A Noise-Resistant Fuzzy Kohonen Clustering Network Algorithm for Color Image Segmentation

摘要：

Fuzzy Kohonen clustering network(FKCN) is a kind of self-organizing fuzzy neural network,it shows great superiority in processing the ambiguity and uncertainty of image.But FKCN will encounter some difficulties when used for real noisy color images and medical Sublingual vein color images segmentation. To overcome this defect ,an improved FKCN algorithm is presented in this paper,which a new measurement of distance,the biologic lateral-inhibition mechanism and an improved cut-set method are used to reduce the effect of noisy pixels.In the end, the improved algorithm will be used for the segmentation of noisy color image and medical Sublingual vein color image. The experiments show that the improved algorithm can segment both noisy color image and medical Sublingual vein color image more effectively and provide more robust segmentation results.

关键词： image segmentation fuzzy clustering robustness Kohonen network

作者: Bosheng Lu Yuke Wei Jiangping Li

作者单位: Department of Computer Guangdong University of Technology Guangzhou,China Department of Material and Energy Source, Guangdong University of Technology Guangzhou,China

会议类型: 国际会议

会议名称: 第四届国际计算机新科技与教育学术会议(2009 4th International Conference on Computer Science & Education)

会议地点: 南京

会议语种:英文

页码: 44-48

在线出版日期: 2009-07-25（万方平台首次上网日期，不代表论文的发表时间）