Adaptive Diffusion Flow for Parametric Active Contours

This paper proposes a novel external force for active contours, called adaptive diffusion flow (ADF). We reconsider the generative mechanism of gradient vector flow (GVF) diffusion process from the perspective of image restoration, and exploit a harmonic hyper surface minimal function to substitute smoothness energy term of GVF for alleviating the possible leakage problem. Meanwhile, a ∞- laplacian functional is incorporated in the ADF framework to ensure that the vector flow diffuses mainly along normal direction in homogenous regions of an image. Experiments on synthetic and real images demonstrate the good properties of the ADF snake, including noise robustness, weak edge preserving, and concavity convergence.