基于FCM和随机游走的地层图像分割方法

doi:10.3969/j.issn.0372-2112.2013.03.018

电子学报

基于FCM和随机游走的地层图像分割方法

陈圣国^1,2, 孙正兴¹, 周杰¹

1. 南京大学计算机软件新技术国家重点实验室, 江苏南京 210093;
2. 金陵科技学院信息技术学院, 江苏南京 211169

收稿日期:2011-08-10 修回日期:2012-09-20 出版日期:2013-03-25
- 通讯作者:
- 孙正兴 男,1964年出生,教授,博士生导师,主要研究领域为多媒体计算,计算机视觉和智能人机交互. E-mail:szx@nju.edu.cn
- 作者简介:
- 陈圣国 男,1969年出生,江苏如皋人,副教授,博士研究生,主要研究领域为图像理解与计算机视觉技术. E-mail:chenshengguo@gmail.com; 孙正兴 男,1964年出生,教授,博士生导师,主要研究领域为多媒体计算,计算机视觉和智能人机交互. E-mail:szx@nju.edu.cn
- 基金资助:
- 国家自然科学基金 (No.61272219,No.61100110,No.61021062); 国家863高技术研究发展计划 (No.2007AA01Z334); 江苏省科技计划 (No.BE2010072,No.BE2011058,No.BY2012190)

A Segmentation Method for Stratum Image Based on FCM and Random Walks

CHEN Sheng-guo^1,2, SUN Zheng-xing¹, ZHOU Jie¹

1. State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, Jiangsu 210093, China;
2. School of Information Technology, Jinling Institute of Technology, Nanjing, Jiangsu 211169, China

Received:2011-08-10 Revised:2012-09-20 Online:2013-03-25 Published:2013-03-25
- Supported by:
- National Natural Science Foundation of China (No.61272219, No.61100110, No.61021062); National High-tech R&D Program of China (863 Program) (No.2007AA01Z334); Jiangsu Science and Technology Program (No.BE2010072, No.BE2011058, No.BY2012190)

摘要/Abstract

摘要： 颜色特征是地层图像分割的重要依据,但地层图像的高噪声以及地层边界颜色混合使得颜色特征空间聚类分割方法无法获得很好的结果.本文提出了一种融合模糊C均值聚类与随机游走算法的图像分割算法,该算法在聚类过程中结合像素的空间信息计算像素的隶属度,在基于随机游走的半监督图像分割算法中像素结点构成的四连通图上插入类属结点作为已标记结点,将随机游走者第一次游走到某个类属结点的概率作为该像素隶属于该类的隶属度.实验结果表明,本算法可以对地层边界颜色混合区域的像素更准确地进行分类,噪声敏感性降低,有效解决构造模拟地层图像的分割问题.

关键词: 图像分割, 模糊C均值聚类, 随机游走

Abstract: The color feature is the crucial basis for segmenting a stratum image,but traditional segmentation algorithms based on color feature clustering cannot get desirable results because of colors mixture near the layers' boundaries and heavy noisy.A new image segmentation method is proposed,it adopts an interactive image segmentation algorithm based on Random Walks to improve the computing method of the membership functions of fuzzy C-mean(FCM) incorporating spatial information.It inserts labeled cluster-nodes into the graph formed with pixels and their 4-connectedness,and takes the probabilities that a random walker starting its walk at a pixel first reaches a labeled cluster-node as the membership it belongs to this cluster.The experimental results show that pixels in the area of mixed colors near the layers' boundary are classified more accurately;the method decreases the noise sensitivity of FCM,and can effectively segment the structure physical modeling images.

Key words: image segmentation, fuzzy C-means clustering, random walks

中图分类号:

TP391.7

陈圣国, 孙正兴, 周杰. 基于FCM和随机游走的地层图像分割方法[J]. 电子学报, DOI: 10.3969/j.issn.0372-2112.2013.03.018.

