一种改进的 C-V 水平集图像分割方法

摘要

A level set image segmentation model presented by Chan-Vese does not rely on the image edge information and it has good segmentation effect on weak edge and the images containing internal outline . However , for the gray scale of background image contains two or more hierarchies , image segmentation can not get accurate results .This paper puts forward a new improved algorithm based on C-V model .The algorithm introduces an improved fast C-V method into the global gradient information and the prior knowledge of the target .The experimental results show that the method can identify the complex grayscale background image with target area profile of multiple hierarchies , which proves to have favorable perform-ance and adaptability .%由Chan-Vese提出的水平集图像分割模型可以不依赖于图像的边缘信息而对弱边缘以及含有内部轮廓的图像具有良好的分割效果。但对于背景图像灰度包含两个及以上等级分层时，图像分割得不到准确的结果。提出一种新的基于C-V模型的改进算法，该算法引入了快速C-V方法的思想，融入全局梯度信息以及目标的先验知识。实验结果表明，该方法能够很好地分辨出背景图像复杂灰度包含多个等级分层的目标区域轮廓且具有良好的适应性。