A symmetric convexity measure

Rosin, Paul L. ORCID: https://orcid.org/0000-0002-4965-3884 and Mumford, Christine Lesley ORCID: https://orcid.org/0000-0002-4514-0272 2006. A symmetric convexity measure. Computer Vision and Image Understanding 103 (2) , pp. 101-111. 10.1016/j.cviu.2006.04.002

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Abstract

A new area-based convexity measure for polygons is described. It has the desirable properties that it is not sensitive to small boundary defects, and it is more symmetric with respect to intrusions and protrusions than other published convexity measures. The measure requires a maximally overlapping convex polygon, and this is efficiently estimated using a genetic algorithm (GA1). A second genetic algorithm (GA2) is then used to fine tune the result. In addition, the convex polygon is used to generate other values, measuring the amount of protrusions and intrusions that a polygon contains. Furthermore, the scheme can be modified to find the convex skull, which yields another new convexity measure. Examples of the measures' application to medical image analysis are shown.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Publisher:	Elsevier
ISSN:	1077-3142
Last Modified:	06 Nov 2022 14:25
URI:	https://orca.cardiff.ac.uk/id/eprint/29462

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