基于FCM聚类的图像分割算法
|
摘要
为提高现有模糊C均值聚类算法(FCM)对噪声图像分割的效果和稳定性,提出一种基于FCM的图像分割算法。利用非局部空间信息构建和图像,根据和图像的直方图,自动选择初始化聚类中心,通过求取目标函数极小值完成图像分割。理论分析和实验结果表明,该算法比现有算法更加有效和稳定,对噪声图像有更强的鲁棒性。
To improve the validity and stability of the existing fuzzy C-means clustering algorithm(FCM) for noise image segmentation,a segmentation algorithm based on FCM was presented.A sum image was set up using non-local information.Initial clustering center was chosen automatically in accordance with histogram of the sum image.The segmentation result was determined by minimizing the object function.Both theoretical analysis and experimental results show that the proposed algorithm is more efficient and stable than the existing algorithms,and has stronger robustness to the noise image.
To improve the validity and stability of the existing fuzzy C-means clustering algorithm(FCM) for noise image segmentation,a segmentation algorithm based on FCM was presented.A sum image was set up using non-local information.Initial clustering center was chosen automatically in accordance with histogram of the sum image.The segmentation result was determined by minimizing the object function.Both theoretical analysis and experimental results show that the proposed algorithm is more efficient and stable than the existing algorithms,and has stronger robustness to the noise image.
引文
[1]Gong M,Liang Y,Shi J,et al.Fuzzy c-means clustering with local information and kernel metric for image segmentation[J].IEEE Transactions on Image Processing,2013,22(2):573-584.
[2]LIU Jian,CHENG Yinglei,SUN Jida[J].Modified FCM SAR image segmentation method based on GLCM feature[J].Computer Engineering and Design,2012,33(9):3502-3506(in Chinese).[刘健,程英蕾,孙纪达.基于GLCM特征的改进FCM的SAR图像分割方法[J].计算机工程与设计,2012,33(9):3502-3506.]
[3]Feng J,Jiao LC,Zhang X,et al.Robust non-local fuzzy c-means algorithm with edge preservation for SAR image segmentation[J].Signal Processing,2013,93(2):487-499.
[4]Zhao F,Liu H,Fan J.A multiobjective spatial fuzzy clustering algorithm for image segmentation[J].Applied Soft Computing,2015,30(C):48-57.
[5]Tan KS,Isa NAM,Lim WH.Color image segmentation using adaptive unsupervised clustering approach[J].Applied Soft Computing,2013,13(4):2017-2036.
[6]Cai W,Chen S,Zhang D.Fast and robust fuzzy c-means clustering algorithms incorporating local information for image segmentation[J].Pattern Recognition,2007,40(3):825-838.
[7]Gong M,Zhou Z,Ma J.Change detection in synthetic aperture radar images based on image fusion and fuzzy clustering[J].IEEE Transactions on Image Processing,2012,21(4):2141-2151.
[8]Ji Z,Xia Y,Chen Q,et al.Fuzzy c-means clustering with weighted image patch for image segmentation[J].Applied Soft Computing,2012,12(6):1659-1667.
[9]Ma J,Tian D,Gong M,et al.Fuzzy clustering with non-local information for image segmentation[J].International Journal of Machine Learning and Cybernetics,2014,5(6):845-859.
[10]Wu J,Qi F,Shi G.Image quality assessment based on improved structural similarity[G].LNCS 7674:Pacific-Rim Conference on Advances in Multimedia Information Processing.Springer Berlin Heidelberg,2012:153-163.
[11]Hu X.Improved fuzzy c-means algorithm for image segmentation[J].Journal of Electrical and Electronic Engineering,2015,3(1):1-5.
[2]LIU Jian,CHENG Yinglei,SUN Jida[J].Modified FCM SAR image segmentation method based on GLCM feature[J].Computer Engineering and Design,2012,33(9):3502-3506(in Chinese).[刘健,程英蕾,孙纪达.基于GLCM特征的改进FCM的SAR图像分割方法[J].计算机工程与设计,2012,33(9):3502-3506.]
[3]Feng J,Jiao LC,Zhang X,et al.Robust non-local fuzzy c-means algorithm with edge preservation for SAR image segmentation[J].Signal Processing,2013,93(2):487-499.
[4]Zhao F,Liu H,Fan J.A multiobjective spatial fuzzy clustering algorithm for image segmentation[J].Applied Soft Computing,2015,30(C):48-57.
[5]Tan KS,Isa NAM,Lim WH.Color image segmentation using adaptive unsupervised clustering approach[J].Applied Soft Computing,2013,13(4):2017-2036.
[6]Cai W,Chen S,Zhang D.Fast and robust fuzzy c-means clustering algorithms incorporating local information for image segmentation[J].Pattern Recognition,2007,40(3):825-838.
[7]Gong M,Zhou Z,Ma J.Change detection in synthetic aperture radar images based on image fusion and fuzzy clustering[J].IEEE Transactions on Image Processing,2012,21(4):2141-2151.
[8]Ji Z,Xia Y,Chen Q,et al.Fuzzy c-means clustering with weighted image patch for image segmentation[J].Applied Soft Computing,2012,12(6):1659-1667.
[9]Ma J,Tian D,Gong M,et al.Fuzzy clustering with non-local information for image segmentation[J].International Journal of Machine Learning and Cybernetics,2014,5(6):845-859.
[10]Wu J,Qi F,Shi G.Image quality assessment based on improved structural similarity[G].LNCS 7674:Pacific-Rim Conference on Advances in Multimedia Information Processing.Springer Berlin Heidelberg,2012:153-163.
[11]Hu X.Improved fuzzy c-means algorithm for image segmentation[J].Journal of Electrical and Electronic Engineering,2015,3(1):1-5.