Research on Improved of Level Set Image Segmentation Algorithms Based on LBF Model

Hongya Wang, Lixia Yu
{"title":"Research on Improved of Level Set Image Segmentation Algorithms Based on LBF Model","authors":"Hongya Wang, Lixia Yu","doi":"10.1109/iske47853.2019.9170464","DOIUrl":null,"url":null,"abstract":"For the images characteristic With intensity inhomogeneity, this paper proposes an improved model of contour evolution LBF energy function, Which combines the global CV model energy term accelerated evolution rate and the combined local mean LBF model information, While the introduction of a global image of the local variance and variance information. Experimental results show that this method can provide accurate smooth closed boundary, precision can reach sub-pixel level. The recognition accuracy rate is high.","PeriodicalId":399084,"journal":{"name":"2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"121 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iske47853.2019.9170464","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

For the images characteristic With intensity inhomogeneity, this paper proposes an improved model of contour evolution LBF energy function, Which combines the global CV model energy term accelerated evolution rate and the combined local mean LBF model information, While the introduction of a global image of the local variance and variance information. Experimental results show that this method can provide accurate smooth closed boundary, precision can reach sub-pixel level. The recognition accuracy rate is high.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于LBF模型的水平集图像分割算法改进研究
针对图像具有强度不均匀性的特点,提出了一种改进的轮廓演化LBF能量函数模型,该模型结合了全局CV模型能量项加速演化率和LBF模型局部均值信息,同时引入了全局图像的局部方差和方差信息。实验结果表明,该方法可以提供精确的光滑封闭边界,精度可达到亚像素级。识别准确率高。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Incremental Learning for Transductive SVMs ISKE 2019 Table of Contents Consensus: The Minimum Cost Model based Robust Optimization A Learned Clause Deletion Strategy Based on Distance Ratio Effects of Real Estate Regulation Policy of Beijing Based on Discrete Dependent Variables Model
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1