Adaptive Region Based Active Contour Model for Image Segmentation
Amira Soudani, Ezzeddine Zagrouba · 2017
In this paper, a new region based active contour model is proposed for image segmentation. The proposed model is based on the combination of an adaptive local term based on the computation of local statistics deduced at each point of the evolved curve and a global term built using the means of intensities inside and outside the evolved curve. The novelty of the approach is the introduction of an adaptive energy term by the definition of local regions along the curve that will be updated at each iteration of the minimization process according to the gradient information. Experiments on medical, synthetic, real-word and noisy images prove the effectiveness of the proposed method regarding methods of state of the art.