• DocumentCode
    1763219
  • Title

    Template-Based Hierarchical Building Extraction

  • Author

    Sellaouti, Aymen ; Hamouda, A. ; Deruyver, Aline ; Wemmert, Cedric

  • Author_Institution
    Lab. of Comput. in Program., Algorithmic & Heuristic, Campus Univ. Tunis, Tunis, Tunisia
  • Volume
    11
  • Issue
    3
  • fYear
    2014
  • fDate
    41699
  • Firstpage
    706
  • Lastpage
    710
  • Abstract
    Automatic building extraction is an important field of research in remote sensing. This letter introduces a new object-based building extraction approach. So far, many object-based algorithms for building extraction have been proposed. However, these algorithms mainly operate in two phases: object construction and building extraction. The majority of these algorithms heavily relies on the object construction process, mainly due to the lack of interaction between the two steps. To overcome these drawbacks, we introduce a new hierarchical approach based on building templates. Carried out experiments on data sets of images from the urban area of Strasbourg show the benefits of our approach.
  • Keywords
    buildings (structures); feature extraction; geophysical image processing; object recognition; remote sensing; automatic building extraction; building template; hierarchical approach; object construction; remote sensing; template based hierarchical building extraction; Buildings; Data mining; Feature extraction; Image resolution; Image segmentation; Remote sensing; Shape; Building; cooperation; dynamic template; object-based;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2013.2276936
  • Filename
    6587110