Computing the nearest neighbor transform exactly with only double precision

David L. Millman, Steven Love, Timothy M. Chan, Jack Snoeyink

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The nearest neighbor transform of a binary image assigns to each pixel the index of the nearest black pixel - it is the discrete analog of the Voronoi diagram. Implementations that compute the transform use numerical calculations to perform geometric tests, so they may produce erroneous results if the calculations require more arithmetic precision than is available. Liotta, Preparata, and Tamassia, in 1999, suggested designing algorithms that not only minimize time and space resources, but also arithmetic precision. A simple algorithm using double precision can compute the nearest neighbor transform: compare the squared distances of each pixel to all black pixels, but this is inefficient when many pixels are black. We develop and implement efficient algorithms, computing the nearest neighbor transform of an image in linear time with respect to the number of pixels, while still using only double precision.

Original languageEnglish (US)
Title of host publicationProceedings of the 2012 9th International Symposium on Voronoi Diagrams in Science and Engineering, ISVD 2012
Pages66-74
Number of pages9
DOIs
StatePublished - Oct 3 2012
Externally publishedYes
Event2012 9th International Symposium on Voronoi Diagrams in Science and Engineering, ISVD 2012 - Piscataway, NJ, United States
Duration: Jun 27 2012Jun 29 2012

Publication series

NameProceedings of the 2012 9th International Symposium on Voronoi Diagrams in Science and Engineering, ISVD 2012

Other

Other2012 9th International Symposium on Voronoi Diagrams in Science and Engineering, ISVD 2012
Country/TerritoryUnited States
CityPiscataway, NJ
Period6/27/126/29/12

Keywords

  • Arithmetic precision
  • Computational geometry
  • Degree-driven analysis of algorithms
  • Distance transform
  • Image processing

ASJC Scopus subject areas

  • Geometry and Topology

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