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基于MSER的无人机图像建筑区域提取

丁文锐 康传波 李红光 刘硕

丁文锐, 康传波, 李红光, 等 . 基于MSER的无人机图像建筑区域提取[J]. 北京航空航天大学学报, 2015, 41(3): 383-390. doi: 10.13700/j.bh.1001-5965.2014.0177
引用本文: 丁文锐, 康传波, 李红光, 等 . 基于MSER的无人机图像建筑区域提取[J]. 北京航空航天大学学报, 2015, 41(3): 383-390. doi: 10.13700/j.bh.1001-5965.2014.0177
DING Wenrui, KANG Chuanbo, LI Hongguang, et al. Building areas extraction basing on MSER in unmanned aerial vehicle images[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(3): 383-390. doi: 10.13700/j.bh.1001-5965.2014.0177(in Chinese)
Citation: DING Wenrui, KANG Chuanbo, LI Hongguang, et al. Building areas extraction basing on MSER in unmanned aerial vehicle images[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(3): 383-390. doi: 10.13700/j.bh.1001-5965.2014.0177(in Chinese)

基于MSER的无人机图像建筑区域提取

doi: 10.13700/j.bh.1001-5965.2014.0177
基金项目: 新世纪优秀人才支持计划资助项目; 总装预研基金资助项目(9140A25031112HK01303)
详细信息
    通讯作者:

    丁文锐(1971—),女(满族),辽宁鞍山人,研究员,ding@buaa.edu.cn,主要研究方向为遥感图像处理等.

  • 中图分类号: TP391

Building areas extraction basing on MSER in unmanned aerial vehicle images

  • 摘要: 对建筑区域自动检测与提取是无人机(UAV,Unmanned Aerial Vehicle)图像处理的一项重要功能.在分析无人机成像特点和最大稳定极值区域(MSER,Maximum Stable Extremal Regions)算法对无人机侦察图像建筑区域检测的适用性基础上,提出了一种基于MSER的无人机侦察图像建筑区域提取算法.算法包含5步:无人机图像预处理,运用MSER算法分析计算图像稳定区域,通过计算稳定区域密度筛选建筑区域,进一步利用自适应K均值聚类算法对建筑区进行划分,最后采用Graham算法生成建筑区的边界从而实现了建筑区的自动提取.选取无人机实飞图像数据进行实验统计,本算法提取精度为92.25%;同时与基于Gabor变换的纹理特征、SIFT特征点的提取算法相比,建筑区域提取时间缩短,满足无人机实时应用需求.

     

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出版历程
  • 收稿日期:  2014-04-03
  • 刊出日期:  2015-03-20

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