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Alternative TitleAdvanced Genetic Algorithm Based Two-dimensional Fuzzy Entropy Image Segmentation Algorithm
王建军; 刘波; 北京8701信箱
Source Publication科技导报
Keyword图像处理 图像分割 二维模糊熵 遗传算法
Other AbstractImage segmentation serves the basis of image analysis. In the application area, because segmented images are always involved with great variability and noise, one-dimensional histogram based classical image segmentation methods are not often adequate in some situations. Recently, the two-dimensional histogram based two-dimensional image segmentation methods has gradually become a focus of the image segmentation. Since the basic genetic algorithm based two-dimensional fuzzy entropy image segmentation algorithms has not been well developed, this paper proposes an advanced genetic algorithm. Through using the fitness maximum space, the proposed algorithm establishes a fuzzy evaluation mechanism in the evolution process. Comparing with the classic genetic algorithm,the proposed genetic algorithm remarkably enhances the algorithm's convergence faculty and the whole search ability, in estimating the chromosomes, the algorithm also enhances rationality and objectivity. Experiment result shows that the proposed algorithm remarkably improves the two-dimensional fuzzy entropy image segmentation algorithm's executing speed. Also comparing with the classic genetic algorithm based the two-dimensional fuzzy entropy image segmentation algorithm, although a little more time is spent, the proposed algorithm's acquired image segmentation effect is better.
Funding Project中国科学院空间科学与应用研究中心
Document Type期刊论文
Corresponding Author北京8701信箱
Recommended Citation
GB/T 7714
王建军,刘波,北京8701信箱. 基于改进遗传算法的二维模糊熵图像分割算法[J]. 科技导报,2010,28(20):43-47.
APA 王建军,刘波,&北京8701信箱.(2010).基于改进遗传算法的二维模糊熵图像分割算法.科技导报,28(20),43-47.
MLA 王建军,et al."基于改进遗传算法的二维模糊熵图像分割算法".科技导报 28.20(2010):43-47.
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