CHEN Sheng-guo, SUN Zheng-xing, ZHOU Jie . A Segmentation Method for Stratum Image Based on FCM and Random Walks[J]. Acta Electronica Sinica, DOI: 10.3969/j.issn.0372-2112.2013.03.018.

参考文献

[1] 时秀朋,李理,龚道好,等.构造物理模拟实验方法的发展与应用 [J].地球物理学进展,2007,22(6):1728-1735. Shi Xiu-Peng,Li Li,Gong Dao-hao,et al.The development and application of structure physical modeling[J].Progress in Geophysics,2007,22(6):1728-1735.(in Chinese)
[2] 黄宇,付琨,吴一戎.基于Markov随机场K-Means图像分割算法 [J].电子学报,2009,37(12):2700-2704. Huang Yu,Fu Kun,Wu Yi-rong.Image segmentation method using K-means based on Markov random field[J].Acta Electronica Sinica,2009,37(12):2700-2704.(in Chinese)
[3] 丁震,胡钟山,杨靖宇,等.FCM算法用于灰度图象分割的研究 [J].电子学报,1997,25(5):39-43. Ding Zhen,Hu Zhong-shan,Yang Jing-yu,et al.FCM algorithm for the research of intensity image segmentation[J].Acta Electronica Sinica,1997,25(5):39-43.(in Chinese)
[4] Dunn J C.A fuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters [J].Cybernetics and Systems,1973,3(3):32-57.
[5] Bezdek J C.Pattern Recognition with Fuzzy Objective Function Algorithms [M].Kluwer Academic Publishers,1981.
[6] Bezdek J C.A convergence theorem for the fuzzy ISODATA clustering algorithms.IEEE Transactions on Pattern Analysis and Machine Intelligence,1980,2(1):1-8.
[7] Liew A,Leung S,Lau W.Fuzzy image clustering incorporating spatial continuity.IEE Proceedings Vision,Image & Signal Processing,2000,147(2):185-192.
[8] Karmakar G C,Dooley L S.A generic fuzzy rule based image segmentation algorithm [J].Pattern recognition letters,2002,23(10):1215-1227.
[9] Ahmed M N,Yamany S M,Mohamed N,et al.A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data [J].IEEE Transactions on Medical Imaging,2002,21(3):193-199.
[10] Chen S C,Zhang D Q.Robust image segmentation using FCM with spatial constraints based on new kernel-induced distance measure [J].IEEE Transactions on Systems,Man,and Cybernetics,Part B:Cybernetics,2004,34(4):1907-1916.
[11] Chen Q,Ji Z X,Sun Q S,et al.Homogeneous patch based FCM algorithm for brain MR Image segmentation [A].Proceedings of the Chinese Conference on Pattern Recognition,2009 [C].Los Alamitos:IEEE Computer Society Press,2009.1-5.
[12] 冯衍秋,陈武凡,梁斌,等.基于Gibbs随机场与模糊C均值聚类的图像分割新算法 [J].电子学报,2004,32(4):645-647. Feng Yan-qiu,Chen Wu-fan,Liang Bin,et al.A new algorithm for image segmentation based on gibbs random field and fuzzy C-means clustering [J].Acta Electronica Sinica,2004,32(4):645-647.(in Chinese)
[13] Udupa J K,Samarasekera S.Fuzzy connectedness and object definition:theory,algorithms,and applications in image segmentation [J].Graphical Models and Image Processing,1996,58(3):246-261.
[14] Udupa J K,Saha P K,Lotufo R A.Fuzzy connected object definition in images with respect to co-objects [A].Proceedings of the SPIE:Medical Imaging 3661 [C].San Diego:SPIE,1999.236-245.
[15] Udupa J K,Saha P K,et al.Relative fuzzy connectedness and object definition:Theory,algorithms,and applications in image segmentation [J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2002,24(11):1485-1500.
[16] 依玉峰,高立群,郭丽.改进FCM在交互式图像分割中的应用 [J].中国图象图形学报,2012,17(3):342-348. Yi Yu-Feng,Gao Li-Qun,Guo Li.Application of improved FCM for interactive image segmentation[J].Chinese Journal of Image and Graphics,2012,17(3):342-348.(in Chinese)
[17] Grady L.Random walks for image segmentation [J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2006,28(11):1768-1783.
[18] Grady L,Funka-lea G.Multi-label image segmentation for medical applications based on graph-theoretic electrical potentials [A].Lecture Notes in Computer Science,Computer Vision and Mathematical Methods in Medical and Biomedical Image Analysis [C].Berlin:Springer Berlin/Heidelberg,2004.230-245.
[19] Grady L,Schiwietz T,et al.Random walks for interactive organ segmentation in two and three dimensions:Implementation and validation [A].Proceedings of the Medical Image Computing and Computer-Assisted Intervention [C].Berlin:Springer Berlin/Heidelberg,2005.773-780.
[20] Doyle P,Snell J.Random Walks and Electric Networks [M].Ann Arbor:The Mathematical Association of America,1984.

