计算机与现代化

• 图像处理 • 上一篇    下一篇

基于互信息的自然图像分割

  

  1. 浙江工商职业技术学院电子与信息工程学院,浙江宁波315012
  • 收稿日期:2014-01-14 出版日期:2014-03-24 发布日期:2014-03-31
  • 作者简介:朱一玮(1970-),男,浙江宁波人,浙江工商职业技术学院电子与信息工程学院副教授,硕士,研究方向:计算机图形图像处理。

Natural Image Segmentation Based on Mutual Information

  1. School of Electronic and Information Engineering, Zhejiang Business Technology Institute, Ningbo 315012, China
  • Received:2014-01-14 Online:2014-03-24 Published:2014-03-31

摘要: 自然图像分割在图像处理和计算机视觉等领域中占据重要地位。基于聚类的图像分割算法是无监督图像分割算法中的一种重要方法,〖JP2〗但是这类方法存在2个问题。首先特征提取一般是基于像素的,这导致分割结果与边界拟合比较差,针对此问题提出引入超像素对待分割图像预处理;其次,分割块数很难确定,针对此问题提出一种基于互信息的能量差,能够自动确定分割块数。在标准数据库上的实验结果表明,本文算法克服了上述问题,取得了比较好的实验结果。

关键词: 图像处理, 计算机视觉, 超像素

Abstract: Natural image segmentation occupies an important position in areas such as image processing and computer vision. The image segmentation algorithm based on clustering is an important method in unsupervised image segmentation algorithm. However, these methods have two main problems. First, features extraction is usuallly based on pixels. This makes the segmentation results do not fit the edges of images. Super pixels are introduced to preprocess images to overcome this problem. Second, it’s difficult to determine the number of segments. An energy difference based on mutual information is proposed to determine the number of segments automatically. Experimental results on standard database show that the proposed algorithm conquers two problems and can segment natural images well.

Key words: image processing, computer vision, super pixels

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