一种基于DA-GMRF的无监督图像分割方法
Unsupervised image segmentation based on DA-GMRF
查看参考文献16篇
文摘
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提出一种基于间断自适应高斯马尔可夫随机场(DA-GMRF)模型的无监督图像分割方法.针对MRF模型中的过平滑问题,利用边缘信息构造能量函数,定义了一种DA-GMRF模型.利用灰度直方图势函数自动确定分类数及分割阈值,进行多阈值分割,得到DA-GMRF模型中标记场的初始化,用Metroplis采样器算法进行标记场的优化,实现了图像的无监督分割.实验结果表明了该方法的有效性. |
其他语种文摘
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A novel classification measure based on matrix volume according to the high dimensional geometry theory is proposed for face recognition. Many two dimensional PCA (2DPCA)-based face recognition methods almost pay much attention to the feature extraction, and the classification measure is little investigated. The typical classification measure used in 2DPCA is the sum of the Euclidean distance between two feature vectors in feature matrix, called traditional Distance Measure (DM). However, this proposed method is to compute the matrix volume. To test its performance, experiments are done based on ORL and AR face databases. The experimental results show the Matrix Volume Measure (MVM) is more efficient than the DM in 2DPCA-based face recognition. |
来源
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光电工程
,2007,34(10):88-92 【核心库】
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关键词
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图像分割
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马尔可夫随机场
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间断自适应
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合成图像
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地址
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1.
中国科学院沈阳自动化研究所, 辽宁, 沈阳, 1100161973
2.
中国科学院沈阳自动化研究所, 辽宁, 沈阳, 110016
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语种
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中文 |
文献类型
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研究性论文 |
ISSN
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1003-501X |
学科
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自动化技术、计算机技术 |
文献收藏号
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CSCD:2939693
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