改进的GrabCut算法木材表面缺陷图像分割试验

摘要

试验采用传统GrabCut算法和改进的GrabCut算法,针对单目标、多目标、复杂背景下多目标的木材表面缺陷图像进行多组对比实验.结果表明:改进后的GrabCut算法,针对木材表面的缺陷图像分割进行了优化,能有效改进传统GrabCut算法中的欠分割和过分割、易受区域凹凸纹理的干扰等缺点,而且分割各类木材表面缺陷图像时都能取得较好的效果.说明改进后的GrabCut算法具有其优势和可行性.%The traditional GrabCut algorithm and the improved GrabCut algorithm are used to simulate the multi -target wood sur-face defect images in single target , multi-target and complex background .The improved GrabCut algorithm was optimized for the defect image segmentation of the wood surface , which could effectively improve the defects of the traditional Grab-Cut algorithm , such as under-segmentation , over-segmentation , and susceptible to interference from regional bumps .The segmentation of all kinds of wood surface defects images achieves better results , and the improved GrabCut algorithm is with its advantages and feasibility .