A Fast Level Set Method for Image Segmentation Based on Gaussian Mixture Models

The level set method(LSM) for image segmentation is used to solve a time-varying partial differential equation, which may require too much calculation time by using the calculus of variation method. Aiming at the problem, this paper proposes a fast level set method for image segmentation. Basing on fuzzy clustering level set method(FCM-LSM), the proposed algorithm utilizes Gaussian mixture models(GMM) to modify the membership loss function. And then, the lattice Boltamann method(LBM) is used to solve the level set equation. Experimental results show that the proposed algorithm is effective in efficiency and segmentation results.