| 一种基于蚁群算法和C-Means算法的图像分割方法 |
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| 作者单位： | 湖北工业大学计算机学院 湖北武汉430068 |
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| 摘 要： | 针对传统C-Means算法在图像分割应用中的缺陷,本文提出一种蚁群算法(Ant Colony Optimization ACO)融合C-Means算法的图像聚类分割方法,它融合了C-Means算法和蚁群算法的优点,比传统的C-Means算法能得到更好的分割质量。实际图像分割试验结果表明该方法是一种良好的图像分割新方法。
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| 关 键 词： | 蚁群算法 C-Means 图像分割 |
Image Segmentation Based on Hybridization of the Ant Colony Optimization with C-Means Algorithm |
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| Authors: | YE Zhi-wei |
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| Abstract: | This paper presents a new method which combined Ant colony optimization algorithm(ACO) with C-Means in order to improve segmented result produced by C-Means . The new algorithm benefits from the least computation of C-Means and robust optimized power of ACO. Compared to traditional C-Means, the algorithm can achieve better segmented results. Experimental results proves that new algorithm is a promising image segmentation method. |
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| Keywords: | Ant Colony Optimization image segmentation C-Means |
| 本文献已被 CNKI 等数据库收录！ |
