###
计算机系统应用英文版:2017,26(2):174-178
本文二维码信息
码上扫一扫!
背景自适应的GrabCut图像分割算法
(1.西南科技大学 信息工程学院, 绵阳 621010;2.西南科技大学 研究生院, 绵阳 621010)
Adaptive Background Image Segmentation Algorithm Based on GrabCut
(1.School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, China;2.School of National Postgraduate academy, Southwest University of Science and Technology, Mianyang 621010, China)
摘要
图/表
参考文献
相似文献
本文已被:浏览 1823次   下载 3540
Received:June 06, 2016    Revised:July 25, 2016
中文摘要: 图割用于图像分割需用户交互,基于激光雷达传感器,提出了阈值法得到目标的外截矩形,再映射到图像完成交互.针对GrabCut算法耗时、对局部噪声敏感和在复杂背景提取边缘不理想等缺点,提出了背景自适应的GrabCut算法,即在确定背景像素中选取可能目标像素邻近的一部分像素作为背景像素,使背景变得简单,尤其适用于前景像素在整幅图中所占比例较小和在目标像素周围的背景相对简单的情况.实验结果表明,所提算法与GrabCut算法相比,减少了图的节点数,降低了错误率,有效的提高了运行效率,提取的目标边缘信息更加完整、平滑.
Abstract:Graph cut needs user interaction on image segmentation, which comes up with that threshold value method, gets the objects by cutting rectangle and then we remaps to image to finish the interaction by laser radar. GrabCut algorithm is sensitive to local noise, and it is time-consuming. In addition, the edge extraction is not ideal under complex background, so an improved GrabCut algorithm is put forward to adapt background automatically in the determined background. The proposed algorithm chooses probable foreground neighboring pixels as background pixels to make background become simple. It is applicable to the case when foreground pixels account for low proportion in the whole image pixels and the background pixels are relatively simple around the foreground. Experimental results show that error rate of the proposed algorithm is reduced and the efficiency is improved in comparison with GrabCut algorithm after reducing nodes number in the graph. In addition, the edge extraction is more complete and smooth.
文章编号:     中图分类号:    文献标志码:
基金项目:
引用文本:
杨绍兵,李磊民,黄玉清.背景自适应的GrabCut图像分割算法.计算机系统应用,2017,26(2):174-178
YANG Shao-Bing,LI Lei-Min,HUANG Yu-Qing.Adaptive Background Image Segmentation Algorithm Based on GrabCut.COMPUTER SYSTEMS APPLICATIONS,2017,26(2):174-178