STREET REGION DETECTION FROM NORMALIZED DIGITAL SURFACE MODEL AND LASER DATA INTENSITY IMAGE
The urban road network extraction process can be simplified by firstly detecting regions corresponding to streets, allowing a substantial reduction of the search area. As a result, the extraction process is benefited in two aspects: the computational complexity and the reliability. This paper aims a...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2013-04-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXVIII-3-W22/197/2011/isprsarchives-XXXVIII-3-W22-197-2011.pdf |
| _version_ | 1811312484737351680 |
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| author | T. S. G. Mendes A. P. Dal Poz |
| author_facet | T. S. G. Mendes A. P. Dal Poz |
| author_sort | T. S. G. Mendes |
| collection | DOAJ |
| description | The urban road network extraction process can be simplified by firstly detecting regions corresponding to streets, allowing a
substantial reduction of the search area. As a result, the extraction process is benefited in two aspects: the computational complexity
and the reliability. This paper aims at detecting street regions using only data obtained by Laser Scanner Systems. A sequence of
standard image processing techniques is used to process height and intensity laser scanner data. A normalized Digital Surface Model
is derived from height laser scanner data, from which regions corresponding to aboveground objects (mainly trees and buildings) are
detected. Next, detected tree regions are eliminated from the aboveground regions, remaining only buildings. Then, morphological
operators are applied in order to obtain elongated street ribbons and homogeneous block regions. Street regions are also detected in
the intensity image. The results obtained from the radiometric and geometric laser scanner data are combined, allowing the
elimination of non-street regions and the improvement of the geometry of region boundaries. The experimental results showed that
the methodology proved to be efficient to detect street regions. |
| first_indexed | 2024-04-13T10:36:58Z |
| format | Article |
| id | doaj.art-6698ec1210c2400a96481cdc1c539171 |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-04-13T10:36:58Z |
| publishDate | 2013-04-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-6698ec1210c2400a96481cdc1c5391712022-12-22T02:50:01ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342013-04-01XXXVIII-3/W2219720210.5194/isprsarchives-XXXVIII-3-W22-197-2011STREET REGION DETECTION FROM NORMALIZED DIGITAL SURFACE MODEL AND LASER DATA INTENSITY IMAGET. S. G. Mendes0A. P. Dal Poz1Cartographic Sciences Graduate Program, UNESP, São Paulo State University, BrazilDepartment of Cartography, UNESP, São Paulo State University, BrazilThe urban road network extraction process can be simplified by firstly detecting regions corresponding to streets, allowing a substantial reduction of the search area. As a result, the extraction process is benefited in two aspects: the computational complexity and the reliability. This paper aims at detecting street regions using only data obtained by Laser Scanner Systems. A sequence of standard image processing techniques is used to process height and intensity laser scanner data. A normalized Digital Surface Model is derived from height laser scanner data, from which regions corresponding to aboveground objects (mainly trees and buildings) are detected. Next, detected tree regions are eliminated from the aboveground regions, remaining only buildings. Then, morphological operators are applied in order to obtain elongated street ribbons and homogeneous block regions. Street regions are also detected in the intensity image. The results obtained from the radiometric and geometric laser scanner data are combined, allowing the elimination of non-street regions and the improvement of the geometry of region boundaries. The experimental results showed that the methodology proved to be efficient to detect street regions.http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXVIII-3-W22/197/2011/isprsarchives-XXXVIII-3-W22-197-2011.pdf |
| spellingShingle | T. S. G. Mendes A. P. Dal Poz STREET REGION DETECTION FROM NORMALIZED DIGITAL SURFACE MODEL AND LASER DATA INTENSITY IMAGE The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | STREET REGION DETECTION FROM NORMALIZED DIGITAL SURFACE MODEL AND LASER DATA INTENSITY IMAGE |
| title_full | STREET REGION DETECTION FROM NORMALIZED DIGITAL SURFACE MODEL AND LASER DATA INTENSITY IMAGE |
| title_fullStr | STREET REGION DETECTION FROM NORMALIZED DIGITAL SURFACE MODEL AND LASER DATA INTENSITY IMAGE |
| title_full_unstemmed | STREET REGION DETECTION FROM NORMALIZED DIGITAL SURFACE MODEL AND LASER DATA INTENSITY IMAGE |
| title_short | STREET REGION DETECTION FROM NORMALIZED DIGITAL SURFACE MODEL AND LASER DATA INTENSITY IMAGE |
| title_sort | street region detection from normalized digital surface model and laser data intensity image |
| url | http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXVIII-3-W22/197/2011/isprsarchives-XXXVIII-3-W22-197-2011.pdf |
| work_keys_str_mv | AT tsgmendes streetregiondetectionfromnormalizeddigitalsurfacemodelandlaserdataintensityimage AT apdalpoz streetregiondetectionfromnormalizeddigitalsurfacemodelandlaserdataintensityimage |