Genetic algorithms for active contour optimization

被引:0
|
作者
MacEachern, LA [1 ]
Manku, T [1 ]
机构
[1] Univ Waterloo, Dept Elect & Comp Engn, Waterloo, ON N2L 3G1, Canada
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Genetic Algorithm Snakes (GA-Snakes) are introduced as a new method of contour-based segmentation. The new algorithm exhibits several key features: a low order of complexity, the ability to handle arbitrary constraints, operation in discrete space, avoidance of higher-order derivatives, possible parallel computation, low/fixed storage requirements, the ability to handle large search spaces comfortably, and the ability to escape local minima and to handle non-convex search spaces. The resulting algorithmic complexity is of order O(n lambda G), where n is the number of control points for the contour, lambda is the number of individuals per generation, and G is the number of generations considered.
引用
收藏
页码:C229 / C232
页数:4
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