计算机应用与软件2017，Vol.34Issue(4)：221-225,333,6.DOI:10.3969/j.issn.1000-386x.2017.04.037
结合空间邻域信息的核FCM图像分割算法
KERNEL FCM IMAGE SEGMENTATION ALGORITHM BASED ON SPATIAL NEIGHBORING INFORMATION
摘要
Abstract
Aiming at the noise sensitive problem of traditional FCM clustering algorithm in image segmentation, a kernel FCM image segmentation algorithm based on spatial neighborhood information is proposed.The algorithm adds the spatial constraint function to the objective function of FCM algorithm and introduces the local membership function which considers the neighborhood information, and then the kernel function is introduced and the original Euclidean distance is replaced by the kernel-induced distance to optimize the features of the segmented image.Finally, by combining the global membership function and the local membership function, a new weighted membership function is obtained, and the image segmentation is realized.Through the segmentation experiments of synthetic images and natural images, the results show that the proposed algorithm is superior to standard FCM and KFCM algorithm in segmentation quality and effectiveness, and is more robust to noise.关键词
模糊C均值聚类/邻域信息/图像分割/核函数/鲁棒性Key words
Fuzzy C-means (FCM)/Neighbor information/Image segmentation/Kernel function/Robustness分类
信息技术与安全科学引用本文复制引用
宗永胜,胡晓辉,屈应照..结合空间邻域信息的核FCM图像分割算法[J].计算机应用与软件,2017,34(4):221-225,333,6.基金项目
国家自然科学基金项目(61163009) （61163009）
甘肃省科技支撑计划项目(144NKCA040). （144NKCA040）
