CAJ | 학술논문

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。
유Chan-Vese제출적수평집도상분할모형가이불의뢰우도상적변연신식이대약변연이급함유내부륜곽적도상구유량호적분할효과。단대우배경도상회도포함량개급이상등급분층시，도상분할득불도준학적결과。제출일충신적기우C-V모형적개진산법，해산법인입료쾌속C-V방법적사상，융입전국제도신식이급목표적선험지식。실험결과표명，해방법능구흔호지분변출배경도상복잡회도포함다개등급분층적목표구역륜곽차구유량호적괄응성。
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 .