标题:Dislocation Theory Based Level Set Image Segmentation
作者:Zhang, Fan ;Zhang, Boyan ;Zhang, Xinhong
通讯作者:Zhang, Fan
作者机构:[Zhang, Fan ] School of Computer and Information Engineering, Henan University, Kaifeng; 475001, China;[Zhang, Xinhong ] School of Software, Henan Uni 更多
会议名称:15th International Conference on Intelligent Computing, ICIC 2019
会议日期:3 August 2019 through 6 August 2019
来源:Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
出版年:2019
卷:11643 LNCS
页码:218-227
DOI:10.1007/978-3-030-26763-6_21
关键词:Dislocation; Distance regularized level set method; Image segmentation
摘要:Dislocation theory of material science is introduced into the level set method. The curve evolution of level set method is viewed as the slipping of edge dislocation, and the curve evolution is driven by the dislocation configuration force which is derived based on the dislocation dynamics mechanism. In the image segmentation, the proposed algorithm can effectively avoid the phenomenon that level set function stop evolution because of the abnormal image gradient, and the phenomenon of boundary leakage because of the smaller image gradient. Experimental results show that the proposed algorithm has better segmentation performance for images with weak boundaries. © 2019, Springer Nature Switzerland AG.
收录类别:EI;SCOPUS
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070673077&doi=10.1007%2f978-3-030-26763-6_21&partnerID=40&md5=cd133231852a51e626d7e0fc312b7590
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