• DocumentCode
    2507257
  • Title

    Automatic Building Detection in Aerial Images Using a Hierarchical Feature Based Image Segmentation

  • Author

    Izadi, Mohammad ; Saeedi, Parvaneh

  • Author_Institution
    Sch. of Eng. Sci., Simon Fraser Univ., Burnaby, BC, Canada
  • fYear
    2010
  • fDate
    23-26 Aug. 2010
  • Firstpage
    472
  • Lastpage
    475
  • Abstract
    This paper introduces a novel automatic building detection method for aerial images. The proposed method incorporates a hierarchical multilayer feature based image segmentation technique using color. A number of geometrical/regional attributes are defined to identify potential regions in multiple layers of segmented images. A tree-based mechanism is utilized to inspect segmented regions using their spatial relationships with each other and their regional/geometrical characteristics. This process allows the creation of a set of candidate regions that are validated as rooftops based on the overlap between existing and predicted shadows of each region according to the image acquisition information. Experimental results show an overall shape accuracy and completeness of 96%.
  • Keywords
    feature extraction; image colour analysis; image segmentation; object detection; trees (mathematics); aerial images; automatic building detection; geometrical attributes; hierarchical multilayer feature; image acquisition information; image color; image segmentation; regional attributes; rooftops; spatial relationship; tree-based mechanism; Accuracy; Buildings; Feature extraction; Image segmentation; Pixel; Satellites; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2010 20th International Conference on
  • Conference_Location
    Istanbul
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4244-7542-1
  • Type

    conf

  • DOI
    10.1109/ICPR.2010.123
  • Filename
    5597414