown from nine image subsets from the two data sets. The results show that the approach is suitable for the extraction of roads in suburban areas from aerial images. eng
dc.language.iso eng
dc.publisher Göttingen : Copernicus GmbH
dc.relation.ispartof ISPRS-Technical-Commission III Symposium on Photogrammetric Computer Vision and Image Analysis (PCV), September 01-03, 2010, Saint Mande, France
dc.relation.ispartofseries International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences: [PCV 2010 - Photogrammetric Computer Vision And Image Analysis, Pt I] 38 (2010), Nr. Part 3A
dc.rights CC BY 3.0
dc.rights.uri https://creativecommons.org/licenses/by/3.0/
dc.subject Road extraction eng
dc.subject Urban eng
dc.subject High resolution eng
dc.subject Aerial eng
dc.subject Automation eng
dc.subject databases eng
dc.subject.ddc 550 | Geowissenschaften ger
dc.title Automatic road network extraction in suburban areas from high resolution aerial images
dc.type article
dc.type conferenceObject
dc.type Text
dc.relation.issn 2194-9034
dc.bibliographicCitation.issue Part 3A
dc.bibliographicCitation.volume 38
dc.bibliographicCitation.firstPage 299
dc.bibliographicCitation.lastPage 304
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


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