基于改进KFCM聚类的图像分割算法  

An Improved Image Segmentation Algorithm Based on KFCM-clustering

作　　者：汪彦[1,2] 杨格兰[1] 何建新[1] 

机构地区：[1]湖南城市学院信息科学与工程学院,湖南益阳413000 [2]中南大学软件学院,长沙410083

出　　处：《控制工程》2016年第11期1857-1860,共4页Control Engineering of China

基　　金：湖南省教育厅科研项目(12C0572);湖南省科技厅科研项目(2014FJ4252)

摘　　要：传统图像分割方法大都存在过度分割、分割速度低下等缺点。针对上述问题,提出一种新的彩色图像区域分割算法。这种方法首先将图像转化至L*a*b*空间,并划分子块,结合harr小波变换,抽取图像子块的颜色、纹理和位置特征组成特征数据后,利用改进的Mean-shift算法产生类别数目和初始聚类中心,最终采用改进的KFCM聚类算法,从而实现图像的区域分割。实验表明,该算法能快速分割彩色图像成区域,同时,分割结果理想。Traditional image segmentation methods often have some disadvantages, such as the over segmentation, the lower segmentation speed etc. In order to solve the above problems, a new region-based color image segmentation method is proposed in the paper, which transforms an image to L＊a＊b＊ space, and divides the image into sub-blocks, and extracts the color, texture and location features for every sub-block with combining the harr wavelet transform firstly. Then, the class number and the initial clustering centers are produced by using an improved Mean-shift algorithm. Finally, the method adopts an improved KFCM algorithm to achieve image segmentation. The experiment results show that this new algorithm can segment the color image into regions, and the segmentation result is good.

关 键 词：图像分割 小波变换 聚类 速度 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]