主动测地线:基于全局边缘约束的区域主动轮廓分割。

Vikram Appia, Anthony Yezzi
{"title":"主动测地线:基于全局边缘约束的区域主动轮廓分割。","authors":"Vikram Appia,&nbsp;Anthony Yezzi","doi":"10.1109/ICCV.2011.6126468","DOIUrl":null,"url":null,"abstract":"<p><p>We present an <i>active geodesic</i> contour model in which we constrain the evolving active contour to be a geodesic with respect to a weighted edge-based energy through its entire evolution rather than just at its final state (as in the traditional <i>geodesic active contour</i> models). Since the contour is always a geodesic throughout the evolution, we automatically get local optimality with respect to an edge fitting criterion. This enables us to construct a purely region-based energy minimization model without having to devise arbitrary weights in the combination of our energy function to balance edge-based terms with the region-based terms. We show that this novel approach of combining edge information as the <i>geodesic constraint</i> in optimizing a purely region-based energy yields a new class of active contours which exhibit both local and global behaviors that are naturally responsive to intuitive types of user interaction. We also show the relationship of this new class of globally constrained active contours with traditional minimal path methods, which seek global minimizers of purely edge-based energies without incorporating region-based criteria. Finally, we present some numerical examples to illustrate the benefits of this approach over traditional active contour models.</p>","PeriodicalId":74564,"journal":{"name":"Proceedings. IEEE International Conference on Computer Vision","volume":"2011 ","pages":"1975-1980"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/ICCV.2011.6126468","citationCount":"40","resultStr":"{\"title\":\"Active Geodesics: Region-based Active Contour Segmentation with a Global Edge-based Constraint.\",\"authors\":\"Vikram Appia,&nbsp;Anthony Yezzi\",\"doi\":\"10.1109/ICCV.2011.6126468\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>We present an <i>active geodesic</i> contour model in which we constrain the evolving active contour to be a geodesic with respect to a weighted edge-based energy through its entire evolution rather than just at its final state (as in the traditional <i>geodesic active contour</i> models). Since the contour is always a geodesic throughout the evolution, we automatically get local optimality with respect to an edge fitting criterion. This enables us to construct a purely region-based energy minimization model without having to devise arbitrary weights in the combination of our energy function to balance edge-based terms with the region-based terms. We show that this novel approach of combining edge information as the <i>geodesic constraint</i> in optimizing a purely region-based energy yields a new class of active contours which exhibit both local and global behaviors that are naturally responsive to intuitive types of user interaction. We also show the relationship of this new class of globally constrained active contours with traditional minimal path methods, which seek global minimizers of purely edge-based energies without incorporating region-based criteria. Finally, we present some numerical examples to illustrate the benefits of this approach over traditional active contour models.</p>\",\"PeriodicalId\":74564,\"journal\":{\"name\":\"Proceedings. IEEE International Conference on Computer Vision\",\"volume\":\"2011 \",\"pages\":\"1975-1980\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1109/ICCV.2011.6126468\",\"citationCount\":\"40\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. IEEE International Conference on Computer Vision\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCV.2011.6126468\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. IEEE International Conference on Computer Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCV.2011.6126468","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 40

摘要

我们提出了一种主动测地线轮廓模型,在该模型中,我们将进化的活动轮廓约束为在其整个进化过程中相对于加权边缘能量的测地线,而不仅仅是在其最终状态(如传统的测地线活动轮廓模型)。由于在整个进化过程中轮廓始终是测地线,因此我们可以根据边缘拟合准则自动获得局部最优性。这使我们能够构建一个纯粹基于区域的能量最小化模型,而无需在我们的能量函数组合中设计任意权重来平衡基于边缘的项和基于区域的项。我们表明,这种将边缘信息作为优化纯基于区域的能量的测地线约束的新方法产生了一类新的活动轮廓,这些轮廓既表现出局部行为,也表现出对直观类型的用户交互自然响应的全局行为。我们还展示了这类新的全局约束活动轮廓与传统最小路径方法的关系,后者寻求纯基于边缘的能量的全局最小值,而不包含基于区域的准则。最后,我们给出了一些数值例子来说明该方法相对于传统活动轮廓模型的优点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Active Geodesics: Region-based Active Contour Segmentation with a Global Edge-based Constraint.

We present an active geodesic contour model in which we constrain the evolving active contour to be a geodesic with respect to a weighted edge-based energy through its entire evolution rather than just at its final state (as in the traditional geodesic active contour models). Since the contour is always a geodesic throughout the evolution, we automatically get local optimality with respect to an edge fitting criterion. This enables us to construct a purely region-based energy minimization model without having to devise arbitrary weights in the combination of our energy function to balance edge-based terms with the region-based terms. We show that this novel approach of combining edge information as the geodesic constraint in optimizing a purely region-based energy yields a new class of active contours which exhibit both local and global behaviors that are naturally responsive to intuitive types of user interaction. We also show the relationship of this new class of globally constrained active contours with traditional minimal path methods, which seek global minimizers of purely edge-based energies without incorporating region-based criteria. Finally, we present some numerical examples to illustrate the benefits of this approach over traditional active contour models.

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
期刊最新文献
PGFed: Personalize Each Client's Global Objective for Federated Learning. The Devil is in the Upsampling: Architectural Decisions Made Simpler for Denoising with Deep Image Prior. Enhancing Modality-Agnostic Representations via Meta-learning for Brain Tumor Segmentation. SimpleClick: Interactive Image Segmentation with Simple Vision Transformers. Improving Representation Learning for Histopathologic Images with Cluster Constraints.
×
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