Computer Science ›› 2015, Vol. 42 ›› Issue (Z6): 190-194.

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Research on Improved Local Fuzzy C-means Clustering Segmentation Algorithm

LIU Meng-jiao and WU Cheng-mao   

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

Abstract: In order to improve the complex image segmentation precision and noise resistance, fuzzy clustering segmentation of fully considering the pixel neighborhood information has caused scholars great attention.For the robust local fuzzy C-means clustering algorithms proposed by Krinidis and Gong Mao-Guo et al,the iterative formulas of their clustering centers lack rigorous mathematical theory,and Lagrange multiplier method was used to turn objective function and constraints of robust fuzzy local C-means clustering algorithm into unconstrained optimization problem.The partial derivative equations was made equal to zero to obtain the membership degree,and the clustering center new expressions was also gained.Then the new algorithm can be applied.The proposed clustering segmentation algorithm was used to segment clustering artificial synthetic graphics and remote sensing image.The results show that the proposed segmentation clustering algorithm is reasonable,and the new robust fuzzy local C-means clustering segmentation algorithm is more suitable for complex images segmentation.

Key words: Fuzzy clustering,Robust fuzzy C-means clustering,Image segmentation

[1] 王骏,王士同,邓赵红.聚类分析研究中的若干问题[J].控制与决策,2012,7(3):321-328
[2] Bezdek J C.Pattern Recognition with Fuzzy Objective Function Algorithms[M].New York:Plenum Press,1981:95-107
[3] 高新波,谢维信.模糊聚类理论发展及应用的研究进展[J].科学通报,1999,4(21):2249-2251
[4] Huang H C,Chuang Y Y,Chen C S.Multiple Kernel FuzzyClustering[J].IEEE Trans on Fuzzy Ssytems,2012,0(1):120-134
[5] Lzakian H,Pedrycz W,Jamal I.Clustering spatiotemporal data:An augmented fuzzy c-means[J].IEEE Trans on Fuzzy Systems,2013,1(5):855-868
[6] Pal N.R,Sarkar K.What and when can we gain from the kernel versions of C-means algorithm?[J].IEEE Trans on Fuzzy Systems,2014,2(2):363-379
[7] Ji Z X,Xia Y,Sun Q S,et al.Interval-valued possibilistic fuzzy c-means clustering algorithms[J].Fuzzy Sets and Systems,2014,3(16):138-156
[8] Zarinbal M,Fazel Zarandi M H,Turksen I B.Interval Type-2Relative Entropy Fuzzy C-Means clustering[J].Information Sciences,2014,2(10):49-72
[9] Lin P L,Huang P W,Kuo C H,et al.A size-insensitive integrity-based fuzzy c-means method for data clustering[J].Pattern Recognition,2014,5(47):2042-2056
[10] Zarinbal M,Fazel Zarandi M H,Turksen I B.Relative entropy fuzzy c-means clustering[J].Information Science,2014,0(1):74-97
[11] 皋军,孙长银,王士同.具有模糊聚类功能的双向二维无监督特征提取方法[J].自动化学报,2012,8(4):549-562
[12] Pedrycz W,Aandrzej B.An optimization of allocation of information granularity in the interpretation of data structures:Toward granular fuzzy clustering[J].IEEE Trans on Systems,Man,and Cybernetics,Part B,2012,2(3):582-590
[13] Saha I,Maulik U,Bandyopadhyay S.SVMeFC:SVM Ensemble Fuzzy Clustering for Satellite Image Segmentation[J].IEEE Geoscience and Remote Sensing Letters,2012,9(1):52-55
[14] Maji P,Paul S.Rough-Fuzzy Clustering for Grouping Functional-ly Similar Genes from Microarray Data[J].IEEE Trans on Computational Biology and Bioinformatics,2013,0(2):286-299
[15] Banerjee T,Keller J M,Skubic M,et al.Day or Night Activity Recognition From Video Using Fuzzy Clustering Techniques[J].IEEE Trans on Fuzzy Systems,2014,2(3):483-493
[16] Gong M G,Su L Z,Jia M,et al.Fuzzy Clustering With a Modified MRF Energy Function for Change Detection in Synthetic Aperture Radar Images[J].IEEE Trans on Fuzzy Systems,2014,2(1):98-109
[17] Zhong Y F,Ma A L,Zhang L P.An Adaptive Memetic Fuzzy Clustering Algorithm With Spatial Information for Remote Sensing Imagery[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2014,7(4):1235-1248
[18] 刘健庄.基于二维直方图的图象模糊聚类分割方法[J].电子学报,1992,0(9):404-46
[19] 原小平,杨明.基于三维直方图加权的模糊聚类图像分割方法[J].电脑开发与应用,2010,3(5):18-20
[20] 裴继红,谢维信,王大勇.基于空间信息及灰度信息的塔型模糊聚类图像分割[J].中国体视学与图像分析,1996,1(1/2):1-5
[21] Liew A W C,Leung S H,Lau W H.Fuzzy image clustering incorporating spatial continuity[J].IEEE Proc.Vis.on Image Signal Process,2000,147(2):185-192
[22] 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 Trans on Medical Imaging,2002,1(3):193-199
[23] Chen S C,Zhang D Q.Rubust image segmentation using FCM with spatial constraints based on new kernel-induced distance meansure[J].IEEE Trans on Systems,Man,and Cybernetics,Part B,2004,4(4):1907-1916
[24] Chuang K S,Tzeng H L,Chen S,et al.Fuzzy c-means clustering with spatial information for image segmentation[J].Computerized Medical Imaging and Graphics,2006,0(1):9-15
[25] Yang Y,Huang S Y.Image Segmentation by fuzzy C-meansclustering algorithm with a novel penalty term[J].Computing and Informatics,2007,6(1):17-31
[26] Krinidis S,Chatzis V.A robust fuzzy local information C-means clustering algorithm[J].IEEE Trans on image Processing,2010,9(5):1328-1337
[27] Gong M G,Liang Y,Shi J,et al.Fuzzy C-means clustering with local information and kernel metric for image segmentation[J].IEEE Trans on Image Processing,2013,2(2):573-584
[28] Xiang D L,Tang T,Hu C B,et al.A Kernel Clustering Algorithm With Fuzzy Factor:Application to SAR Image Segmentation[J].IEEE Geoscience and Remote Sensing letters,2014,1(7):1290-1294
[29] Murugeswari M,Gayathri M.Tumor detection in MRI brain ima-ge segmentation using phase congruency modified fuzzy C-mean algorithm[J].International Journal of Innovative Science,Engineering& Technology,2014,1(2):190-194
[30] Celik T,Lee H K.Comments on “A Robust Fuzzy Local Information C-Means Clustering Algorithm”[J].IEEE Trans on Image Processing,2013,2(3):1258-1261
[31] Bensaid A M,Hall L O,Bezdek J C,et al.Validity-Guided(Re)Clustering with Applications to Image Segmentation[J].IEEE Trans on Fuzzy System,1996,4(2):112-122
[32] 吴成茂,范九伦.数据分类效果[J].模糊系统与数学,2002,6(增刊):200-203

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