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计算机工程

• 图形图像处理 • 上一篇    下一篇

改进模糊C均值算法在民族服饰图像分割中的应用

王禹君 a,周菊香 b,徐天伟 c   

  1. (云南师范大学 a.信息学院;b.民族教育信息化教育部重点实验室;c.研究生处,昆明650500)
  • 收稿日期:2016-07-20 出版日期:2017-05-15 发布日期:2017-05-15
  • 作者简介:王禹君(1991—),男,硕士研究生,主研方向为数字图像处理、民族文化数字化;周菊香,助理研究员、博士研究生;徐天伟,教授、博士。
  • 基金资助:
    国家自然科学基金(61462097,61262071);国家科技支撑计划项目(2013BAJ07B00);云南省科技厅应用基础研究计划项目(2014FD016)。

Application of Improved Fuzzy C-means Algorithm for Ethnic Costume Image Segmentation

WANG Yujun  a,ZHOU Juxiang  b,XU Tianwei  c   

  1. (a.College of Information; b.Key Laboratory of Education Informatization for Nationlties,Ministry of Education;c.Graduate Student Department,Yunnan Normal University,Kunming 650500,China)
  • Received:2016-07-20 Online:2017-05-15 Published:2017-05-15

摘要: 以少数民族服饰图像为分割对象,结合块截断算法设计思想,提出一种基于空间邻域的模糊C均值图像分割算法。利用方块截断编码理论将图像RGB颜色空间分量截断为6个分量,通过六维特征向量对民族服饰图像进行特征表示,将其作为算法输入进行聚类分割。实验结果表明,该算法在分割精度、划分系数和划分熵3个量化指标上的性能均优于FCM,FCM_S1和FCM_S2算法,对民族服饰图像的分割效果较好,尤其表现在对民族服饰具有代表性的特征元素区域分割上。

关键词: 民族服饰, 块截断编码, 图像分割, 空间邻域, 模糊C均值算法

Abstract: By taking the image of ethnic minority costumes as the segmentation object,based on block truncation theory,an algorithm for image segmentation based on spatial neighborhood of Fuzzy C-means(FCM) algorithm is proposed.Firstly,the Block Truncation Coding(BTC) theory is used to cut the image RGB color space into six components.Then,the six-dimensional feature vector is used to express the characteristics of the national costume image.Finally,this six-dimensional feature vector is used as the data input of the algorithm.Experimental results show that the performance of the proposed algorithm in this paper is better than FCM,FCM_S1,FCM_S2 in segmentation accuracy,partition coefficient and partition entropy.It has better performance on ethnic costume image segmentation,especially for typical elements of ethnic constume.

Key words: ethnic costume, Block Truncation Coding(BTC), image segmentation, spatial neighborhood, Fuzzy C-means(FCM) algorithm

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