一种SVM与区域生长相结合的图像分割方法

作为一种全局门限处理方法,支持向量机图像分割方法不能完成对图像进行精细分割，其分割结果需要其他分割方法进一步处理。提出一种结合支持向量机和区域生长的交互式分割方法,不仅可有效剔除与感兴趣区域特征类似的非目标区域，而且把为SVM选择训练样本和为区域生长选择种子点两个步骤合二为一，从而提高了图像分割质量和交互式分割方法的自动分割能力。

Interactive segmentation method with SVM and region growing

The SVM segmentation method, as a kind of global thresholding, cannot segment the image finely. The results need to be post-processed by other segmentation approaches. In this paper, a new interactive segmentation method was proposed, which integrated the SVM and region growing. The proposed method can remove the regions of non-interest that have similar characteristics to regions of interest. Furthermore, it can combine the two procedures into one: the procedure of selecting samples for training SVM and the procedure of selecting seeds for region growing. As a result, the method improves the quality of segmentation and the performance of auto-segmentation.