计算机工程与应用 ›› 2011, Vol. 47 ›› Issue (27): 221-224.

• 图形、图像、模式识别 • 上一篇    下一篇

自适应模型的水平集图像分割方法

谢 意1,杨 玲2   

  1. 1.成都信息工程学院 电子工程学院,成都 610225
    2.成都信息工程学院 网络工程学院,成都 610225
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2011-09-21 发布日期:2011-09-21

Level set method of image segmentation based on adaptive model

XIE Yi1,YANG Ling2   

  1. 1.College of Electronic Engineering,Chengdu University of Information Technology,Chengdu 610225,China
    2.College of Networks Engineering,Chengdu University of Information Technology,Chengdu 610225,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-09-21 Published:2011-09-21

摘要: 水平集广泛应用于图像分割。给出基于传统C-V和GAC模型的水平集方法,在此基础上,介绍了一种结合C-V模型和GAC模型并根据图像特征选择性融入图像局部信息的自适应模型的水平集分割方法。通过实例分析,证明了该方法对分割弱边缘和灰度渐进的图像是有效的,并且抗噪声性能较好。

关键词: 水平集, 能量函数, 图像分割, 偏微分方程

Abstract: Level-set has been widely used in image segmentation.This paper introduces the traditional level-set based on the model of C-V and GAC,then a new method is presented to segment images,which combines with the advantages of the C-V model and the GAC model mean while it selectively considers the local information in the illegibility area according to the characteristics of image.Finally,a real example demonstrates the method is effectiveness and feasibility on segmenting the noisy blurry boundary and intensity inhomogeneity images.

Key words: level-set, energy function, image segmentation, Partial Differential Equation(PDE)