摘要
结合粗糙集理论和K 均值聚类算法,提出了一种图像分割方法。将原图像按等价关系进行划分,基于属性约简的概念对不同区域按照不可分辨关系分类。分割结果表明,文中方法是一种有效的图像分割方法,具有良好的鲁棒性。
Rough Set theory is a new mathematical tool to deal with problems on vagueness and uncertainty. An image segmentation method based on Rough Set theory and K-means clustering is presented. The original image is segmented according to the relation of equal value. By applying value reduct to the attribute values, different regions are classified based on indiscernibility. The experimental results indicate that the method can improve veracity and stability of image segmentation.
出处
《红外与激光工程》
EI
CSCD
北大核心
2004年第3期300-302,共3页
Infrared and Laser Engineering
基金
高等学校博士点专项科研基金(20020699014)
关键词
粗糙集
K-均值聚类
图像分割
Rough Set
K-means clustering
Image segmentation
