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一种基于HMRF模型的无监督图像分割算法
引用本文:朱国普,曾庆双,屈彦呈,王常虹,沈博昌.一种基于HMRF模型的无监督图像分割算法[J].电子学报,2006,34(2):374-379.
作者姓名:朱国普  曾庆双  屈彦呈  王常虹  沈博昌
作者单位:哈尔滨工业大学空间控制与惯性技术研究中心,黑龙江哈尔滨,150001;哈尔滨工业大学空间控制与惯性技术研究中心,黑龙江哈尔滨,150001;哈尔滨工业大学空间控制与惯性技术研究中心,黑龙江哈尔滨,150001;哈尔滨工业大学空间控制与惯性技术研究中心,黑龙江哈尔滨,150001;哈尔滨工业大学空间控制与惯性技术研究中心,黑龙江哈尔滨,150001
摘    要:研究了基于隐马尔可夫随机场(HMRF)模型的无监督图像分割问题.对于每一阶模型的图像分割,该算法充分利用了相邻模型之间的相关信息,由此,该算法克服了均值场算法对初始化条件要求非常苛刻的缺点.而且,针对无监督图像分割的模型选择问题提出了带惩罚项的误差平方和阶次判定准则.实验结果证实本文提出的阶次判定准则优于伪似然信息准则(PLIC),并且,该算法具有满意的分割结果.

关 键 词:图像分割  HMRF模型  均值场算法  模型选择
文章编号:0372-2012(2006)02-0374-06
收稿时间:2004-07-16
修稿时间:2004-07-162005-11-15

An Unsupervised Image Segmentation Algorithm Based on HMRF Model
ZHU Guo-pu,ZENG Qing-shuang,QU Yan-cheng,WANG Chang-hong,SHENG Bo-chang.An Unsupervised Image Segmentation Algorithm Based on HMRF Model[J].Acta Electronica Sinica,2006,34(2):374-379.
Authors:ZHU Guo-pu  ZENG Qing-shuang  QU Yan-cheng  WANG Chang-hong  SHENG Bo-chang
Affiliation:Space Control and Inertial Technology Research Center,Harbin Institute of Technology,Harbin,Heilongjiang 150001,China
Abstract:This paper presents a novel unsupervised image segmentation algorithm based on hidden Markov random field(HMRF) model.For each order model segmentation the proposed algorithm makes use of the correlated information between adjacent models.Therefore the algorithm avoids the drawback about that mean field algorithm is restricted by initial condition.Furthermore,in order to solve the model selection problems of unsupervised image segmentation,the sum of squared error criterion with penalty term is proposed.The experiment results testify that the proposed criterion is superior to the Pseudo-likelihood Information Criterion(PLIC),and it is shown that the performance of the segmentation is satisfied.
Keywords:HMRF model  image segmentation  mean field algorithm  model selection
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