首页> 外文会议>DAGM symposium on pattern recognition >Level Set Based Image Segmentation with Multiple Regions
【24h】

Level Set Based Image Segmentation with Multiple Regions

机译:基于水平集的多区域图像分割

获取原文

摘要

We address the difficulty of image segmentation methods based on the popular level set framework to handle an arbitrary number of regions. While in the literature some level set techniques are available that can at least deal with a fixed amount of regions greater than two, there is very few work on how to optimise the segmentation also with regard to the number of regions. Based on a variational model, we propose a minimisation strategy that robustly optimises the energy in a level set framework, including the number of regions. Our evaluation shows that very good segmentations are found even in difficult situations.
机译:我们解决了基于流行的水平集框架来处理任意数量区域的图像分割方法的难题。尽管在文献中可以使用一些级别集技术,这些技术至少可以处理大于两个的固定数量的区域,但是关于区域数量的如何优化分割的工作却很少。基于变分模型,我们提出了一种最小化策略,该策略可在包括区域数量在内的水平集框架中稳健地优化能量。我们的评估表明,即使在困难的情况下也可以找到很好的细分。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号