摘要
针对分水岭变换算法对噪声敏感和易于产生过分割的问题,提出了一种基于分水岭变换和模糊C均值聚类(FCM)的图像分割算法。该算法不仅解决了分水岭变换算法的过分割问题,而且同时解决了FCM算法初始值难以确定的不足。实验结果显示,该算法可以快速准确地分割出目标,是一种有效的方法。
A new image segmentation algorithm based on watershed transformation and fuzzy C means clustering is proposed for solving the problems of noise-sensitive and over-segmentation watershed transformation. The algorithm also solves the shortage that the initial value is uncertain in the Fuzzy C-means clustering algorithm. The experimental results show that the algorithm is an effective way to segment the target partition quickly and accurately.
出处
《计算机工程与科学》
CSCD
北大核心
2009年第12期56-57,64,共3页
Computer Engineering & Science
基金
湖南省高等学校科学研究重点资助项目(08A001)
湖南省自然科学基金重点资助项目(07JJ3120)
关键词
分水岭变换
模糊C均值聚类
图像分割
watershed transformation
fuzzy C-means clustering
image segmentation
