Hybrid geodesic region-based active contours for image segmentation

In this paper, we propose novel hybrid edge and region based active contour models. First, we consider geodesic curve and region-based model, and evolve contours based on global information to segment images with intensity homogeneity. Second, we extend the global model to the local intensity fitting energy for segmenting the images with intensity inhomogeneity. Moreover, the level set regularization term is added to the energy functional to ensure accurate computation and avoid expensive re-initialization of the evolving level set function. Experimental results indicate the proposed method has advantage over the geodesic active contour (GAC) model, the Chan–Vese (C–V) model, the Lankton’s method and the local binary fitting (LBF) model in terms of efficiency and robustness.