期刊文献+
任意字段
题名或关键词
题名
关键词
文摘
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息

FCM与马氏空间约束条件下的快速图像分割技术研究 被引量：3

Research of fast image segmentation based on Markov spatial constraint and fuzzy C-means clustering
在线阅读 下载PDF
导出
摘要 提出了一种FCM与马氏空间约束的快速图像分割技术。在FCM图像分割算法的基础上,引入了Markov随机场用以描述图像分割中的空间约束信息,并通过多级级联的方式获得最后的图像分割结果。这样既克服了传统模糊C均值聚类算法只考虑图像中的数值特征信息,忽略像素间的空间约束关系的缺点,又最大限度地保证了分割算法计算的简单有效性。实验证明,与其他模糊C均值聚类算法相比,本文方法有更好的可靠性与有效性。 This paper put forward a novel image segmentation technology based on Markov spatial constraint and fuzzy C- means （FCM） clustering. Based on fuzzy segmentation information drawn from standard fuzzy C-means clustering algorithm, the algorithm used Markov random filed to represent the spatial constraint information of image segmentation result. The new approach avoided the defect of standard FCM algorithm and kept the computation simplicity. The results of experiment prove the robustness and validity.
作者 刘思远 李晓峰 吴宏刚 李在铭
机构地区 电子科技大学通信与信息工程学院
出处 《计算机应用研究》 CSCD 北大核心 2007年第8期220-222,共3页 Application Research of Computers
基金 国家自然科学基金资助项目(10376005) 国家"863"计划资助项目(2004AA823120)
关键词 图像分割 马氏空间约束 模糊C均值聚类 image segmentation Markov spatial constraint fuzzy C-means clustering
分类号 TP391 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献7

  • 1BEZDEK J C.Pattern recognition with fuzzy objective function algorithms[M].NY:Plenum Press,1981:309-321.
  • 2LEUNG S H,WANG Shi-lin.Lip image segmentation using fuzzy clustering incorporating an elliptic shape function[J].IEEE Trans on Image Processing,2004,13(1):51-62.
  • 3冯衍秋,陈武凡,梁斌,林亚忠.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. 被引量：35
  • 4BESAG J.Spatial interaction and the statistical analysis of lattice systems[J].J Roy Statist Soc B,1974,36(2):192-236.
  • 5DERIN H,ELLIOTT H.Modeling and segmentation of noisy and textured images using Gibbs random fields[J].IEEE Trans Pattern Anal Machine Intell,1987,9(1):39-55.
  • 6高新波,李洁,姬红兵.基于加权模糊c均值聚类与统计检验指导的多阈值图像自动分割算法[J].电子学报,2004,32(4):661-664. 被引量：49
  • 7Brain MR images[EB/OL].(2001-08).[2006-03-21].http://www.bic.mni.mcgill.ca/.

二级参考文献23

  • 1刘健庄,谢维信,高新波.多阈值图像分割的遗传算法方法[J].模式识别与人工智能,1995,8(A01):126-132. 被引量：8
  • 2叶秀清,顾伟康,肖强.快速模糊分割算法[J].模式识别与人工智能,1996,9(1):66-70. 被引量：27
  • 3Axel Drehera, Peter Nunnenkampb, Rainer Thielec, 2010, "Are 'new'donors different? Comparing the allocation of bilateral aid between non-DAC and DAC donor countries", Kiel Working Paper 1601.
  • 4Dane Rowlands, "Emerging donors in international development assistance: a synthesis report", International Development Research Centre, Canada, January 2008.
  • 5Kimberly Smith, Talita Yamashiro Fordelone and Felix Zimmermann, 2010, "Beyond the DAC: the welcome role of other providers of development co-operation", OECD Development Co-operation Directorate.
  • 6Ngaire Woods, 2008, "Whose aid? Whose influence? China, emerging donors and the silent revolution in devel- opment assistance", International Affairs 84(6): 1205-1221.
  • 7Tsai D M,Chen Y H.A fast histogram-clustering approach for multi-level thresholding [J].Pattern Recognition Letters,1992,13:245-252.
  • 8Cheng H D,Chen J R,Li J G.Thresholding selection based on fuzzy C-partition entropy arrpoach [J].Pattern Recognition,1998,31(7):857-870.
  • 9Pornphan DULYAKARN,Yuttapong RANGSASERI.Fuzzy C-Means Clustering Using Spatial Information with Application to Remote Sensing [A].22nd Asian Conference on Remote Sensing [C].Singapore,2001.11.
  • 10Y Zhang,M Brady,S Smith.Segmentation of brain MR images through a hidden markov random field model and the expectation-maximization algorithm [J].IEEE Trans.Medical Imaging,2001,20(1):45-57.

共引文献78

同被引文献32

  • 1宋淑然,洪添胜,王卫星,李震.基于马氏距离的荔枝图像分割设计方法[J].沈阳农业大学学报,2005,36(6):655-658. 被引量：8
  • 2Jimenez A R,Ceres R, Pons J L.A survey of computer vision methods for locating fruit on trees[J].Transactions of the ASAE, 2000,43 (6) : 1911-1920.
  • 3Plebe A,Grasso G.Localization of spherical fruits for robotic har- vesting[J].Machine Vision and Applications, 2001,13 (2) : 70-79.
  • 4Ahmed 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 Med Imaging,2002,21(3):193-200.
  • 5Li Ma, Staunton R C.A modified fuzzy C-means image segraen- tation algorithm for use with uneven illumination pattems[J].Pat- tern Recognition, 2007,40( 11 ) : 3005-3011.
  • 6Smith A R.Color gamut transformation pairs[J].Computer Graph- ics, 1978,12(3) : 12-19.
  • 7Li S Z.Markov random field modeling in image analysis[M].3rd ed.[S.l.]: Springer, 2009.
  • 8Ahmed M N, Yamany S M, Mohamed N, Farag A A and Moriarty T.2002. A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data. IEEE Transactions on Medical Ima- ging, 21 (3) : 193 - 199.
  • 9Begum S A and Devi O M. 2012. A Rough type-2 fuzzy clustering algo- rithm for MR image segmentation. International Journal of Computer Applications, 54 (4) : 4 - 11.
  • 10Bezdek J C. 1981. Pattern Recognition with Fuzzy Objective Function Algorithms. New York : Plenum Press : 79 - 88.

引证文献3

二级引证文献22

计算机应用研究
2007年 第8期

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部