基于HSI空间和K-means方法的彩色图像分割算法  

A Kind of Color Image Segmentation Algorithm Based on HSI Space and K-means Method

作　　者：李丹丹[1] 史秀璋[1] 

机构地区：[1]北京城市学院,北京100083

出　　处：《微电子学与计算机》2010年第7期121-124,共4页Microelectronics & Computer

摘　　要：提出了一种新的彩色图像聚类分割算法,选用HSI空间作为彩色分割空间,在研究H分量的聚类算法中,该分量的圆循环特性被充分的考虑,同时也定义了H分量空间中两点距离的定义和中心的概念;选用最重要的H分量和I分量作为分割聚类特征,运用模糊隶属度刻画了该聚类特征,最后运用K-means算法对彩色图像进行聚类分割.实验结果表明,此算法能够准确地从彩色图像中提取目标区域,且在H分量和I分量上联合分割的结果好于在单个分量上分割的结果.A kind of clustering algorithm for color image segmentation is proposed,choosing HSI representation as the color segmentation space,in the study of H component,the circulation characteristics were full consideration,also the distance of two points and centers of H component is defined. Choosing the most important component of H and I component as segmentation clustering features,using fuzzy membership function depicts the clustering features,at last K-means clustering algorithm is used to segment color image. An experiments is given on bone regional segmentation,and achieve good segmentation results,experimental results shows that the results of the H and I components is superior to the results on a single component of HIS space.

关 键 词：HSI K-MEANS H分量 聚类算法 模糊隶属度 彩色图像 

分 类 号：TP31[自动化与计算机技术—计算机软件与理论]