An improved region-based model with local statistical feature

In this paper, a new region-based active contour model is proposed for image segmentation. Different from the general region-based active contour models, this model partitions the regions of interests in images depending on the local statistics of the intensity and the magnitude of gradient in the neighborhood of the contour. Inspired by the structure tensor method, an improved regularization term is defined through the duality formulation to penalize the length of region boundaries. Experiments on medical images demonstrate the proposed model outperforms the classical segmentation models in terms of efficiency and accuracy.