基于空间信息的直觉模糊C-均值图像分割算法
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作者单位:

(1.西安邮电大学 通信与信息工程学院,西安 710061; ;2.福建师范大学 光电与信息工程学院,福州 350007)

作者简介:

马姣婷(1990-),女,陕西渭南人,硕士研究生,主要从事信息安全方向的研究。 [FQ)]

基金项目:

国家自然科学基金资助项目(61571361);陕西省科技计划资助项目(2014KJXX-72);陕西省教育厅科学研究计划资助项目(15JK1658)。


Image Segmentation Algorithm Based on Spatial Information of Intuitionstic Fuzzy C-Means
Author:
Affiliation:

(1.School of Communication and Information Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710061, China;2.College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou 350007, China)

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    摘要:

    针对模糊C-均值聚类算法的单一隶属度不能充分描述图像不确定性,且聚类过程中忽略像素空间关系的问题,提出一种基于空间信息的直觉模糊C-均值算法;该算法选取3×3的模板计算邻域像素灰度均值;并引入权重项,来控制灰度信息和空间信息各自所占的比重,同时用犹豫度更新直觉模糊集的隶属度函数;对常用标准图像的仿真结果表明,该算法能更好地保留图像细节信息,得到更加理想的图像分割效果。

    Abstract:

    In view of the Fuzzy C-Means clustering algorithm’s single membership degree can’t fully describe the images uncertainty, and ignore the pixel spatial relations in the process of clustering, here put forward a kind of image segmentation algorithm based on spatial information and intuitionistic fuzzy sets. The algorithm select the template of 3×3 computing neighborhood pixels within the grayscale average; and introduce the weight to control the gray information and spatial information, at the same time using hesitation degree to update the membership function of intuitionistic fuzzy sets. In view of the common standard image simulation experiment results show that the algorithm can keep the details of the image information better and obtain a more ideal image segmentation results.

    参考文献
    [1] 徐胜军, 韩九强, 刘光辉.基于马尔可夫随机场的图像分割方法综述.计算机应用研究, 2013,0(9):2576-2582.
    [2] 田小平, 侯伟建, 吴成茂.改进的核空间直觉模糊C-均值聚类分割算法.西安邮电大学学报, 2015,0(6):45-50.
    [3] 李琳, 范九伦, 赵凤.模糊 C-均值聚类图像分割算法的一种改进.西安邮电大学学报, 2014,9(5):56-60.
    [4] 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.Medical Imaging, IEEE Transactions on, 2002,1(3):193-199.
    [5] Chen S, Zhang D.Robust image segmentation using FCM with spatial constraints based on new kernel-induced distance measure.Systems, Man, and Cybernetics, Part B:Cybernetics, IEEE Transactions on, 2004,4(4):1907-1916.
    [6] Atanassov K T.Intuitionistic fuzzy sets.Fuzzy sets and Systems, 1986,0(1):87-96.
    [7] Qinli Z, Xiuna Z, Yafan Y, et al.Robust Image Segmentation Using FCM Based on New Kernel-Induced Distance Measure with Membership Constraints.中国四川成都, F, 2011.
    [8] Li Y, Shen Y.Fuzzy c-means clustering based on spatial neighborhood information for image segmentation.Systems Engineering and Electronics, 2010,1(2):323-328.
    [9] 王昭, 范九伦, 娄昊, 等.一种融入局部信息的直觉模糊C-均值聚类图像分割算法.计算机应用研究, 2014(9):2864-2866+2872.[ZK)]
    [10] 支晓斌, 范九伦.一种广义模糊补运算和相应的广义模糊熵.模糊系统与数学, 2008,2(1):96-102.
    [11] Chaira T.A Novel Intuitionistic Fuzzy c Means Color Clustering on Human Cell Images.proceedings of the World Congress on Nature & Biologically Inspired Computing, NaBIC 2009.Coimbatore, India, F, 2009.
    [12] 兰蓉, 马姣婷.基于直觉模糊C-均值聚类算法的图像分割 [EB/OL].西安邮电大学学报, http://www.cnki.net/kcms/detail/61.1493.TN.20160321.1025.002.html.
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引用本文

马姣婷,贾世英,吴伟霖.基于空间信息的直觉模糊C-均值图像分割算法计算机测量与控制[J].,2016,24(9):195-197, 202.

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  • 收稿日期:2016-03-04
  • 最后修改日期:2016-04-25
  • 在线发布日期: 2016-09-28
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