摘要： 基于经典的图割(Graph cut)理论,提出一种基于超像素和改进Graph cut算法的图像分割算法。采用改进简单线性迭代聚类算法,得到前景边缘信息保存较完整的超像素图像。以超像素为处理单元,通过融合颜色、梯度等信息重建能量函数,并基于Graph cut框架进行分割。仿真结果显示,与Grabcut算法相比,改进算法不仅具有更高的分割精度,提取的目标边缘较完整、光滑,而且大幅提升了分割效率。

关键词: 图像分割, 改进迭代图割算法, 简单线性迭代聚类算法, 超像素, 能量函数

Abstract: Based on the classical graph cut theory,an image segmentation algorithm using super-pixel technique and improved iterated Graph cut algorithm is proposed.The super-pixel representation with the edges of foreground objects well preserved is obtained through an improved Simple Linear Iterative Clustering(SLIC) algorithm.Taking super-pixel as processing unit,segmentation is performed based on the framework of Graph cut,where the energy function is rebuilt by incorporating color and gradient information.Experimental results show that,compared with the Graph cut algorithm,the proposed algorithm not only has higher segmentation accuracy,extracts foreground objects with edges more complete and smooth,but also enhances the segmentation efficiency more significantly.

Key words: image segmentation, improved iterated Graph cut algorithm, Simple Linear Iterative Clustering(SLIC) algorithm, super-pixel, energy function

中图分类号: 

• TP301.6