Computing the Euclidean Distance Transform on a Linear Array of Processors

  • Authors:
  • Marina L. Gavrilova;Muhammad H. Alsuwaiyel

  • Affiliations:
  • Department of Computer Science, University of Calgary, Calgary, Canada marina@cpsc.ucalgary.ca;Department of Information and Computer Science, KFUPM, Dhahran, Saudi Arabia suwaiyel@ccse.kfupm.edu.sa

  • Venue:
  • The Journal of Supercomputing
  • Year:
  • 2003

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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.