We propose a image segmentation method which couples support vector machine and mumford-shah active contour model

where the advantages of supervised learning classification and the global region distribution information can be exploited to enhance the performance.A new region-based image energy term in curve evolution based on the output of support vector machine classifier is presented.It is more robust than classical active contour because it takes into account the image segmentation knowledge of human being and interactive operation as well.In order to improve the segmentation speed

support vector machine also be used to obtain initial contour firstly.Experimental results have demonstrated the flexibility and better performance of this new image segmentation method.