计算机工程与应用2019，Vol.55Issue(17)：227-231,5.DOI:10.3778/j.issn.1002-8331.1904-0307
基于改进的直觉模糊核聚类的图像分割方法
Image Segmentation Based on Intuitionistic Fuzzy Kernel c-Means Clustering Algorithms
摘要
Abstract
To handle the uncertainty of noisy image, the image segmentation based on improved intuitionistic fuzzy kernel c-means clustering algorithms is proposed. Firstly, the intuitionistic fuzzy set is used to describe the uncertainty information of noisy image, and the gray values of image are transferred to intuitionistic fuzzy domain. Secondly, fuzzy kernel c-means clustering algorithms are extend to intuitionistic fuzzy kernel c-means clustering algorithms, and the image is clustered in intuitionistic fuzzy domain. Thirdly, the intuitionistic fuzzy factor which Gaussian kernel function and Euclidean distance are used to model the grey level and spatial information of 8-neighbor separately, is added into the object function of intuitionistic fuzzy kernel c-means clustering algorithms. Then, the iterative formulas are deduced by gradient descent methods. At last, experiments executed on one synthetic image and nature image demonstrate the effectiveness and robustness of the proposed method.关键词
直觉模糊集/直觉模糊聚类/图像分割/核方法/模式识别Key words
intuitionistic fuzzy set/intuitionistic fuzzy clustering/image segmentation/kernel method/pattern recognition分类
信息技术与安全科学引用本文复制引用
徐小来,房晓丽..基于改进的直觉模糊核聚类的图像分割方法[J].计算机工程与应用,2019,55(17):227-231,5.基金项目
湖南省教育厅科学研究重点项目(No.18A511). （No.18A511）
