A single-step 2D thinning scheme with deletion of P-simple points

K. Palágyi, Péter Kardos

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

1 Citation (Scopus)

Abstract

Thinning is a frequently applied technique for producing skeletons from digital binary pictures in a topology-preserving way. Bertrand proposed a two-step thinning scheme that is based on P-simple points. In this paper, we give two sufficient conditions for topology-preserving reductions working on the three possible 2D regular grids. The new conditions combined with parallel thinning strategies and geometrical constraints yield a single-step thinning scheme that deletes solely P-simple points.

Original languageEnglish
Title of host publicationProgress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 22nd Iberoamerican Congress, CIARP 2017, Proceedings
PublisherSpringer Verlag
Pages475-482
Number of pages8
ISBN (Print)9783319751924
DOIs
Publication statusPublished - Jan 1 2018
Event22nd Iberoamerican Congress on Pattern Recognition, CIARP 2017 - Valparaiso, Chile
Duration: Nov 7 2017Nov 10 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10657 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other22nd Iberoamerican Congress on Pattern Recognition, CIARP 2017
CountryChile
CityValparaiso
Period11/7/1711/10/17

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Keywords

  • Digital topology
  • P-simple points
  • Regular 2D grids
  • Shape analysis
  • Topology preservation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Palágyi, K., & Kardos, P. (2018). A single-step 2D thinning scheme with deletion of P-simple points. In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 22nd Iberoamerican Congress, CIARP 2017, Proceedings (pp. 475-482). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10657 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-75193-1_57