Weighed FCM algorithm with an application in color image segmentation

• Main Authors: TSAI, CHENG-LIN., 蔡政霖
• Other Authors: Hung, Wen-Liang
• Format: Others
• Language: en_US
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/398w7x

碩士 === 國立清華大學 === 應用數學系所 === 105 === Fuzzy c-Means Algorithm (FCM Algorithm) is a commonly used method of clustering analysis. When there are noise variables in the data, the error rate of the fuzzy c-means algorithm is relatively improved. How to choose the weight of the variable to reduce the error rate is an important issue. Based on this , this paper presents a new method of variable weight selection, called Covariance Matrix (CM) method. The simulation results show that the proposed variable selection method can effectively reduce the error rate of clustering. Finally , the proposed CM method is applied to color image segmentation. Keyword: Fuzzy C-Means Algorithm、feature-weight、Covariance Matrix、color image segmentation.