| 基于微分进化的加权模糊C均值图像分割方法 |
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| 引用本文： | 陈育玲,刘秉瀚.基于微分进化的加权模糊C均值图像分割方法[J].福州大学学报(自然科学版),2010,38(1). |
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| 作者姓名： | 陈育玲 刘秉瀚 |
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| 作者单位： | 福州大学数学与计算机科学学院; |
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| 基金项目： | 福建省自然科学基金资助项目(2009J01283;2009J01248);;福建省科技计划重点资助项目(2008H0026) |
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| 摘 要： | 提出基于微分进化和加权模糊C均值的图像分割方法.鉴于加权模糊C均值算法对初始值敏感、容易陷入局部最优的缺点,采用微分进化进行全局寻优,能够找到全局最优的模糊划分;考虑到欧氏距离的局限性,实验中引入特征距离,改善了图像分割效果.实验结果表明,该方法的收敛速度更快、稳定性更好,所获得的适应度值更高.
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| 关 键 词： | 微分进化 加权模糊C均值 特征距离 图像 分割 |
Image segmentation method based on differential evolution and weighted fuzzy C means algorithm |
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| CHEN Yu-ling,LIU Bing-han.Image segmentation method based on differential evolution and weighted fuzzy C means algorithm[J].Journal of Fuzhou University(Natural Science Edition),2010,38(1). |
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| Authors: | CHEN Yu-ling LIU Bing-han |
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| Institution: | College of Mathematics and Computer Science;Fuzhou University;Fuzhou;Fujian 350108;China |
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| Abstract: | With superiorities of differential evolution(DE)and weighted fuzzy C means(WFCM),a new image segmentation method is proposed-image segmentation method based on DE and WFCM.As WFCM is sensitive to initial values and easy to fall into a local optimum,DE is applied for global optimization,so the best globally fuzzy segmentation can be found.Considering the limitation of Euclidian distance,feature distance is applied in the experiment to improve image segmentation.Experiments show that the method has better eff... |
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| Keywords: | differential evolution weighted fuzzy C means feature distance image segmentation |
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