摘要
针对灰度不均匀图像难以正确分割和分割结果依赖于初始轮廓的问题,提出一种快速稳定的分割算法,首先通过自适应距离保持水平集演化(ADPLS)算法进行初始分割以获取较好的初始轮廓,然后采用局部二值拟合(LBF)模型进行快速分割。实验表明,改进后的模型有良好的分割效果,较好地解决了分割速度、精度及稳定性之间的矛盾。
It is difficult to get the correct segmentation results for the intensity inhomogeneity images, and the segmentation results are very sensitive to the initial contours. Thus, a fast and stable approach was proposed to overcome these disadvantages. First, an Adaptive Distance Preserving Level Set （ADPLS） method was utilized to get a better initial contour. Second, the Local Binary Fitting （LBF） model was used for a further segmentation. The experimental results show that the improved model can achieve good performance and is better to solve the contradiction among the segmentation speed, accuracy and stability.
出处
《计算机应用》
CSCD
北大核心
2013年第2期491-494,共4页
journal of Computer Applications
基金
南京军区重点项目(11Z023)
福建省自然科学基金资助项目(2008J0312)
关键词
图像分割
水平集
曲线演化
偏微分方程
活动轮廓模型
image segmentation
level set
curve evolution
Partial Differential Equation （PDE）
active contour model
