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Mathematical Morphology and its Applications to Image and Signal Processing pp 331–340Cite as

A General Algorithm for Computing Distance Transforms in Linear Time

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Part of the Computational Imaging and Vision book series (CIVI,volume 18)

Abstract

A new general algorithm for computing distance transforms of digital images is presented. The algorithm consists of two phases. Both phases consist of two scans, a forward and a backward scan. The first phase scans the image column-wise, while the second phase scans the image row-wise. Since the computation per row (column) is independent of the computation of other rows (columns), the algorithm can be easily parallelized on shared memory computers. The algorithm can be used for the computation of the exact Euclidean, Manhattan (L 1 norm), and chessboard distance (L ∞ norm) transforms.

Key words

  • Distance Transforms
  • Row-Column Factorization
  • Parallelization

A. Meijster works at the Computing Centre of the University of Groningen.

J.B.T.M. Roerdink and W.H. Hesselink work at the Institute for Mathematics and Computing Science.

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References

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Author information

Authors and Affiliations

  1. University of Groningen, P.O. Box 800, 9700 AV, Groningen, The Netherlands

    A. Meijster, J. B. T. M. Roerdink & W. H. Hesselink

Authors
  1. A. Meijster
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  2. J. B. T. M. Roerdink
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  3. W. H. Hesselink
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Editor information

Editors and Affiliations

  1. Johns Hopkins University, Baltimore

    John Goutsias

  2. Xerox, Palo Alto

    Luc Vincent & Dan S. Bloomberg & 

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© 2002 Kluwer Academic/Plenum Publishers

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Meijster, A., Roerdink, J.B.T.M., Hesselink, W.H. (2002). A General Algorithm for Computing Distance Transforms in Linear Time. In: Goutsias, J., Vincent, L., Bloomberg, D.S. (eds) Mathematical Morphology and its Applications to Image and Signal Processing. Computational Imaging and Vision, vol 18. Springer, Boston, MA. https://doi.org/10.1007/0-306-47025-X_36

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  • DOI: https://doi.org/10.1007/0-306-47025-X_36

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-0-7923-7862-4

  • Online ISBN: 978-0-306-47025-7

  • eBook Packages: Springer Book Archive