A Split-and-Merge Technique for Automated Reconstruction of Roof Planes

There is an increasing demand for digital building models, which are useful in town planning, telecommunication, tourist information systems, and generation of 3D city models. This article describes a split-and-merge technique for automated reconstruction of roof planes. The authors note that 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 article, the authors describe how the split-and-merge technique makes use of height data to overcome the problem of overgrown and undergrown regions in the segmentation of aerial images. 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. The authors experimental testing of the method shows that it is computationally efficient, and the reconstructed roof planes are of acceptable accuracy.

  • Availability:
  • Authors:
    • Khoshelham, Kourosh
    • Li, Zhilin
    • King, Bruce
  • Publication Date: 2005-7


  • English

Media Info

  • Media Type: Print
  • Features: Figures; References; Tables;
  • Pagination: pp 855-862
  • Serial:

Subject/Index Terms

Filing Info

  • Accession Number: 01002744
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jul 29 2005 7:55AM