TY - JOUR
T1 - Scale-space medialness transform based on boundary concordance voting
AU - Xu, Ming
AU - Pycock, David
N1 - Funding Information:
The authors would like to thank The University of Birmingham and the ORS Award Scheme of the Committee of Vice-Chancellors and Principals, UK for the financial support for Ming Xu. We would also like to thank the reviewers of this article for their helpful and stimulating comments.
PY - 1999
Y1 - 1999
N2 - 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 localization 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.
AB - 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 localization 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.
UR - http://www.scopus.com/inward/record.url?scp=0033340959&partnerID=8YFLogxK
U2 - 10.1023/A:1008312821522
DO - 10.1023/A:1008312821522
M3 - Article
AN - SCOPUS:0033340959
SN - 0924-9907
VL - 11
SP - 277
EP - 299
JO - Journal of Mathematical Imaging and Vision
JF - Journal of Mathematical Imaging and Vision
IS - 3
ER -