A scale-space medialness transform based on boundary concordance voting

Ming Xu, David Pycock

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)
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Abstract

The Concordance-based Medial Axis Transform (CMAT) presented in this paper is a multiscale medial axis (MMA) algorithm that computes the medial response from grey-level boundary measures. This non-linear operator responds only to symmetric structures, overcoming the limitations of linear medial operators which create ?side-lobe? responses for symmetric structures and respond to edge structures. In addition, the spatial localisation of the medial axis and the identification of object width is improved in the CMAT algorithm compared with linear algorithms. The robustness of linear medial operators to noise is preserved in our algorithm. The effectiveness of the CMAT is accredited to the concordance property described in this paper. We demonstrate the performance of this method with test figures used by other authors and medical images that are relatively complex in structure. In these complex images the benefit of the improved response of our non-linear operator is clearly visible.
Original languageEnglish
Pages (from-to)277-299
Number of pages23
JournalJournal of Mathematical Imaging and Vision
Volume11
Issue number3
DOIs
Publication statusPublished - 1 Dec 1999

Keywords

  • image analysis, medial axis, multiscale, shape representation

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