As the representative of geometric active contour model

the C-V model as well as its improved LBF model has attracted much attention. However

the C-V model and LBF model have strong dependence on the initial contour curve

so that they are instable or have high computational complexity in the process of image segmentation. In this study

we first analyze the principle of the two models and their characteristics of dependence on initial contours. Based on our analysis

we address a novel level set model for image segmentation using dual contour evolutional curve. The process of the proposed model is as follows:1)By setting the inner and outer contours

the model can approximate the target boundary from both

intern and extern of an object. The design principle of two contours is simple

and two contours are selected to be external and overlap with the object. 2)The evolution of two contours is controlled automatically through setting related terms of the model. The evolution controls the evolutionary trend of two contours automatically by minimizing the difference between internal and external contours

and stabilizes gradually at the boundary of the target from the internal and external. The proposed model avoids the re-initialization of signed distance function by setting an internal energy functional in our model. In addition

the proposed model enhances the capability of capturing the boundary in complex heterogeneous areas by applying the global regular function. By adopting the evolution mechanism of the internal and external contour at the same time

the proposed model avoids the dependence on initial contour curve. The proposed model avoids strong dependence on the initial contour of the traditional region-based segmentation model

and the initial contour is easy and robust to be selected. The segmentation results of objects are accurate and stable.