  Active contour models based on local region fitting energy can segment images
with intensity inhomogeneity effectively, but their segmentation results are
easy to error if the initial contour is inappropriate. In this paper, we
present a simple and universal method of improving the robustness of initial
contour for these local fitting-based models. The core idea of proposed method
is exchanging the fitting values on the two sides of contour, so that the
fitting values inside the contour are always larger (or smaller) than the
values outside the contour in the process of curve evolution. In this way, the
whole curve will evolve along the inner (or outer) boundaries of object, and
less likely to be stuck in the object or background. Experimental results have
proved that using the proposed method can enhance the robustness of initial
contour and meanwhile keep the original advantages in the local fitting-based
models.
