Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/13703
Title: A split-and-merge technique for automated reconstruction of roof planes
Authors: Khoshelham, K
Li, Z 
King, B 
Issue Date: 2005
Publisher: American Society for Photogrammetry and Remote Sensing
Source: Photogrammetric engineering and remote sensing, 2005, v. 71, no. 7, p. 855-862 How to cite?
Journal: Photogrammetric engineering and remote sensing 
Abstract: Automated reconstruction of buildings from different data sources has been one of the most challenging problems in photogrammetry and computer vision. Systems for automated building reconstruction fail in many cases due to complexities involved in the data including image noise, occlusion, shadow, and low contrast, as well as, low accuracy or density of height data. In this paper, the problem of overgrown and undergrown regions in the segmentation of aerial images is discussed, and a split-and-merge technique is presented to overcome this problem by making use of height data. This technique is based on splitting image regions whose associated height points do not fall in a single plane, and merging coplanar neighboring regions. A robust plane-fitting method is used to fit planar surfaces to height points that are highly contaminated by gross errors. Final roof planes are extracted out of the image planar regions by checking their slope and height over a morphologically opened DSM. An experimental evaluation is conducted, and its results indicate the capability of the proposed technique in splitting overgrown regions, merging undergrown coplanar regions, and selecting the final roof planes. Also, the method is shown to be computationally efficient, and the reconstructed roof planes are of acceptable accuracy.
URI: http://hdl.handle.net/10397/13703
ISSN: 0099-1112
EISSN: 2374-8079
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

26
Last Week
2
Last month
Citations as of Oct 17, 2017

WEB OF SCIENCETM
Citations

22
Last Week
0
Last month
0
Citations as of Oct 17, 2017

Page view(s)

42
Last Week
1
Last month
Checked on Oct 15, 2017

Google ScholarTM

Check



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.