摘要
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。
Aiming at the problem of the ineffective segmentation results of the non-uniform gray images for CV model, an improved C-V model is presented. The model, which is on the basis of the C-V model, can 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 is 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.
出处
《电视技术》
北大核心
2013年第1期41-44,共4页
Video Engineering
基金
山西省自然科学基金项目(2009011018-2)
