摘要
为了提高均值漂移(MS)分割算法的运行效率,提出了一种结合MS与最小生成树(MST)的图像分割方法,简称MS-MST方法。首先选取较小的空间带宽参数,以较快的速度对图像进行MS分割,得到过分割图像;然后,以过分割区域作为后续处理的基本单元,构造加权区域邻接图,运用MST算法对其进行合并,得到最终的分割结果。实验结果表明,本文算法在保证图像分割质量的前提下,大幅提高了经典MS算法的分割速度。
This paper presents an image segmentation algorithm combining mean-shift with the minimum spanning tree,in order to improve the operating efficiency of the classic mean shift. The algorithm first selects a smaller spatial bandwidth,and applies the mean shift to over-segment image at a faster speed. Then,we regard the over-segmentation region as the basic unit of subsequent procedure to construct a weighted region adjacency graph,and then use the minimum spanning tree algorithm to merge over-seg- mentation image. The experimental results verify that this algorithm, on the premise of ensuring the quality of image segmentation, substantially increases the speed of the classic mean shift segmentation algorithm.
出处
《光电子．激光》
EI
CAS
CSCD
北大核心
2012年第3期588-594,共7页
Journal of Optoelectronics·Laser
基金
天津市科技支撑计划重点(10ZCKFGX00400)资助项目
作者简介
王倩,E-mail:wangqianky09@163.com;张桦(1962-),女,教授,博士生导师,主要研究方向为虚拟现实、图像处理、模式识别等.
