基于图论的Normalized Cut图像分割方法研究

Research on Graph-based Normalized Cut Image Segmentation Method

基于图论的图像分割是近年来国际上研究图像分割算法领域中一个新的热点研究方向,Normalized Cut(规一化分割)是基于图论的分割方法中比较典型的一种。本文介绍Normalized Cut方法的相关内容,分析它的优缺点并提出几种有效的改进方法。最后,实验显示Normalized Cut在特定图片的分割上取得了不错的效果。

Graph-based image segmentation method is newly developing technique in recent years.Normalized cut is one of typically graph-based segmentation methods.This paper introduces correlative content of normalized cut,analyzes advantages and disadvantages of it,and proposes some efficiently solutions for improving.Finally,experimental results show that good result of segmentation can be obtained by the normalized cut algorithm.