An ADMM-based scheme for distance function approximation

Alexander Belyaev, Pierre-Alain Fayolle

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Abstract

A novel variational problem for approximating the distance function (to a domain boundary) is proposed. It is shown that this problem can be efficiently solved by ADMM. A review of several other variational and PDE-based methods for distance function estimation is presented. Advantages of the proposed distance function estimation method are demonstrated by numerical experiments. Applications of the method to the problems of surface curvature estimation and computing the skeleton of a binary image are shown.
Original languageEnglish
Pages (from-to)1-14
Number of pages14
JournalNumerical Algorithms
Early online date19 Aug 2019
DOIs
Publication statusE-pub ahead of print - 19 Aug 2019

Keywords

  • Curvature
  • Distance function
  • Distance transform
  • Skeleton
  • Variational methods

ASJC Scopus subject areas

  • Applied Mathematics

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