Integrated segmentation of noisy image based on the spatial relationship

T. Nguyen, Q. M. J. Wu
{"title":"Integrated segmentation of noisy image based on the spatial relationship","authors":"T. Nguyen, Q. M. J. Wu","doi":"10.1109/ICSAI.2012.6223469","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a new algorithm for an integrated image segmentation based on the combination of both Markov Random Fields (MRF) and Graph Cuts (GC). In the well-known GrabCut method, the T-link weights do not take into account the spatial relationship between the neighboring pixels. The proposed algorithm, unlike GrabCut method, incorporates this spatial relationship right into the T-link weights. The performance results obtained using natural images clearly demonstrate the robustness, accuracy and effectiveness of the proposed algorithm, as compared to other known methods.","PeriodicalId":164945,"journal":{"name":"2012 International Conference on Systems and Informatics (ICSAI2012)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Conference on Systems and Informatics (ICSAI2012)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSAI.2012.6223469","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

In this paper, we propose a new algorithm for an integrated image segmentation based on the combination of both Markov Random Fields (MRF) and Graph Cuts (GC). In the well-known GrabCut method, the T-link weights do not take into account the spatial relationship between the neighboring pixels. The proposed algorithm, unlike GrabCut method, incorporates this spatial relationship right into the T-link weights. The performance results obtained using natural images clearly demonstrate the robustness, accuracy and effectiveness of the proposed algorithm, as compared to other known methods.
基于空间关系的噪声图像综合分割
本文提出了一种基于马尔可夫随机场(MRF)和图割(GC)相结合的图像分割算法。在众所周知的GrabCut方法中,T-link权重没有考虑相邻像素之间的空间关系。与GrabCut方法不同的是,该算法将这种空间关系直接纳入t链路权重中。与其他已知方法相比,使用自然图像获得的性能结果清楚地证明了该算法的鲁棒性、准确性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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