Abstract: Geometrical Active Contour（GAC） models，i.e.，active contour models implemented via level set methods，have recently become very popular image segmentation methods in image processing and computer vision.Almost these models rely on the Halting Speed Function（HSF），which is typically the function of the image gradient，to stop the active contour（evolving curve）on the boundary of the desired object.In order to speed up the evolution of the active contour，this paper proposes a scheme that the scale transform is applied to the HSF.Experimental results on four synthetic and real world images show that the proposed scheme can significantly reduce segmentation time and perform better in the presence of concave and weak object boundaries.

摘要： 近年来，通过水平集方法实现的几何活动轮廓模型（GAC）已成为图像处理和计算机视觉领域里十分流行的图像分割方法。几乎所有的GAC模型都依赖于停止速度函数，该函数通常是基于图像梯度定义的，其作用是使活动轮廓（演化曲线）停止在所希望的目标边界上。为了加快活动轮廓的演化速度，提出对停止速度函数进行尺度变换的方法。对4幅人工和自然图像的实验结果显示，所提出的方案能够大大减少分割时间，同时，对于凹陷边界和弱边界的分割取得了更好的效果。