基于超像素的多主体图像交互分割

目的 为解决多主体图像的交互分割问题,在保证分割效果的前提上,提高分割的效率,达到实时交互修改分割结果的目的, 提出基于超像素的图像多主体交互分割算法.方法 基于图像的超像素构造一个多层流网络,利用用户交互绘制的简单笔画给出多主体分割的指导信息.流网络的边权值保证利用图割算法将图像分割成多个部分后,每个部分代表图像的一个主体.允许用户交互给出标记,实时修改分割结果,直到得到满意的多主体分割.结果 通过实验显示,本文方法能得到的满意多主体分割结果,而且时间效率较高.对分辨率为449×275的图像,算法能在1 s内给出结果,满足实时修改的要求.结论 基于超像素建立的图规模较小,能大大减少图割算法的运行时间,达到用户实时交互添加新笔画信息,交互地修正分割结果的目的.利用超像素的边界信息,用户只需输入比较简单的笔画信息,分割算法就能得到正确的多主体分割结果.

Interactive multiphase image segmentation based on superpixels

Objective This paper proposes an interactive method of multi-phase image segmentation that maximizes the boundary information in the superpixels of an image. This new method is adequately fast as a real-time, interactive segmentation tool. Method The new approach first constructs a multi-layer graph that employs the superpixels of an image as graph nodes. The weights of the graph edges are assigned specifically by applying the GraphCut algorithm that appropriately segments the input image. We also propose an interface through which new indicating strokes can be added interactively to improve segmentation quality. Result A number of examples demonstrate the capability of the new approach to facilitate accurate multi-phase segmentation at low computational cost. In fact, a satisfactory segmentation result is obtained in less than one second for an image with adimension of 449×275 pixels. Conclusion The computation time of the GraphCut algorithm increases logarithmically as the number of superpixels increases. By contrast, super-pixel computation time increases linearly. Thus, our new method is advantageous in that it uses superpixels as graph nodes instead of employing pixels, as in previous methods. The utilization of pixels considerably reduces graph dimension.