结合隶属度空间约束的模糊聚类图像分割
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摘要
针对传统模糊聚类分割方法未考虑邻域像素隶属度空间关系的问题,该文提出了一种结合隶属度空间约束的模糊聚类图像分割方法。采用邻域之间的空间约束来限制隶属度值,解决同质区域中可能出现的噪声问题,从而提高分割精度。分别对模拟图像和彩色图像进行分割实验,并与未结合隶属度空间约束的分割结果进行对比分析。实验表明,此方法实现了对隶属度的空间约束,验证了本文算法的有效性。
To the problems of the traditional fuzzy clustering segmentation method did not take the spatial relationship of membership degree of the neighborhood pixels into consideration,this paper proposed a new method that a fuzzy clustering image segmentation algorithm was based on the spatial constraint of membership degree.The spatial constraint of neighborhood was used to limit the membership value to solve the possible noise problems in homogeneous regions,so as to improve the segmentation accuracy.The proposed algorithm was performed on the simulated image and some color images,and the results were compared with those obtained without spatial constraint of membership degree.The experiment results showed that this method realized the membership of space constraints and verifies the effectiveness of the proposed algorithm.
To the problems of the traditional fuzzy clustering segmentation method did not take the spatial relationship of membership degree of the neighborhood pixels into consideration,this paper proposed a new method that a fuzzy clustering image segmentation algorithm was based on the spatial constraint of membership degree.The spatial constraint of neighborhood was used to limit the membership value to solve the possible noise problems in homogeneous regions,so as to improve the segmentation accuracy.The proposed algorithm was performed on the simulated image and some color images,and the results were compared with those obtained without spatial constraint of membership degree.The experiment results showed that this method realized the membership of space constraints and verifies the effectiveness of the proposed algorithm.
引文
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[17]赵雪梅,李玉,赵泉华.结合高斯回归模型和隐马尔可夫随机场的模糊聚类图像分割[J].电子与信息学报,2014,36(11):2730-2736.(ZHAO Xuemei,LI Yu,ZHAO Quanhua.Image segentation by fuzzy clustring algorithm combining hidden Markov random field and Gaussian regression model[J].Journal of Electronics&Information Technology,2014,36(11):2730-2736.)
[18]LIU H C,JENG B C,YIH J M,et al.Fuzzy C-means algorithm based on standard Mahalanobis distances[J].Proceedings of the International Symposium on Information Proces,2009,15:581-595.
[19]李旭超,刘海宽,王飞,等.图像分割中的模糊聚类方法[J].中国图象图形学报,2012,17(4):447-457.(LI Xuchao,LIU Haikuan,WANG Fei,et al.The survey of fuzzy clustering method for image segmentation[J].Journal of Image and Graphics,2012,17(4):447-457.)
[2]刘金尧,纪则轩.鲁棒空间约束的模糊聚类图像分割[J].中国图象图形学报,2014,19(10):1438-1448.(LIU Jinyao,JI Zexuan.Robust spatial factor based fuzzzy clustering for image segmentation[J].Journal of Image and Graphics,2014,19(10):1438-1448.)
[3]仲崇峰,刘智,杨阳,等.改进的基于邻域隶属度约束的FCM图像分割算法[J].吉林大学学报(信息科学版),2013,31(6):627-633.(ZHONG Chongfeng,LIU Zhi,YANG Yang,et al.Improved FCM algorithm based on neighboring membership constraint for image segmentation[J].Journal of Jilin University(Information Science Edition),2013,31(6):627-633.)
[4]武小红,周建江.可能性模糊C-均值聚类新算法[J].电子学报,2008,36(10):1996-2000.(WU Xiaohong,ZHOU Jianjiang.A novel possibilistic fuzzy C-means clustering[J].Acta Electronica Sinica,2008,36(10):1996-2000.)
[5]徐少平,刘小平,李春泉,等.基于区域特征分析的快速FCM图像分割改进算法[J].模式识别与人工智能,2012,25(6):987-995.(XU Shaoping,LIU Xiaoping,LI Chunquan,et al.An improved fast FCM image segmentation algorithm based on region feature analysis[J].Pattern Recognition and Artificial Intelligence,2012,25(6):987-995.)
[6]KANNAN S R,RAMATHILAGAM S A,PANDIYARAJAN R.Effective fuzzy C-means based kernel function in segmenting medical images[J].Computers in Biology and Medicine,2010,40(6):572-579.
[7]CHEN Z,QI Z,MENG F,et al.Image segmentation via improving clustering algorithms with density and distance[J].Procedia Computer Science,2015,55:1015-1022.
[8]DUNN J C.Well-separated clusters and the optimal fuzzy partition[J].Journal of Cybernetic,1974,4(1):95-104.
[9]BEZDEK J C.Pattern recognition with fuzzy objection function algorithms[M].New York:Plenum Press,1981.
[10]刘兵,夏士雄,周勇,等.基于样本加权的可能性模糊聚类算法[J].电子学报,2012,40(2):371-375.(LIU Bing,XIA Shixiong,ZHOU Yong,et al.A sampleweighted possilibistic fuzzy clustering algorithm[J].Acta Electronica Sinica,2012,40(2):371-375.)
[11]纪则轩,陈强,孙权森,等.各向异性权重的模糊C均值聚类图像分割[J].计算机辅助设计与图形学学报,2009,21(10):1451-1459.(JI Zexuan,CHEN Qiang,SUN Quansen,et al.Image segmentation with anisotropic weighted fuzzy C-means clustering[J].Journal of Computer-Aided Design &Computer Graphics,2009,21(10):1451-1459.)
[12]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,2013,41(3):526-531.(CHEN Shengguo,SUN Zhengxing,ZHOU Jie.A segmentation method for stratum image based on FCM and random walks[J].Acta Electronica Sinica,2013,41(3):526-531.)
[13]李艳灵,沈轶.基于空间邻域信息的FCM图像分割算法[J].华中科技大学学报(自然科学版),2009,37(6):56-59.(LI Yanling,SHEN Yi.Fuzzy c-means algorithm based on the spatial information for image segmentation[J].Journal of Huazhong University of Science and Technology(Nature Science Edition),2009,37(6):56-59.)
[14]AHMED M,YAMANY S,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.
[15]ICHIHASHI H,MIYAGISHI K,HONDA K.Fuzzy c-means clustering with regularization by K-L information[C]//IEEE International Conference on Fuzzy Systems.[S.l.:s.n.],2001:924-927.
[16]CHATZIS S P,VARVARIGOU T A.A fuzzy clustering approach toward hidden Markov random field models for enhanced spatially constrained image segmentation[J].IEEE Transactions on Fuzzy Systems,2008,16(5):1351-1361.
[17]赵雪梅,李玉,赵泉华.结合高斯回归模型和隐马尔可夫随机场的模糊聚类图像分割[J].电子与信息学报,2014,36(11):2730-2736.(ZHAO Xuemei,LI Yu,ZHAO Quanhua.Image segentation by fuzzy clustring algorithm combining hidden Markov random field and Gaussian regression model[J].Journal of Electronics&Information Technology,2014,36(11):2730-2736.)
[18]LIU H C,JENG B C,YIH J M,et al.Fuzzy C-means algorithm based on standard Mahalanobis distances[J].Proceedings of the International Symposium on Information Proces,2009,15:581-595.
[19]李旭超,刘海宽,王飞,等.图像分割中的模糊聚类方法[J].中国图象图形学报,2012,17(4):447-457.(LI Xuchao,LIU Haikuan,WANG Fei,et al.The survey of fuzzy clustering method for image segmentation[J].Journal of Image and Graphics,2012,17(4):447-457.)