计算机应用 ›› 2011, Vol. 31 ›› Issue (12): 3378-3381.

• 图形图像技术 • 上一篇    下一篇

结合多空间特征的多尺度马尔可夫随机场彩色图像分割

杨华勇1,余正红2,郑晨3   

  1. 1. 武汉科技大学 城市学院
    2. 武汉科技大学城市学院 信息工程学部, 武汉 430083
    3. 武汉大学 数学与统计学院,武汉 430072
  • 收稿日期:2011-05-13 修回日期:2011-07-08 发布日期:2011-12-12 出版日期:2011-12-01
  • 通讯作者: 杨华勇

Color image segmentation of multi-resolutin Markov random field in combination with multi-space characteristics

YANG Hua-yong1,YU Zheng-hong2,ZHENG Chen3   

  1. 1.
    2. Department of Information Engineering, City College of Wuhan University of Science and Technology, Wuhan Hubei 430083, China
    3. School of Mathematics and Statistics, Wuhan University, Wuhan Hubei 430072, China
  • Received:2011-05-13 Revised:2011-07-08 Online:2011-12-12 Published:2011-12-01
  • Contact: YANG Hua-yong

摘要: 提出了一种结合多空间特征的多尺度马尔可夫随机场(MRF)模型——MS-MRMRF。针对RGB单空间对彩色图像描述不足的问题,模型首先将图像转化为HSV空间并与RGB空间结合形成多空间特征;然后根据多空间特征的形式,提出了一种模糊化估参的多尺度MRF模型对其进行分割。彩色图像的分割实验表明:相比现有的单空间特征的多尺度MRF算法,结合多空间特征的多尺度MRF可以有效地提高分割精度。

关键词: 分割, 多空间特征, 多尺度, 马尔科夫, 模糊

Abstract: This paper proposed a new Multi-Space Multi-Resolutin Markov Random Field Model (MS-MRMRF). Concerning the inadequate description of the color images in a single RGB space, the proposed model firstly transformed images from the RGB color space to the HSV color space and combined these two color spaces as a multi-space feature; then a new multi-resolution Markov model was designed to segment the image based on the multi-space feature, which estimated the parameters by fuzzy theory. The experiments of the color images demonstrate that the segmentation results of MS-MRMRF model have a higher segmentation accuracy compared with the segmentation results of multi-resolution MRF with a single RGB space.

Key words: segmentation, multi-space feature, multiresolution, Markov Random Field, fuzzy

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