结合聚类与改进分水岭算法的彩色图像分割  

Color Image Segmentation Based on Clustering and Improved Watershed Segmentation

作　　者：徐蔚钦[1] 许雪梅[1] 黄帅[1] 

机构地区：[1]中南大学物理科学与技术学院,长沙410083

出　　处：《计算机系统应用》2011年第7期53-56,21,共5页Computer Systems & Applications

基　　金：中国博士后基金(20070420825)

摘　　要：针对传统分水岭算法产生严重的过分割问题,提出了一种聚类和改进分水岭算法结合的彩色图像分割算法。该算法首先利用聚类算法在HSV颜色空间将特征相似的像素归为一类,然后对分水岭算法产生的分割区域进行种子区域生长,并利用区域合并将剩余的小区域进行合并,从而完成了对彩色图像的分割。实验证明该算法减少了分水岭算法的过分割现象,提高了图像分割的精确性,具有很好的鲁棒性和适应性。In view of the existence of obvious over-segmentation problem in traditional watershed algorithm,an improved color image segmentation algorithm is proposed in this paper.This algorithm combines clustering and improved watershed algorithm methods.In HSV color space,the algorithm firstly utilizes clustering to classify pixels with similar features,then applies seed region growing algorithm for the regions generated by watershed segmentation algorithm.Furthermore,region merging approach is used to merge remaining small regions.Experimental results show that this algorithm reduces over-segmentation phenomenon significantly,and improves image accuracy while maintaining strong robustness and adaptability.

关 键 词：图像分割 分水岭算法 颜色聚类 区域生长 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]