自适应区间二型直觉模糊聚类算法研究  

Research on Adaptive Interval Type-2 Intuitionistic Fuzzy Clustering Algorithm

作　　者：陈艺蕾 毕杨 CHEN Yi-lei;BI Yang(School of Electronic Engineering,Xi′an Aeronautical Institute,Xi′an 710077,China;School of Communication and Information Engineering,Xi′an University of Posts and Telecommunications,Xi′an 710121,China)

机构地区：[1]西安航空学院电子工程学院,西安710077 [2]西安邮电大学通信与信息工程学院,西安710121

出　　处：《西安航空学院学报》2022年第5期85-90,共6页Journal of Xi’an Aeronautical Institute

摘　　要：针对区间二型模糊聚类算法存在初始聚类中心敏感,提出自适应区间二型直觉模糊聚类算法。该算法首先利用高斯滤波函数对图像的统计直方图做平滑处理,同时设计波峰与聚类中心的对应规则,精准地确定初始聚类中心,然后构造融合直觉模糊信息的目标函数,最后通过类内紧致和类间分离两个方面的信息共同判断聚类效果。将该算法应用于彩色图像分割中,实验结果表明该算法能够有效得到合适的初始聚类中心并取得较好的分割结果。To solve the problem that interval type-2 fuzzy clustering algorithm is sensitive to the selection of initial clustering centers, adaptive interval type-2 intuitionistic fuzzy clustering algorithm is proposed. Firstly, a gaussian filtering function is used to smooth the statistical histograms of images, and a corresponding rule of peaks and clustering centers is designed to determine the initial clustering centers accurately. Then, a novel objective function with intuitionistic fuzzy information is constructed and the algorithm is applied to the color image segmentation. The results show that the algorithm can effectively get the appropriate initial clustering center and obtain better segmentation results.

关 键 词：区间二型模糊聚类 统计直方图 直觉模糊 图像分割 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]