计算机与数字工程2025，Vol.53Issue(1)：221-227,7.DOI:10.3969/j.issn.1672-9722.2025.01.040
像素点可信度划分层级且具梯度权重的GrabCut
GrabCut with Gradient Weight and Hierarchical Pixel Credibility
摘要
Abstract
The article studies the classic foreground subject segmentation algorithm GrabCut,where all pixels are initialized and labeled as front/background labels,and subsequently participate equally in GMM.However,pixels may be located in the front/background boundary region or even in opposite classes,and propagating the labels of these pixels to their neighboring pixels may mislead segmentation.Therefore,the article proposes GrabCut(HCGW_GrabCut),which divides pixel credibility into hierarchical levels and has gradient weights.Initialization is achieved through membership clustering(soft clustering),such as KFCM_iI,to ob-tain the probability of pixels being located in non edge regions,which is called credibility.Then,the pixel set is divided into levels based on credibility and gradient weights are used,so that pixels with higher credibility participate in the subsequent GMM compo-nents more frequently and with higher weights,emphasizing the contribution and importance of high credibility pixels.Finally,em-pirical results on images with complex backgrounds,high similarity between the foreground and background,or subjects with jag-ged edges(sourced from COCO_test2014,DIV2K,BSDS300)show that HCGW_GrabCut has a certain competitiveness compared to GrabCut.关键词
图像前景主体分割/可信度/层级/权重/GrabCutKey words
image foreground subject segmentation/credibility/hierarchical/weight/GrabCut分类
信息技术与安全科学引用本文复制引用
沈雅婷,宗平,曾璐洁,黄延浩..像素点可信度划分层级且具梯度权重的GrabCut[J].计算机与数字工程,2025,53(1):221-227,7.基金项目
江苏省大学生创新创业项目(编号:202413654018Y) （编号:202413654018Y）
江苏高校"青蓝工程"资助. （）
