基于改进主动轮廓模型的图像分割算法

针对C-V模型对灰度不均匀的图像分割效果不理想的情况,提出一种改进的C-V模型.该模型在C-V模型的基础上,引入非加权的邻域平均和局部窗口方差概念,加快并精确了C-V模型的演化效果,同时在C-V模型的能量函数中加入惩罚项,使得C-V模型在演化过程中无须重新初始化,进一步提高了分割速度.仿真实验结果表明改进的C-V模型较原模型对灰度不均匀图像分割具有较好的分割效果.

Image segmentation algorithm based on an improved active contour model

Aiming at the problem of the ineffective segmentation results of the non-uniform gray images for CV model, this paper presented an improved C-V model. The model, which is on the basis of the C-V model, could accelerate and make an accurate C-V model evolution effects by introducing the concept of the non-weighted neighborhood averaging and the local window variance. Meanwhile the penalty term was put in the C-V model energy function in order to avoid the re-initialization in the process of evolution of the C-V model and improve the segmentation speed. Simulation results show that the improved CV model has better segmentation effect than the original model in the non-uniform gray images.