基于KFCM与改进CV模型的Split Bregman图像分割方法

计算机科学 ›› 2014, Vol. 41 ›› Issue (Z6): 153-155.

基于KFCM与改进CV模型的Split Bregman图像分割方法

谢东,龚劬,陈小彪

重庆大学数学与统计学院重庆401331;重庆大学数学与统计学院重庆401331;重庆大学数学与统计学院重庆401331

出版日期:2018-11-14 发布日期:2018-11-14

Split Bregman Method of Image Segmentation Based on KFCM and Improved CV Model

XIE Dong,GONG Qu and CHEN Xiao-biao

Online:2018-11-14 Published:2018-11-14

摘要/Abstract

摘要： 针对基于梯度变化的水平集图像分割方法对噪声敏感、计算效率不高、分割结果依赖初始值等问题,提出了一种基于KFCM与改进CV模型的Split Bregman图像分割方法。该算法首先通过核模糊C均值的聚类方法确定出感兴趣区域作为分割初始值,然后采用Split Bregman方法来提高CV模型的迭代计算时间效率。实验结果表明, 所提算法不仅保持了CV模型图像分割算法的优势,而且在抗噪性能和分割效率方面有明显效果。

关键词: KFCM算法,CV模型,图像分割,Split Bregman方法中图法分类号O245文献标识码A

Abstract: Aiming at the problems of the sensitivity to noise,the low computational efficiency and the segmentation result depended on heavily the initial value,we put forward an image segmentation method based on KFCM and improved CV model.Firstly,the average nuclear fuzzy clustering method was used to determine the interest area as the initial value in the algorithm.Then we improved the efficiency of iterative calculation of the CV model in calculation and time by the Split Bregman method.The experimental results show that this algorithm not only keeps the advantage of image segmentation algorithm,but also has obvious effect on the noise performance and segmentation efficiency．

Key words: KFCM agorithm,CV model,Image segmentation,Split Bregman method

谢东,龚劬,陈小彪. 基于KFCM与改进CV模型的Split Bregman图像分割方法[J]. 计算机科学, 2014, 41(Z6): 153-155. https://doi.org/

XIE Dong,GONG Qu and CHEN Xiao-biao. Split Bregman Method of Image Segmentation Based on KFCM and Improved CV Model[J]. Computer Science, 2014, 41(Z6): 153-155. https://doi.org/

参考文献

[1] Mumford D.Optimal approximations by piecewise smooth functions and associated variational problems[J].Commuications on Pure and Applied Mathematics,1989,2(5):577-685
[2] Chan T F.Active contours without edges[J].IEEE Transac-tions on Image Processing,2001,0(2):266-277
[3] 李伟斌,高二,宋松和.一种全局最小化的图像分割方法[J].电子与信息学报,2013,5(4):792-793
[4] 宋新,罗军,等.基于快速水平集算法的图像分割方法[J].信号处理,2008,4(3):423-424
[5] 康家银,纪志成,等.一种核模糊C均值聚类算法及其应用[J].仪器仪表学报,2010,1(7):1658-1660
[6] 朱晓舒,孙权森,等.基于凸优化的自适应CV模型[J].计算机应用研究,2012,9(2):780-781
[7] 王凯,贺国平,等.改进的模糊核C-均值算法[J].微电子学与计算机,2006,3(12):142-145
[8] 于剑,程乾生.关于FCM算法中权重指数m的一点注记[J].电子学报,2003,3(3):2-3
[9] 吴一全,郝亚斌,等.基于KFCM和改进CV模型的海面溢油SAR图像分割[J].仪器仪表学报,2012,3(12):2814-2815
[10] 杨青,何明一.改进CV模型的医学图像分割[J].计算机工程与应用,2010,6(17):196-198
[11] Caselles V,Catte F,Coll T,et al.A geometric model for active contours in image Proces-sing[J].IEEE Trans on image processing,2001,0(2):266-268
[12] 龚劬,王迎龙,等.改进CV模型图像分割的Split-Bregman算法[J].计算机工程与应用,2013,3(4):2-4

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed