计算机应用与软件2025，Vol.42Issue(5)：198-202,216,6.DOI:10.3969/j.issn.1000-386x.2025.05.027
基于空间邻域复杂度和直觉模糊集的FCM图像分割算法
FCM IMAGE SEGMENTATION ALGORITHM BASED ON SPATIAL NEIGHBORHOOD COMPLEXITY AND INTUITIONISTIC FUZZY SET
摘要
Abstract
Fuzzy C-means(FCM)algorithm only considers the gray information of pixels and ignores the neighborhood information of pixels,resulting in inaccurate segmentation results.To solve this problem,considering the distribution characteristics and interaction between image pixels,this paper designs a complexity to increase the weight of pixel spatial neighborhood information in the algorithm.This complexity information was integrated into FCM algorithm.Combined with intuitionistic fuzzy set theory,hesitation degree and non-membership degree were introduced to improve the uncertain information in the image and optimize the membership matrix.Experimental results show that the algorithm weakens the influence of noise on the image and has stronger robustness to the processing of edge details.关键词
像素相似性/复杂度/直觉模糊集/模糊C均值Key words
Pixel similarity/Complexity/Intuitionistic fuzzy sets/Fuzzy C-means分类
计算机与自动化引用本文复制引用
韩玉兰,曹晓峰,徐寒..基于空间邻域复杂度和直觉模糊集的FCM图像分割算法[J].计算机应用与软件,2025,42(5):198-202,216,6.基金项目
宁夏自然科学基金项目(2024AAC03039) （2024AAC03039）
国家自然科学基金项目(81863030). （81863030）
