Image Segmentation Technology Based On Weighted Intuitionistic Fuzzy Support Vector Machines

General fuzzy support vector machine is based on the distance from the sample to thegeometric center ofthe sample to determine the membership degree,that is likely to eliminatenoise points or outlier,and is also weaken the influence of the edge of classification ofsupport vector．If the different importance of sample is ignored,it could lead to importantsamples that are misclassified In order to overcome these problems effectively,a weightedintuitionistic fuzzy support vector machine that based on intuitionistic fuzzy support vectormachine is provided,the importance of samples is measured by the membership,intuitiveindex and weight,that made up the limitation of fuzzy support vector machine to determinethe membership by space distance singly,and the weighted intuitionistic fuzzy support vectormachine is applied to image segmentation Experimental results show that the weightedintuitionistic fuzzy support vector machine is applied to image segmentation that theclassification accuracy can be improved...