计算机工程与应用 ›› 2009, Vol. 45 ›› Issue (24): 156-158.DOI: 10.3778/j.issn.1002-8331.2009.24.046

• 图形、图像、模式识别 • 上一篇    下一篇

扩展无边活动轮廓模型

何瑞英,何传江   

  1. 重庆大学 数理学院,重庆 400030
  • 收稿日期:2008-10-21 修回日期:2008-12-26 出版日期:2009-08-21 发布日期:2009-08-21
  • 通讯作者: 何瑞英

Extended active contours model without edges

HE Rui-ying,HE Chuan-jiang   

  1. 重庆大学 数理学院,重庆 400030
  • Received:2008-10-21 Revised:2008-12-26 Online:2009-08-21 Published:2009-08-21
  • Contact: HE Rui-ying

摘要: 灰度变化对图像分割是至关重要的。然而,一个著名的基于区域的活动轮廓模型——无边活动轮廓模型(通常称CV模型)完全忽略了这种灰度变化。提出了一个扩展CV模型(ECV),它利用了图像的灰度变化信息。实验表明:(1)ECV模型能分割CV模型不适用的某些类型的图像;(2)ECV模型也能分割CV模型适用的图像,且对噪声的鲁棒性强于CV模型。

关键词: 图像分割, V模型, 平集, 微分方程

Abstract: Intensity changes are crucial for accurate segmentation of many images.However,intensity changes are ignored in active contours model without edges(called CV model,usually),one of the most popular region-based active contour models.This paper proposes an extended version of CV model,which is able to utilize intensity change information in images.The experimental results show:(1)the Extended CV(ECV) model can be used to segment certain types of images to which CV model is not applicable.(2)ECV model is also able to segment the images that CV model is applicable to,and is significantly fewer sensitive to noise than CV model.

Key words: image segmentation, V model, level set, artial differential equation

中图分类号: