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Computing the Euclidean Distance Transform on a Linear Array of Processors

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Abstract

Given an n×n binary image of white and black pixels, we present an optimal parallel algorithm for computing the distance transform and the nearest feature transform using the Euclidean metric. The algorithm employs the systolic computation to achieve O(n) running time on a linear array of n processors.

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Authors and Affiliations

  1. Department of Computer Science, University of Calgary, Calgary, Canada

    Marina L. Gavrilova

  2. KFUPM, Department of Information and Computer Science, Dhahran, Saudi Arabia

    Muhammad H. Alsuwaiyel

Authors
  1. Marina L. Gavrilova
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  2. Muhammad H. Alsuwaiyel
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Gavrilova, M.L., Alsuwaiyel, M.H. Computing the Euclidean Distance Transform on a Linear Array of Processors. The Journal of Supercomputing 25, 177–185 (2003). https://doi.org/10.1023/A:1023948712732

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  • DOI: https://doi.org/10.1023/A:1023948712732

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