ROBUST ACTIVE CONTOURS WITH INSENSITIVE PARAMETERS

Active contours, known as snakes, have found wide applications since their first introduction in 1987 by Kass et al. (Int. J. Comput. Vision 1, 321-331). However, one problem with the current models is that the performance depends on proper internal parameters and initial contour position, which, unfortunately, cannot be determined a priori. It is usually a hard job to tune internal parameters and initial contour position. The problem comes from the fact that the internal normal force at each point of contour is also a function of contour shape. To solve this problem, we propose to compensate for this internal normal force so as to make it independent of shape. As a result, the new model works robustly with no necessity to fine-tune internal parameters, and can converge to high curvature points like corners.