Robust active contours driven by order-statistic filtering energy for fast image segmentation

摘要

In this paper, a robust active contour model driven by order-statistic filtering (OSF) energy is proposed for fast image segmentation. The main idea of the order-statistic filtering energy is to construct the edge force function (EFF) to quickly and adaptively attract curves to evolve towards the boundaries of targets. Besides, because the EFF is computed before iterations, therefore, segmentation speed of the OSF model improves greatly. Furthermore, an optimized regularization term and an optimized length term are used in the OSF model to replace the traditional penalty and length term, respectively. Experiments on some synthetic and real images show that the OSF model can segment images with intensity inhomogeneity quickly and precisely. In addition, several experiments also show that the OSF model is robust to initial contour and parameters.