Multiscale medial response of grey-level images

Ming Xu; David Pycock

doi:10.5244/C.12.23

Multiscale medial response of grey-level images

Ming Xu, David Pycock

University of Birmingham

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

Abstract

The Concordance-based Medial Axis Transform (CMAT) presented in this paper is a multiscale medial axis (MMA) algorithm that computes medial evidence from grey-level boundary measures. It differs from previous algorithms of this type in considering the symmetry of both boundary position and strength. The resultant MMA transform is not prone to the generation of spurious medial responses exhibited by previous algorithms, but accurately estimates the position of the medial axis across scale. In addition, the medial axis and object scale are more distinctly identified. Thus CMAT medialness responses are easier to interpret than responses from previously reported measures. This is illustrated using a test figure and a radiograph of a hand.

Original language	English
Title of host publication	Proceedings - British Machine Vision Conference (BMVC’98)
Editors	Mark Nixon, John Carter
Place of Publication	Southampton
Publisher	British Machine Vision Association
Pages	224-234
ISBN (Electronic)	1-901725-05-7
ISBN (Print)	1-901725-04-9
DOIs	https://doi.org/10.5244/C.12.23
Publication status	Published - 1998
Externally published	Yes

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https://bmva-archive.org.uk/bmvc/1998/pdf/p090.pdf

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title = "Multiscale medial response of grey-level images",

abstract = "The Concordance-based Medial Axis Transform (CMAT) presented in this paper is a multiscale medial axis (MMA) algorithm that computes medial evidence from grey-level boundary measures. It differs from previous algorithms of this type in considering the symmetry of both boundary position and strength. The resultant MMA transform is not prone to the generation of spurious medial responses exhibited by previous algorithms, but accurately estimates the position of the medial axis across scale. In addition, the medial axis and object scale are more distinctly identified. Thus CMAT medialness responses are easier to interpret than responses from previously reported measures. This is illustrated using a test figure and a radiograph of a hand.",

author = "Ming Xu and David Pycock",

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language = "English",

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AU - Xu, Ming

AU - Pycock, David

PY - 1998

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N2 - The Concordance-based Medial Axis Transform (CMAT) presented in this paper is a multiscale medial axis (MMA) algorithm that computes medial evidence from grey-level boundary measures. It differs from previous algorithms of this type in considering the symmetry of both boundary position and strength. The resultant MMA transform is not prone to the generation of spurious medial responses exhibited by previous algorithms, but accurately estimates the position of the medial axis across scale. In addition, the medial axis and object scale are more distinctly identified. Thus CMAT medialness responses are easier to interpret than responses from previously reported measures. This is illustrated using a test figure and a radiograph of a hand.

AB - The Concordance-based Medial Axis Transform (CMAT) presented in this paper is a multiscale medial axis (MMA) algorithm that computes medial evidence from grey-level boundary measures. It differs from previous algorithms of this type in considering the symmetry of both boundary position and strength. The resultant MMA transform is not prone to the generation of spurious medial responses exhibited by previous algorithms, but accurately estimates the position of the medial axis across scale. In addition, the medial axis and object scale are more distinctly identified. Thus CMAT medialness responses are easier to interpret than responses from previously reported measures. This is illustrated using a test figure and a radiograph of a hand.

U2 - 10.5244/C.12.23

DO - 10.5244/C.12.23

M3 - Conference Proceeding

SN - 1-901725-04-9

SP - 224

EP - 234

BT - Proceedings - British Machine Vision Conference (BMVC’98)

A2 - Nixon, Mark

A2 - Carter, John

PB - British Machine Vision Association

CY - Southampton

ER -

Multiscale medial response of grey-level images

Abstract

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