| 基于 PSO的快速模糊 C均值图像分割算法 * |
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| 引用本文： | 李艳灵,李刚. 基于 PSO的快速模糊 C均值图像分割算法 *[J]. 计算机应用研究, 2008, 25(10): 3053-3055 |
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| 作者姓名： | 李艳灵 李刚 |
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| 作者单位： | 1. 华中科技大学,控制科学与工程系,武汉,430074;信阳师范学院,计算机科学系,河南,信阳,464000
2. 信阳师范学院,计算机科学系,河南,信阳,464000 |
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| 基金项目： | 国家自然科学基金资助项目 ( 60574025) ;河南省教育厅自然科学基金资助项目 ( 2008A520021) ;信阳师范学院青年骨干教师计划资助项目 ( 20080619) |
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| 摘 要： | 利用粒子群算法全局性和鲁棒性的特点 ,可以解决模糊 C均值算法 ( FCM)用于图像分割时对初始值敏感、容易陷入局部极小值的问题。但是设定粒子群算法的初始搜索范围依赖于人的经验 ,并且所设范围往往过大,影响算法的执行速度 ,为此提出用收敛速度快的 K均值聚类法得到的聚类中心作为粒子群算法初始搜索范围的参考 ,缩小粒子群算法的搜索范围 ,提高算法执行速度。实验表明该算法具有较高的分割速度和良好的抑制噪声的能力。
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| 关 键 词： | 图像分割 模糊 C均值 K均值算法 粒子群算法 |
Fast fuzzy C-means algorithm for image segmentation based on PSO |
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| LI Yan-ling,LI Gang. Fast fuzzy C-means algorithm for image segmentation based on PSO[J]. Application Research of Computers, 2008, 25(10): 3053-3055 |
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| Authors: | LI Yan-ling LI Gang |
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| Affiliation: | ( 1. Dept. of Control Science & Engineering, Huazhong University of Science & Technology, Wuhan 430074, China; 2 . Dept. of Computer Science, Xinyang Normal University, Xinyang Henan 464000, China) |
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| Abstract: | The fuzzy C-means algorithm is sensitive to noise and always converges to the local infinitesimal value, which is overcome by PSO algorithm with the feature of overall robustness. But the initial searching scope of PSO was selected by hu-man experience, and the selected searching scope was always too big, which influenced the velocity of algorithm. This paper used the clustering centers obtained by K-means algorithm as the reference of the searching scope of PSO algorithm, which re-duced the search scope and improved the velocity of algorithm. The experimental results show that new algorithm can converge more quickly than the standard FCM algorithm and suppress the noise effectively. |
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| Keywords: | image segmentation fuzzy C-means( FCM) K-means algorithm particle swarm optimization( PSO) algorithm |
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