Feature-preserving medial axis noise removal

Roger Tam; Wolfgang Heidrich

doi:10.1007/3-540-47967-8_45

Feature-preserving medial axis noise removal

Roger Tam, Wolfgang Heidrich

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

12 Scopus citations

Abstract

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 language	English (US)
Title of host publication	Computer Vision - 7th European Conference on Computer Vision, ECCV 2002, Proceedings
Editors	Anders Heyden, Gunnar Sparr, Mads Nielsen, Peter Johansen
Publisher	Springer Verlag
Pages	672-686
Number of pages	15
ISBN (Print)	9783540437444
DOIs	https://doi.org/10.1007/3-540-47967-8_45
State	Published - 2003
Externally published	Yes
Event	7th European Conference on Computer Vision, ECCV 2002 - Copenhagen, Denmark Duration: May 28 2002 → May 31 2002

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2351
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	7th European Conference on Computer Vision, ECCV 2002
Country/Territory	Denmark
City	Copenhagen
Period	05/28/02 → 05/31/02

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2002.

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/3-540-47967-8_45

Cite this

Tam, R., & Heidrich, W. (2003). Feature-preserving medial axis noise removal. In A. Heyden, G. Sparr, M. Nielsen, & P. Johansen (Eds.), Computer Vision - 7th European Conference on Computer Vision, ECCV 2002, Proceedings (pp. 672-686). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2351). Springer Verlag. https://doi.org/10.1007/3-540-47967-8_45

Tam, Roger ; Heidrich, Wolfgang. / Feature-preserving medial axis noise removal. Computer Vision - 7th European Conference on Computer Vision, ECCV 2002, Proceedings. editor / Anders Heyden ; Gunnar Sparr ; Mads Nielsen ; Peter Johansen. Springer Verlag, 2003. pp. 672-686 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Tam, R & Heidrich, W 2003, Feature-preserving medial axis noise removal. in A Heyden, G Sparr, M Nielsen & P Johansen (eds), Computer Vision - 7th European Conference on Computer Vision, ECCV 2002, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2351, Springer Verlag, pp. 672-686, 7th European Conference on Computer Vision, ECCV 2002, Copenhagen, Denmark, 05/28/02. https://doi.org/10.1007/3-540-47967-8_45

Feature-preserving medial axis noise removal. / Tam, Roger; Heidrich, Wolfgang.
Computer Vision - 7th European Conference on Computer Vision, ECCV 2002, Proceedings. ed. / Anders Heyden; Gunnar Sparr; Mads Nielsen; Peter Johansen. Springer Verlag, 2003. p. 672-686 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2351).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N1 - Publisher Copyright: © Springer-Verlag Berlin Heidelberg 2002.

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N2 - 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.

AB - 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.

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DO - 10.1007/3-540-47967-8_45

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AN - SCOPUS:84949032973

SN - 9783540437444

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Computer Vision - 7th European Conference on Computer Vision, ECCV 2002, Proceedings

A2 - Heyden, Anders

A2 - Sparr, Gunnar

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Tam R, Heidrich W. Feature-preserving medial axis noise removal. In Heyden A, Sparr G, Nielsen M, Johansen P, editors, Computer Vision - 7th European Conference on Computer Vision, ECCV 2002, Proceedings. Springer Verlag. 2003. p. 672-686. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/3-540-47967-8_45

Feature-preserving medial axis noise removal

Abstract

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Bibliographical note

ASJC Scopus subject areas

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