A novel robust and fast Segmentation of the Color Images using Fuzzy Classification C-means
This paper brings out a method for segmentation of color images based on fuzzy classification. It proceeds in a first step by a fine segmentation using the algorithm of fuzzy c-means (FCM). The method then applies a test fusion of fuzzy classes. The result is a coarse segmentation, where each region is the union of elementary regions grown from FCM. The fuzzy CMeans (FCM) clustering is an iterative partitioning method that produces optimal c-partitions, the standard FCM algorithm takes a long time to partition a large data set. The proposed FCM program must read the entire data set into a memory for processing. Our results show that the system performance is robust to different types of images.
Segmentation Classification FuzzyLogic FCM Merge regions Optimal c-partitions
Mohamed Lamine Toure Zou Beiji Felix Musau
School of Information Science and Engineering Central South University Changsha, 410083, Hunan, China
国际会议
上海
英文
341-344
2010-06-22（万方平台首次上网日期，不代表论文的发表时间）