• DocumentCode
    798434
  • Title

    Linear time Euclidean distance transform algorithms

  • Author

    Breu, Heinz ; Gil, Joseph ; Kirkpatrick, David ; Werman, Michael

  • Author_Institution
    Dept. of Comput. Sci., British Columbia Univ., Vancouver, BC, Canada
  • Volume
    17
  • Issue
    5
  • fYear
    1995
  • fDate
    5/1/1995 12:00:00 AM
  • Firstpage
    529
  • Lastpage
    533
  • Abstract
    Two linear time (and hence asymptotically optimal) algorithms for computing the Euclidean distance transform of a two-dimensional binary image are presented. The algorithms are based on the construction and regular sampling of the Voronoi diagram whose sites consist of the unit (feature) pixels in the image. The first algorithm, which is of primarily theoretical interest, constructs the complete Voronoi diagram. The second, more practical, algorithm constructs the Voronoi diagram where it intersects the horizontal lines passing through the image pixel centers. Extensions to higher dimensional images and to other distance functions are also discussed
  • Keywords
    computational geometry; image processing; transforms; Voronoi diagram; asymptotically optimal algorithms; linear time Euclidean distance transform algorithms; regular sampling; two-dimensional binary image; Computer vision; Councils; Euclidean distance; Histograms; Image databases; Indexing; Layout; Lighting; Object recognition; Optimized production technology;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/34.391389
  • Filename
    391389