Genetic Algorithm Combined with Mutual Information for Image Segmentation

被引：2
|
作者：
Shi, Dejia [1 ,2 ]
Liu, Zhiqiang [2 ]
He, Jing [1 ]
机构：
[1] Hunan Univ Commerce, Sch Comp & Elect Engn, Changsha 410205, Hunan, Peoples R China
[2] Hunan Renhua Technol Co Ltd, Changsha 410205, Hunan, Peoples R China
来源：
PROGRESS IN MEASUREMENT AND TESTING, PTS 1 AND 2 | 2010年 / 108-111卷
关键词：
Image Segmentation; Mutual Information; Genetic Algorithm; REGISTRATION;
D O I：
10.4028/www.scientific.net/AMR.108-111.1193
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In order to automatically determine the optimal threshold in image segmentation, this paper presented a new method of image segmentation based on improved genetic algorithm combined with mutual information; it used this improved genetic algorithm to globally optimize infrared image segmentation functions. This method could automatically adjust the parameters of genetic algorithm according to the fitness values of individuals and the decentralizing degree of individuals of the population, and kept the variety of population for rapidly converging to get the optimal thresholds in image segmentation, it overcame the shortcomings including worse convergent speed, easy to premature that exist in traditional genetic algorithm etc.
引用
收藏
页码：1193 / +
页数：2
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