摘要
由于传统基于图论的图像分割方法是基于像素级别的,随着像素的增多,其应用也受到了限制,因此,提出一种改进的图像分割方法。该图像分割方法利用Dijkstra算法,将图像的像素点聚集形成超像素;应用Kruskal算法,得到最小生成树,确定并删除最小生成树的不一致边,完成图像分割。实验结果表明,改进方法分割的区域内部特征具有较好的均匀性和一致性。
The traditional image segmentation method based on graph theory is based on pixel level, whose application is limited when pixel number gets larger. So an improved image segmentation algorithm is proposed, in which image pixels are aggregated to form a super pixel using the Dijkstra algorithm and the Kruskal algorithm is used to get minimum spanning tree, determine and delete the inconsistent minimum spanning tree, and complete image segmentation. The experimental results show that the im- proved algorithm has the characteristics of regional segmentation uniformity and good consistency.
出处
《计算机与现代化》
2016年第9期64-67,共4页
Computer and Modernization
基金
湖南省教育厅科学研究基金资助项目(13C714)
怀化学院重点学科建设资助项目
关键词
图论
图像分割
最小生成树
最短路径
不一致边
graph theory
image segmentation
minimum spanning tree
shortest path
inconsistent side
