Feature-preserving medial axis noise removal

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

12 Scopus citations


This paper presents a novel technique for medial axis noise removal. The method introduced removes the branches generated by noise on an object’s boundary without losing the fine features that are often altered or destroyed by current pruning methods. The algorithm consists of an intuitive threshold-based pruning process, followed by an automatic feature reconstruction phase that effectively recovers lost details without reintroducing noise. The result is a technique that is robust and easy to use. Tests show that the method works well on a variety of objects with significant differences in shape complexity, topology and noise characteristics.

Original languageEnglish (US)
Title of host publicationComputer Vision - 7th European Conference on Computer Vision, ECCV 2002, Proceedings
EditorsAnders Heyden, Gunnar Sparr, Mads Nielsen, Peter Johansen
PublisherSpringer Verlag
Number of pages15
ISBN (Print)9783540437444
StatePublished - 2003
Externally publishedYes
Event7th European Conference on Computer Vision, ECCV 2002 - Copenhagen, Denmark
Duration: May 28 2002May 31 2002

Publication series

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


Other7th European Conference on Computer Vision, ECCV 2002

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2002.

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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