In the traditional variational level set method for image segmentation, the evolving level set function needs periodical re-initialization to keep it close to a signed distance function during the evolution. It remains many serious problems such as when and how to apply the re-initialization. Li presented a new variational formulation that forces the level set function to be close to a signed distance function by adding an internal energy into the energy functional, and therefore completely eliminates the need of the expensive re-initialization procedure. We present a new image segmentation model based on variational level set method. It also completely eliminates the need of the re-initialization by adding a new and simple internal energy into the energy functional. In addition, a new external energy by redefining the edge stopping function is introduced, which makes the proposed model more robust to noisy image segmentation. The experimental results show that, compared with Li model, our model has some superiority in the convergence speed andsegmentation quality for noisy image.