A study on image segmentation by an improved adaptive algorithm

被引：0
|
作者：
Li, Qing [1 ]
He, Wen-Hao [1 ]
Jiang, Han-Hong [2 ]
Li, Xuan-Zhong [1 ]
机构：
[1] Wuhan Univ Technol, Sch Informat Engn, Wuhan 430070, Peoples R China
[2] Naval Univ Engn, Sch Elect & Informat Engn, Wuhan 430070, Peoples R China
来源：
PROCEEDINGS OF 2007 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2007年
关键词：
image segmentation; improved adaptive genetic algorithm (IAGA); crossover; mutation;
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：
In the first place, an improvement was made on crossover and mutation of adaptive genetic algorithm (AGA) to let the crossover probability and mutation probability adapt nonlinearly. Then a comparison was made between Improved Adaptive Genetic Algorithm (IAGA) and Adaptive Genetic Algorithm (AGA) in segmentation time and adaptive function curve. The results indicated that IAGA can give attention to the main information of experiment images. And much less time was used by the algorithm. The process of searching for global optimum also became more stable than AGA.
引用
收藏
页码：1570 / +
页数：2
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