An Improved Random Walker using Spatial Feature for Image Segmentation

摘要：

　　The random walker algorithm for image segmentation is an effective method.However,the traditional random walker algorithm (RW) is only determined by the adjacent node (pixels) intensity information in the feature space,and the algorithm does not take the spatial feature information of nodes (pixels) into consideration,which makes the segmentation results discrete in the spatial distribution.In this work,an improved random walker algorithm (SRW) has been proposed to improve the efficiency and accuracy of the extraction with complicate background.Firstly,spatial feature information has been employed to combine with the intensity information to measure weights between adjacent nodes (pixels).The freedom parameters have been then adjusted for the two features above to obtain the scale.Finally,the experimental result shows that the improved random walker algorithm (SRW) is effective in extracting objects contour with complicate background.

关键词： Image Segmentation Random Walker Algorithm Spatial Feature

作者: Zhaohua Cui Wenna Li Gai Pan Liqun Gao

作者单位: School of information science and engineering, Northeastern University, Shenyang, 110819;Unit 65041, School of information science and engineering, Northeastern University, Shenyang, 110819

会议类型: 国际会议

会议名称: the 25th Chinese Control and Decision Conference(第25届中国控制与决策会议)

会议地点: 贵阳

会议语种:英文

页码: 1479-1482

在线出版日期: 2013-05-01（万方平台首次上网日期，不代表论文的发表时间）