DETERMINATION OF OPTIMAL GENERAL EDGE DETECTORS BY GLOBAL MINIMIZATION OF A COST FUNCTION

被引：10
|
作者：
JALALI, S
BOYCE, JF
机构：
[1] Wheatstone Laboratory, King's College London, The Strand, London
来源：
IMAGE AND VISION COMPUTING | 1995年 / 13卷 / 09期
关键词：
EDGE DETECTION; GLOBAL MINIMIZATION; NUMERICAL OPTIMIZATION;
D O I：
10.1016/0262-8856(95)98863-O
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We present a numerical optimization technique based on genetic algorithms or simulated annealing functional search engines, and use it to optimize linear and nonlinear versions of Canny's performance measure for general edge operators. No prior knowledge of the point-spread-function is assumed. We demonstrate that the results obtained are superior both for an ideal and a real edge to those arrived at by previous researchers.
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页码：683 / 693
页数：11
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