A symmetric convexity measure

被引：5
|
作者：
Rosin, PL [1 ]
Mumford, CL [1 ]
机构：
[1] Univ Wales Coll Cardiff, Cardiff Sch Comp Sci, Cardiff, S Glam, Wales
来源：
PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 4 | 2004年
关键词：
D O I：
10.1109/ICPR.2004.1333693
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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 symmetric with respect to intrusions and protrusions. The measure requires a maximally overlapping convex polygon, and this is efficiently estimated using a genetic algorithm. Examples of the measures application to medical image analysis are shown.
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页码：11 / 14
页数：4
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