改进模糊C均值算法在民族服饰图像分割中的应用  

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

作　　者：王禹君 周菊香[2] 徐天伟[3] 

机构地区：[1]云南师范大学信息学院,昆明650500 [2]云南师范大学民族教育信息化教育部重点实验室,昆明650500 [3]云南师范大学研究生处,昆明650500

出　　处：《计算机工程》2017年第5期261-267,274,共8页Computer Engineering

基　　金：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)

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。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 $1, 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.

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 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]