Image segmentation combining support vector machines with C-means
结合支持向量机与C均值聚类的图像分割

Image segmentation based on support vector machines(SVM) requires the user to provide the training data.The proposed method in this paper used C-means to obtain feature vectors and labels for training SVM.Firstly,image was divided into several regions and discrete wavelet transform was performed on each region in order to remove edged region.Secondly,after applying C-means to smooth region classification,the energy of region and labels were taken as training data of SVM(Support Vector Machine).Finally,image segmentation was performed using SVM classifier.Experimental results show that the method has good performance in image segmentation.Meanwhile,using one representative image for the training of SVM,the produced classifier can be applied to the set of similar images and 3D volume data.