关键词: 图像分割, 水平集方法, 选择性自适应演化系数, 梯度选择性边缘停止函数

Abstract: Adaptive distance preserving level set evolution model is derived from level set evolution without re-initialization model, which introduces a variable weight coefficient and so eliminates the need of initial contours. However, this model has the drawbacks of high sensitiveness to noise and locating inaccurately the object edge of image due to intensity inhomogeneity. Following this model, this paper introduces a new variable weight coefficient and a new edge stop function based on this variable weight coefficient. Experimental results show that the distance preserving level set evolution model can really overcome the above-mentioned drawbacks.

Key words: image segmentation, level set method, selective adaptive evolution coefficient, gradient edge stop function of selective