Snake模型与深度凹陷区域的分割

在基于Snake模型的图像分割中，深度凹陷区域的分割是一个难点．尽管GVFSnake模型极大地改善了这个问题，但它需要事先求解一个偏微分方程组，增大了计算量；同时，GVFsnake模型在初始化时还存在一个“临界点”问题．探讨了深度凹陷区域的分割，用离散轮廓上顺序3点所成三角形内切圆圆心来定义离散轮廓的曲率，该曲率既能反映轮廓的弯曲程度，又具有合理的方向．基于该曲率定义了曲率外力项，构造了基于Snake模型的两阶段算法，先采用传统Snake模型使离散轮廓逼近目标边缘，然后在曲率外力的作用下使离散轮廓进入目标的凹陷区．曲率外力项的引入能较好地解决深度凹陷区域的分割问题，也可以扩展该外力项来扩大Snake模型的捕捉范围．实验结果表明该方法是有效的．

Research on Boundary Concavities Segmentation via Snake Models

Snake models are extensively used from its debut in image processing and motion tracking, but its poor convergence on concave boundary is a handicap for object location. Although, the GVF Snake model shows high performance for this problem, but it suffers from costly computation by virtual of PDE's and another so-called critical point problem for the initial contour selection. In order to improve the performance of the traditional Snake model for concavity segmentation, a new external force based on the local curvature of the discrete contour and a two-stage Snake-based algorithm are proposed. The local curvature of the discrete contour, which characterizes the bending of a contour associated with a direction, is defined using the center of the inscribed circle of the triangle derived from three consecutive contour nodes. The first stage of the new method is a traditional Snake, and in the second stage the new force would drive the contour into the concave region. This new force can also be generalized to enlarge the capture range of the Snake model. In this case, it can be considered as a generalization of the balloon force. In order to overcome the difficulty of determining the magnitude, the magnitude is set to be small and the gradient-based force is first used as resistance; when the contour is converged, the gradient-based force swerves to attract the contour. Generalized in this way, the capture range is enlarged and there is no critical point problem. The experimental results validate the performance of this method.