西安石油大学学报（自然科学版）2017，Vol.32Issue(5)：102-106,5.DOI:10.3969/j.issn.1673-064X.2017.05.017
空间加权模糊C均值聚类图像分割算法
Spatial Weighted Fuzzy C-means Clustering Algorithm for Image Segmentation
摘要
Abstract
Fuzzy C-means clustering (FCM) is an unsupervised clustering method,which is widely used in image segmentation.A spatial weighted fuzzy C-means clustering algorithm for image segmentation is proposed in order to overcome the sensitivity of the standard FCM algorithm to noises and other imaging artifacts.Firstly,the local prior probabilities of pixel classification marks are defined are defined according to the fuzzy membership function value of neighborhood pixels,and then those local prior probabilities are incorporated into the objective function of the standard FCM.Simulation experiments show the effectiveness and robustness of the proposed algorithm through both synthetic and real images.关键词
图像分割算法/模糊C均值聚类/空间加权Key words
image segmentation algorithm/fuzzy C-means clustering/spatial weighting分类
信息技术与安全科学引用本文复制引用
李小和,屈展,王魁生,卢胜男..空间加权模糊C均值聚类图像分割算法[J].西安石油大学学报（自然科学版）,2017,32(5):102-106,5.基金项目
国家自然科学基金项目(51674200) （51674200）
西安石油大学青年科技创新基金项目(2013BS021) （2013BS021）
