C-V Level Set Model Based on the Gaussian Laplace Operator

The traditional Chan-Vese (C-V) model is sensitive to noise and inaccurate positioning of the edges in an image. This paper proposes a C-V model based on the Gaussian Laplace operator. By smoothing the image, the Gaussian smoothing function can reduce noise on the image segmentation. The Laplace operator can detect zero crossing points, and then determine the edge positions of the image. The experiments show that the proposed algorithm can achieve good segmentation effect.