A General Algorithm for Computing Distance Transforms in Linear Time

  • A. Meijster
  • J. B. T. M. Roerdink
  • W. H. Hesselink

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 (L1 norm), and chessboard distance (L norm) transforms.

Key words

Distance Transforms Row-Column Factorization Parallelization 

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Copyright information

© Kluwer Academic/Plenum Publishers 2002

Authors and Affiliations

  • A. Meijster
    • 1
  • J. B. T. M. Roerdink
    • 1
  • W. H. Hesselink
    • 1
  1. 1.University of GroningenGroningenThe Netherlands

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