摘要
针对图像分割特征具有交叉重叠现象、其类属的划分存在不确定性的分割问题,模糊聚类分割算法具有较强的优势,但其速度慢且容易陷入局部最优以及对初始值的设置敏感等问题.根据粒子群优化算法具有全局寻优能力,同时还具有较强的局部寻优能力,能更快收敛于最优解的特点,提出了一种基于粒子群的模糊聚类分割算法.实验证明,该算法相比传统的模糊聚类分割算法,具有更快的收敛速度和更高的分割精度.
The fuzzy clustering segmentation algorithm gains an advantage over others when it comes to the phenomena of crossing and overlapping in segmentation characters and the problems of the uncertain division on the types,while it easily plunges into the local optimization and is sensitive to the initial values with low speed.On the basis that particle swarm optimization algorithm（PSO）is of the whole optimization and quite good local optimization with higher speed to converge to the optimization,this paper advanced a fuzzy clustering segmentation algorithm based on particle swarm.The results proved that the algorithm is of higher convergence speed and more accurate segmentation precision.
出处
《福州大学学报（自然科学版）》
CAS
CSCD
北大核心
2010年第1期32-35,共4页
Journal of Fuzhou University(Natural Science Edition)
基金
福建省自然科学基金资助项目(A0710008)
关键词
图像分割
模糊聚类
粒子群优化
算法
image segmentation
fuzzy clustering
particle swarm optimization
algorithm
