华中科技大学学报（自然科学版）2017，Vol.45Issue(9)：39-45,7.DOI:10.13245/j.hust.170908
基于多层次聚类的纹理图像分割算法
Texture image segmentation based on multi-level clustering
摘要
Abstract
A method based on multi-level clustering was proposed for saving the space and computa-tion and reducing the sensitivity of the parameters.This algorithm consists of three phases,which were coarsening,representative data clustering and exact partition.First,affinity propagation (AP) algorithm was used for coarsening.Specifically,in order to save the space and computational cost,on-ly the similarity between each point and its t nearest neighbors were computed,and a condensed simi-larity matrix was obtained.Second,to further improve the efficiency and effectiveness of the proposed algorithm,the find of density peaks (FDP)clustering was used to the resulted points (the representa-tive points gotten in the first phase)to do the representative data clustering.Third,the classes of all data were obtained by merging the results of the first two steps.As a result,the proposed algorithm can realize the clusters quickly and precisely for texture image segmentation.The experimental results show that the proposed algorithm is more efficient than the compared algorithms FCM (fuzzy C-means),K-means and SOM (self-organizing maps).关键词
图像分割/特征提取/灰度直方图/亲和传播算法/密度峰值算法Key words
texture image segmentation/feature extraction/gray level histogram/affinity propaga-tion algorithm/find of density peaks (FDP)algorithm分类
信息技术与安全科学引用本文复制引用
杜辉,王宇平,钟俊坤,任楚楚..基于多层次聚类的纹理图像分割算法[J].华中科技大学学报（自然科学版）,2017,45(9):39-45,7.基金项目
国家自然科学基金资助项目 (61272119,61402350,61662068). （61272119,61402350,61662068）
