基于改进Mumfold-Shah模型的图像分割算法

Image Segmentation Based on Mumfold-Shah Model

针对传统图像分割方法中由于边缘模糊难以取得理想分割效果的问题,提出了一种基于改进Mumfold-Shah模型的图像分割算法.结合模糊C均值聚类算法对Mumfold-Shah模型进行改进,以提高图像的分割速度和分割的鲁棒性.实验结果表明:该算法具有可行性和有效性.

According to the fact that the traditional method for image segmentation is not suitable for medical image, a medical image segmentation algorithm based on modified Mumfold-Shah model with rapid level set method is presented. Fuzzy C-means clustering algorithm is used to modify the Mumfold-Shah model, which improves the speed and robustness of the image segmentation. The experimental results indicate the feasibility and validity of this algorithm.