摘要
C-V(Chan-Vese)模型不能分割灰度不均图像,分割速度慢。因此,对图像分割理论进行深入探讨,采用实验方法,提出一个新的边缘停止函数,并将其与图像灰度变换及H1正则项融入C-V模型中,对其进行集成化改进,提出一个新颖的以偏微分方程形式表示的活动轮廓模型。实验表明:该模型能分割灰度不均图像,对初始轮廓的大小敏感性较小,抗噪性较强,分割速度较快。
C-V (Chan-Vese) model can not segment images with intensity inhomogeneity, the segmentation speed is also slow. Therefore we discuss in depth the image segmentation theory and propose a novel edge stopping function with the experimental method, and integrate it to C-V model together, with images gray-scale transformation and Hl regular term. The algorithm is also made the integrated improvement, and a novel active contour model expressed in partial differential equation (PDE) is proposed. Experimental results show that the improvement model can segment images with intensity, inhomogeneity, it is less sensitive to the size of initial contours and is significantly less sensitive to noise, and its segmentation speed is faster as well.
出处
《计算机应用与软件》
CSCD
北大核心
2012年第10期280-282,299,共4页
Computer Applications and Software
基金
遵义师范学院科研基金资助项目(11KY16)
关键词
图像分割
H1正则项
边缘停止函数
幂次变换
偏微分方程
C-V模型
集成化
Image segmentation H1 regular term Edge stopping function Power transformation Partial differential equation C-Vmodel Integration