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Received:September 12, 2012 Revised:October 29, 2012
Received:September 12, 2012 Revised:October 29, 2012
中文摘要: 提出一种基于K-Means聚类的人工鱼群算法, 该算法利用人工鱼群算法鲁棒性较强且不易陷入局部最优值的特点, 动态的确定了聚类的数目和中心, 解决了K-Means聚类初始点选择不稳定的缺陷, 在此两种算法融合的基础上进行图像分割处理, 经试验证明该算法效果理想.
中文关键词: 图像分割技术 K-Means聚类算法 人工鱼群算法
Abstract:The paper presents an artificial fish swarm algorithm based on K-Means clustering. The algorithm uses the feature of having artificial fish swarm algorithm's strong robustness and being not easy to fall into local optimum value, and hence dynamically determines the number of clusters and center, overcoming the defects of K-Means clustering initial point selected unstable. The image segmentation is processed based on the fusion of two algorithms. The test proves the algorithm is ideal.
文章编号： 中图分类号： 文献标志码：
基金项目:
| Author Name | Affiliation |
| CHU Xiao-Li | Guangdong AIB Polytechnic College, Guangzhou 510507, China |
| Author Name | Affiliation |
| CHU Xiao-Li | Guangdong AIB Polytechnic College, Guangzhou 510507, China |
引用文本：
楚晓丽.K-Means聚类算法和人工鱼群算法应用于图像分割技术.计算机系统应用,2013,22(4):92-94,103
CHU Xiao-Li.K-Means Clustering Algorithm and Artificial Fish Swarm Algorithm Applied in Image Segmentation Technology.COMPUTER SYSTEMS APPLICATIONS,2013,22(4):92-94,103
楚晓丽.K-Means聚类算法和人工鱼群算法应用于图像分割技术.计算机系统应用,2013,22(4):92-94,103
CHU Xiao-Li.K-Means Clustering Algorithm and Artificial Fish Swarm Algorithm Applied in Image Segmentation Technology.COMPUTER SYSTEMS APPLICATIONS,2013,22(4):92-94,103
