Curvature-Independent Directional Diffusion and Modified Chan-Vese Active Contour Model

Segmentation under low SNR is a hard problem in image segmentation research and applications.Targeting at the accuracy deficiency problem of the state-of-art non-parametric active contour models under low SNR and high curvature conditions,a new curvature-independent directional diffusion based noise-proofing method for the active contour models is proposed from the perspective of devising the noise-proofing term.The proposed method preserves active contour's shape by introducing curvature-independent directional diffusion,and furthermore distinguishes target edges from noise with unregularized edge-stopping function.Active contour's convergence to high-curvature edges is guaranteed while noise interference is suppressed effectively.Furthermore,a modified Chan-Vese active contour model is proposed for image segmentation under low SNR conditions.The effectiveness of the proposed noise-proofing method and the modified Chan-Vese active contour model are certified by thorough experiments conducted.