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基于图像特征分析的物体轮廓提取

王田 邹子龙 乔美娜

王田, 邹子龙, 乔美娜等 . 基于图像特征分析的物体轮廓提取[J]. 北京航空航天大学学报, 2016, 42(8): 1762-1768. doi: 10.13700/j.bh.1001-5965.2015.0491
引用本文: 王田, 邹子龙, 乔美娜等 . 基于图像特征分析的物体轮廓提取[J]. 北京航空航天大学学报, 2016, 42(8): 1762-1768. doi: 10.13700/j.bh.1001-5965.2015.0491
WANG Tian, ZOU Zilong, QIAO Meinaet al. Object contour extraction based on image feature analysis[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(8): 1762-1768. doi: 10.13700/j.bh.1001-5965.2015.0491(in Chinese)
Citation: WANG Tian, ZOU Zilong, QIAO Meinaet al. Object contour extraction based on image feature analysis[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(8): 1762-1768. doi: 10.13700/j.bh.1001-5965.2015.0491(in Chinese)

基于图像特征分析的物体轮廓提取

doi: 10.13700/j.bh.1001-5965.2015.0491
基金项目: 国家自然科学基金(U1435220,61503017);中央高校基本科研业务费专项资金(YWF-14-RSC-102)
详细信息
    作者简介:

    王田,男,博士,讲师。主要研究方向为:计算机视觉与模式识别。Tel.:010-82339358。E-mail:wangtian@buaa.edu.cn

    通讯作者:

    王田,Tel.:010-82339358,E-mail:wangtian@buaa.edu.cn

  • 中图分类号: TP391.4

Object contour extraction based on image feature analysis

  • 摘要: 对物体的轮廓进行分析提取,是计算机视觉方向的基础问题之一,对其进行研究对于复杂场景的分析理解至关重要。本文对室内场景图像进行研究,基于图像特征进行图像分割,提取物体轮廓。在彩色场景图像全局轮廓后验边界概率(gPb)提取算法的基础上,加入深度图像信息,对室内场景的彩色、深度(RGB-D)图像中的物体轮廓进行分析。通过多尺度信息融合,计算得到多尺度轮廓后验概率(mPb)和谱后验概率(sPb),两后验概率加权综合得到gPb。而后结合超度量轮廓图与分水岭算法,对基于方向特征变化的gPb图像融合处理,最终得到清晰的物体轮廓。本文所提方法在通用的RGB-D数据库基础上进行实验。实验结果表明,本文所提出的方法能提取出清晰的室内物体轮廓图。

     

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出版历程
  • 收稿日期:  2015-07-22
  • 刊出日期:  2016-08-20

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