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基于图割的低景深图像自动分割

刘毅 陈圣磊 冯国富 黄兵 夏德深

刘毅, 陈圣磊, 冯国富, 黄兵, 夏德深. 基于图割的低景深图像自动分割. 自动化学报, 2015, 41(8): 1471-1481. doi: 10.16383/j.aas.2015.c140734
引用本文: 刘毅, 陈圣磊, 冯国富, 黄兵, 夏德深. 基于图割的低景深图像自动分割. 自动化学报, 2015, 41(8): 1471-1481. doi: 10.16383/j.aas.2015.c140734
LIU Yi, CHEN Sheng-Lei, FENG Guo-Fu, HUANG Bing, XIA De-Shen. Automatic Segmentation of Images with Low Depth of Field Based on Graph Cuts. ACTA AUTOMATICA SINICA, 2015, 41(8): 1471-1481. doi: 10.16383/j.aas.2015.c140734
Citation: LIU Yi, CHEN Sheng-Lei, FENG Guo-Fu, HUANG Bing, XIA De-Shen. Automatic Segmentation of Images with Low Depth of Field Based on Graph Cuts. ACTA AUTOMATICA SINICA, 2015, 41(8): 1471-1481. doi: 10.16383/j.aas.2015.c140734

基于图割的低景深图像自动分割

doi: 10.16383/j.aas.2015.c140734
基金项目: 

国家自然科学基金(61473157), 江苏省高校自然科学研究项目(13KJ B520013, 14KJB520019)资助

详细信息
    作者简介:

    陈圣磊 博士,南京审计学院副教授,澳大利亚莫纳什大学信息技术学院兼职研究员.主要研究方向为数据挖掘与机器学习.E-mail:tristan_chen@126.com

Automatic Segmentation of Images with Low Depth of Field Based on Graph Cuts

Funds: 

Supported by National Natural Science Foundation of China (61473157) and Natural Science Foundation of the Jiangsu Higher Education Institutions of China (13KJB520013, 14KJB5 20019)

  • 摘要: 结合图割算法,提出了一种针对低景深(Depth of field, DOF)图像的自动分割模型.首先,通过改进的点锐度算法得到图像的点锐度图, 并结合图像的颜色特征,得到一个四维的特征向量.其次, 通过对图像点锐度图强边缘的计算,利用图像清晰部分边缘较连续, 模糊部分边缘较弱、连续性较差的特点得到图像初步的前景/背景区域. 然后,对前景/背景的颜色和点锐度特征进行高斯混合模型(Gaussian mixture model, GMM)建模,结合全局、局部自适应的λ值,对图割算法的Shrinking bias 现象进行改善.最后,通过迭代的图割算法对前景/背景区域进行修正. 实验结果表明,该模型鲁棒性较高,分割结果更加精确.
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出版历程
  • 收稿日期:  2014-10-22
  • 修回日期:  2015-04-11
  • 刊出日期:  2015-08-20

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