基于FCM和随机游走的地层图像分割方法

A Segmentation Method for Stratum Image Based on FCM and Random Walks

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

[1]	曹阳, 高旻, 余俊良, 范琪琳, 荣文戈, 文俊浩. 基于双图混合随机游走的社会化推荐模型[J]. 电子学报, 2023, 51(2): 286-296.
[2]	唐利明, 熊点华, 方壮. 基于比尔朗伯定律的变分水平集模型[J]. 电子学报, 2023, 51(2): 416-426.
[3]	金天虎, 陶砚蕴, 李佐勇. 基于超像素图像分割的暗通道先验去雾改进算法[J]. 电子学报, 2023, 51(1): 146-159.
[4]	蔡超丽, 李纯纯, 黄琳, 杨铁军. ED-NAS: 基于神经网络架构搜索的陶瓷晶粒SEM图像分割方法[J]. 电子学报, 2022, 50(2): 461-469.
[5]	张淑军, 彭中, 李辉. SAU-Net：基于U-Net和自注意力机制的医学图像分割方法[J]. 电子学报, 2022, 50(10): 2433-2442.
[6]	吴绿, 张馨月, 唐茉, 王梓, 王永安. Focus+Context语义表征的场景图像分割[J]. 电子学报, 2021, 49(3): 596-604.
[7]	李青青, 马慧芳, 李举, 李志欣. 属性网络中相似性增强随机游走的多社区搜索[J]. 电子学报, 2021, 49(11): 2096-2100.
[8]	朱占龙, 刘永军. 融合混沌优化和改进模糊聚类的图像分割算法[J]. 电子学报, 2020, 48(5): 975-984.
[9]	梁新宇, 林洗坤, 权冀川, 肖铠鸿. 基于深度学习的图像实例分割技术研究进展[J]. 电子学报, 2020, 48(12): 2476-2486.
[10]	石雪, 李玉, 赵泉华. 自适应类别的层次高斯混合模型遥感影像分割[J]. 电子学报, 2020, 48(1): 131-136.
[11]	雷涛, 张肖, 加小红, 刘侍刚, 张艳宁. 基于模糊聚类的图像分割研究进展[J]. 电子学报, 2019, 47(8): 1776-1791.
[12]	季鼎承, 蒋亦樟, 王士同. 基于域与样例平衡的多源迁移学习方法[J]. 电子学报, 2019, 47(3): 692-699.
[13]	范虹, 张程程, 侯存存, 朱艳春, 姚若侠. 结合双树复小波变换和改进密度峰值快速搜索聚类的乳腺MR图像分割[J]. 电子学报, 2019, 47(10): 2149-2157.
[14]	侯小刚, 赵海英, 马严. 基于超像素多特征融合的快速图像分割算法[J]. 电子学报, 2019, 47(10): 2126-2133.
[15]	张峰, 钟宝江. 基于兴趣目标的图像检索[J]. 电子学报, 2018, 46(8): 1915-1923.