关键词: K均值算法, 支持向量聚类算法（SVC）, 图像分割

Abstract: Using the benefit of support vector clustering which supplies’ clustering accuracy，few parameters and unsupervised learning，a method of SVC image segmentation is proposed.Firstly，this method divides data sets into some pieces of data block and carries through supporting vector clustering.Secondly，the mean value of per cluster is considered as the sample data of K-means and goes through clustering.At last，the received result is incorporated.Experimental results demonstrate that this method not only has a good result for small targets with more yawp，but also automatically determines threshold values，which are artificial selections in the past.The robustness of image segmentation has been improved and the performance becomes steadier.The proposed methods can segment image effectively.

Key words: K-means algorithm, Support Vector Clustering（SVC） algorithm, image segmentation