结合FCMS与变分水平集的图像分割模型

唐利明; 田学全; 黄大荣; 王晓峰

doi:10.3724/SP.J.1004.2014.01233

结合FCMS与变分水平集的图像分割模型

doi: 10.3724/SP.J.1004.2014.01233

1.
重庆科技学院数理学院重庆 401331;
2.
重庆大学数学与统计学院重庆 401331;
3.
重庆交通大学山区桥梁与隧道工程国家重点实验室培育基地重庆 400074

基金项目:

国家自然科学基金（61004118）资助

详细信息

作者简介:
田学全重庆科技学院数理学院副教授.主要研究方向为粗糙集，数据挖掘，运筹与优化. E-mail：tianxueq@126.com

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- 文章访问数: 1888
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- 被引次数: 0
出版历程
- 收稿日期: 2012-12-11
- 修回日期: 2013-07-16
- 刊出日期: 2014-06-20

Image Segmentation Model Combined with FCMS and Variational Level Set

1.
College of Mathematics and Physics, Chongqing University of Science and Technology, Chongqing 401331;
2.
College of Mathematics and Statistics, Chongqing University, Chongqing 401331;
3.
National Key Laboratory Incubation Base of Mountain Bridge and Tunnel Engineering, Chongqing Jiaotong University, Chongqing 400074

Funds:

Supported by National Natural Science Foundation of China (61004118)

摘要

摘要: 提出了一个结合融合空间约束的模糊C均值（Fuzzy C means with spatial constraints，FCMS）聚类与变分水平集的图像模糊聚类分割模型.在该模型中引入了一个基于图像局部信息和空间信息的外部模糊聚类能量，从而可以获取精确的局部图像的空间特征，使得本文模型对噪声图像的聚类分割具有较强的鲁棒性.采用不同类型的实验图像，将本文模型与10个不同类型的图像分割模型进行了对比实验，实验结果显示本文模型能克服图像中噪声影响并取得较满意的聚类分割结果.
- 变分水平集 /
- 图像聚类 /
- 图像分割 /
- FCMS聚类 /
- 隶属度 /
- 聚类中心
Abstract: This paper proposes an image fuzzy clustering segmentation model combined with FCMS clustering and variational level set method. An external fuzzy clustering energy based on local information and spatial information of the image is introduced in the energy functional to enable us to extract the accurate spatial information of the local image. Therefore, the proposed model is robust to noisy image segmentation. The experiment results illustrate that the proposed model, compared with 10 different models, can overcome the influence of noise and obtain better segmentation results for different images.
- Variational level set /
- image clustering /
- image segmentation /
- fuzzy C means with spatial constraints (FCMS) clustering /
- membership /
- clustering centers

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参考文献(24)

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