基于模糊c均值聚类和图切优化的多相水平集图像分割方法

Lin Song, M. Gao, Sa Wang, Shuxia Wang
{"title":"基于模糊c均值聚类和图切优化的多相水平集图像分割方法","authors":"Lin Song, M. Gao, Sa Wang, Shuxia Wang","doi":"10.1109/ICISCE.2015.141","DOIUrl":null,"url":null,"abstract":"Multiphase level set model is sensitive to initial contour curve and has huge computation in the process of the multiple objects' segmentation. This paper presents a novel Image segmentation method for multiphase scenario, which initialize the multiphase level set function by coarse image segmentation using fuzzy C-means clustering algorithm and apply graph cut algorithm to acquire multiphase output image. The method effectively reduces the sensitivity of the multiphase level set algorithm to initial contour and is easier to gain the multiphase output image by graph cut algorithm. At the same time, because of using the graph cut algorithm, the multiphase level set function quickly converge to the minimum energy value with small amount of calculation and high computational efficiency. The experiments show that this method has better segmentation effect and higher efficiency of image segmentation.","PeriodicalId":356250,"journal":{"name":"2015 2nd International Conference on Information Science and Control Engineering","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An Image Segmentation Method by Combining Fuzzy C-Means Clustering and Graph Cuts Optimization for Multiphase Level Set Algorithms\",\"authors\":\"Lin Song, M. Gao, Sa Wang, Shuxia Wang\",\"doi\":\"10.1109/ICISCE.2015.141\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Multiphase level set model is sensitive to initial contour curve and has huge computation in the process of the multiple objects' segmentation. This paper presents a novel Image segmentation method for multiphase scenario, which initialize the multiphase level set function by coarse image segmentation using fuzzy C-means clustering algorithm and apply graph cut algorithm to acquire multiphase output image. The method effectively reduces the sensitivity of the multiphase level set algorithm to initial contour and is easier to gain the multiphase output image by graph cut algorithm. At the same time, because of using the graph cut algorithm, the multiphase level set function quickly converge to the minimum energy value with small amount of calculation and high computational efficiency. The experiments show that this method has better segmentation effect and higher efficiency of image segmentation.\",\"PeriodicalId\":356250,\"journal\":{\"name\":\"2015 2nd International Conference on Information Science and Control Engineering\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-04-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 2nd International Conference on Information Science and Control Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICISCE.2015.141\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 2nd International Conference on Information Science and Control Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICISCE.2015.141","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

多相水平集模型对初始轮廓曲线敏感,在多目标分割过程中计算量大。提出了一种新的多相场景图像分割方法,利用模糊c均值聚类算法对图像进行粗分割,初始化多相水平集函数,并应用图切算法获取多相输出图像。该方法有效地降低了多相水平集算法对初始轮廓的敏感性,更容易通过图切算法获得多相输出图像。同时,由于采用了图割算法,多相水平集函数快速收敛到最小能量值,计算量小,计算效率高。实验表明,该方法具有较好的分割效果和较高的分割效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Image Segmentation Method by Combining Fuzzy C-Means Clustering and Graph Cuts Optimization for Multiphase Level Set Algorithms
Multiphase level set model is sensitive to initial contour curve and has huge computation in the process of the multiple objects' segmentation. This paper presents a novel Image segmentation method for multiphase scenario, which initialize the multiphase level set function by coarse image segmentation using fuzzy C-means clustering algorithm and apply graph cut algorithm to acquire multiphase output image. The method effectively reduces the sensitivity of the multiphase level set algorithm to initial contour and is easier to gain the multiphase output image by graph cut algorithm. At the same time, because of using the graph cut algorithm, the multiphase level set function quickly converge to the minimum energy value with small amount of calculation and high computational efficiency. The experiments show that this method has better segmentation effect and higher efficiency of image segmentation.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信