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Proceedings Paper

Building extraction using local surface normal angle transformation
Author(s): Y. Li; T. Qian
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Paper Abstract

Building detection and extraction from digital surface model (DSM) becomes more and more attracted when high resolution airborn radar and CCD sensor find their more applications in photogrammetric field. Because DSM contains the terrain heights, we firstly derive DTM from DSM, and then generate Normalized DSM (NDSM). The buildings are extracted from NDSM. However, since urban appearance is complex, with large buildings, small buildings, trees in mass, etc., building extraction is implemented through several stages. Local Surface Normal Angle Transform (LSNAT) is implemented to the height field. Big buildings are distinguished from other large regions generated from binary NDSM. Watershed segmentation is used to detect trees in mass together with LSNAT. Roofs of the small building are extracted based on the histogram of LSNAT. A case study is presented and analyzed in the end of this paper.

Paper Details

Date Published: 1 August 2007
PDF: 12 pages
Proc. SPIE 6751, Geoinformatics 2007: Cartographic Theory and Models, 67511E (1 August 2007); doi: 10.1117/12.760094
Show Author Affiliations
Y. Li, Nanjing Univ. (China)
T. Qian, Nanjing Univ. (China)


Published in SPIE Proceedings Vol. 6751:
Geoinformatics 2007: Cartographic Theory and Models

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