Journal of Software:2014.25(11):2675-2689

(智能感知与图像理解教育部重点实验室(西安电子科技大学), 陕西 西安 710071)
Image Segmentation Based on Rough Set and Differential Immune Fuzzy Clustering Algorithm
MA Wen-Ping,HUANG Yuan-Yuan,LI Hao,LI Xiao-Ting,JIAO Li-Cheng
(Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China (Xidian University), Xi'an 710071, China)
Chart / table
Similar Articles
Article :Browse 2264   Download 2322
Received:March 15, 2013    Revised:November 11, 2013
> 中文摘要: 提出了基于粗糙集模糊聚类与差分免疫克隆聚类的图像分割算法.该算法在差分免疫克隆聚类算法的基础上,通过引入粗糙集模糊聚类,将差分免疫克隆聚类算法中的硬聚类变成模糊聚类,从而获得更丰富的聚类信息.具体来说,由于粗糙集的优势是处理不确定的数据,因此,加入粗糙集模糊聚类后更有利于算法解决不确定性问题.通过对9幅图像分割实验结果与4种算法的对比,验证了该算法在聚类性能稳定性方面的优越性,结果还同时证明了该算法具有更高的分割正确率和更好的分割结果.
中文关键词: 粗糙集  差分免疫克隆  图像分割
Abstract:In this paper, a new method based on rough-fuzzy set and differential immune clone clustering algorithm (DICCA) for image segmentation is proposed. By replacing hard clustering with fuzzy clustering through incorporating rough-fuzzy set into DICCA, this algorithm can obtain more abundant clustering information. Specially, as the advantage of rough set is processing uncertain data, the proposed algorithm is more conducive to solve the uncertainty problem. In experiments, nine images are used for segmentation and four algorithms are chosen for comparison to validate the performance in the clustering stability. The experimental results show that the algorithm has higher segmentation accuracy and better segmentation results.
文章编号:     中图分类号:    文献标志码:
基金项目:国家自然科学基金(61203303, 61202176, 61272279) 国家自然科学基金(61203303, 61202176, 61272279)
Foundation items:
Reference text:


MA Wen-Ping,HUANG Yuan-Yuan,LI Hao,LI Xiao-Ting,JIAO Li-Cheng.Image Segmentation Based on Rough Set and Differential Immune Fuzzy Clustering Algorithm.Journal of Software,2014,25(11):2675-2689