利用模糊特征向量表示图像上各区域上的特性，然后把模糊特征向量集成到简化Mumford-Shah模型。这种推广的Mumford-Shah模型与原来的Mumford-Shah模型相比能包含更多的图像信息，增强了图像分割的性能，而复杂程度却没有提高。原来的模型是推广模型的特例。对弱边缘、凹凸区域和复杂背景的图像能较好地分割。人工合成图像、真实图像的实验说明推广模型对图像分割的有效性。

Fuzzy feature vector has been used to represent the characteristics of image on different regions. The fuzzy feature vector has been integrated into Mumford-Shah model for the image segmentation. The generalized Mumford-Shah model has contained more information of image, enhanced capability of segmentation image and not increased complexity in comparison with original model. The original model is a particular case of the generalized model. The generalized model provides well segmentation to weak edges， concavo-convex region and complexity background image. Experimental results of applying the scheme to artificial and real images demonstrate its segmentation power.