Advanced Search
Volume 40 Issue 12
Dec.  2014
Turn off MathJax
Article Contents
Journal of Beijing University of Aeronautics and Astronautics  > 2014  >  40(12): 1678-1684.
Chen Weishi, Li Jing. Foreign object debris detection for airport runway with video data[J]. Journal of Beijing University of Aeronautics and Astronautics, 2014, 40(12): 1678-1684. doi: 10.13700/j.bh.1001-5965.2013.0762(in Chinese)
Citation: Chen Weishi, Li Jing. Foreign object debris detection for airport runway with video data[J]. Journal of Beijing University of Aeronautics and Astronautics, 2014, 40(12): 1678-1684. doi: 10.13700/j.bh.1001-5965.2013.0762(in Chinese)
shu

Foreign object debris detection for airport runway with video data

doi: 10.13700/j.bh.1001-5965.2013.0762

  • Airport Research Institute, China Academy of Civil Aviation Science and Technology, Beijing 100028, China

  • Received Date: 13 Jan 2014
  • Publish Date: 20 Dec 2014
    Abstract
  • Foreign object debris (FOD) detection algorithm was proposed for airport runway with video data, including four steps of geometric adjustment, background subtraction, noise suppression and camouflage elimination. Firstly, geometric adjustment rejected the image change due to slight camera motion. In the step of background subtraction, the color vector information to each pixel was used for the establishment of the background model and its periodical update. For noise suppression and camouflage elimination, Markov random field and probability statistical model were established based on the information from the subtracted and original images, which reduced the false alarms and improved the detection rate. The algorithm was applied to two sets of live video images under different lighting conditions, with the FOD targets of different shapes and colors. The algorithm effectiveness was also approved by the tests on the airport ground-truth data.

     

    • FullText(HTML)
  • loading
    • References(16)
  • [1]
    NAS-412 REV.1 Foreign object damage/foreign object debris(FOD) prevention[S]
    [2]
    Patterson Jr J.Foreign object debris(FOD)detection research[J].International Airport Review,2008,11(2):22-27
    [3]
    FAA AC:150/5220-24 Airport foreign object debris (FOD) detection equipment[S]
    [4]
    李煜,肖刚.机场跑道异物检测系统设计与研究[J].激光与红外,2011,41(8):909-915 Li Yu,Xiao Gang.Study and design on FOD detection and surveillance system for airport runway[J].Laser & Infrared,2011,41(8):909-915(in Chinese)
    [5]
    樊曼劼.机场跑道异物检测研究[D].北京:北京交通大学,2011 Fan Manjie.Airport FOD detection research on runway[D].Beijing:Beijing Jiaotong University,2011(in Chinese)
    [6]
    Xu Q Y,Ning H S,Chen W S.Video-based foreign object debris detection[C]//Proceedings of IEEE International Workshop on Imaging Systems and Techniques.Piscataway,NJ:IEEE Comput- er Society,2009:123-126
    [7]
    Beasley P D L,Binns G,Hodges R D,et al.Tarsier®,a millimeter wave radar for airport runway debris detection[C]//Proceedings of European Radar Conference.Amsterdam:Horizon House Publishing Ltd,2004:261-264
    [8]
    Vogel B.An object lesson in finding FOD[J].Jane's Airport Review,2008,20(8):56-57
    [9]
    Radke R J,Andra S,Al-Kofahi O,et al.Image change detection algorithm: a systematic survey[J].IEEE Transactions on Image Processing,2005,14(3):294-307
    [10]
    Zitova B,Flusser J.Image registration methods:a survey[J].Image and Vision Computing,2003,21(11):977-1000
    [11]
    Haines T S F,Xiang T.Background subtraction with dirichlet processes[C]//Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).Heidelberg:Springer Verlag,2012,7575 LNCS(PART 4):97-111
    [12]
    Diaz R,Hallman S,Fowlkes C.Detecting dynamic objects with multi-view background subtraction[C]//Proceedings of IEEE International Conference on Computer Vision (ICCV).Sydney:IEEE,2013:273-280
    [13]
    Shimada A,Nagahara H,Taniguchi R.Backgroundmodeling based on bidirectional analysis[C]//Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.Washington D C:IEEE Computer Society,2013:1979-1986
    [14]
    Elgammal A,Duraiswami R,Harwood D,et al.Background and foreground modeling using nonparametric kernel density estimation for visual surveillance[J].Proceedings of the IEEE,2002,90(7):1151-1162
    [15]
    Barnich O,Van Droogenbroeck M.ViBe:auniversal background subtraction algorithm for video sequences[J].IEEE Transactions on Image Processing,2011,20(6):1709-1724
    [16]
    McHugh J,Konrad J,Saligrama V,et al.Foreground-adaptive background subtraction[J].IEEE Signal Processing Letters,2009,16(5):390-393
    • Relative Articles
    • Supplements(0)
    • Cited By
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索
    Get Citation
    PDF
    XML

    Article Metrics

    Article views(1456) PDF downloads(681) Cited by()
    Proportional views
    Related

    Copyright © Journal of Beijing University of Aeronautics and Astronautics

    Address: Editorial Department of Journal of Beijing University of Aeronautics and Astronautics, 37 Xueyuan Road, Haidian District, Beijing Post Code: 100191 Email: jbuaa@buaa.edu.cn

    Supported by: Beijing Renhe Information Technology Co., Ltd.    

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return