基于核密度估计的活动轮廓模型

Active Contour Model Based on Kernel Density Estimation

基于核密度估计的活动轮廓模型如果没有适当的扰动机制,往往不能在弧度突变的边缘上获得较好的收敛结果,且在大噪声环境下鲁棒性较差。针对该问题,提出一个新的代价函数。该函数通过融合边缘映射的曲率信息,改善原算法在突变边缘的收敛效果,降低算法对初始轮廓的依赖。

If active contour model based on Kernel Density Estimation（KDE） has not proper interruption method, it is hard to obtain a desirable result on the edge changed violently, and its robustness is bad under big noise environment. In order to solve the problem, this paper proposes a new cost function. By combining the curvature information of edge mapping, it improves the convergence effect of the exsisted algorithm on break edge, and decreases its dependence on initial contour.