• DocumentCode
    3669428
  • Title

    Automatic detection of concealed pistols using passive millimeter wave imaging

  • Author

    Zelong Xiao;Xuan Lu;Jiangjiang Yan;Li Wu;Luyao Ren

  • Author_Institution
    School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, China
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    A method is proposed for automatic detection of the concealed pistols detected by passive millimeter in security applications. In this paper, we extend four half-surrounded Haar-like features and use integral image to rapidly calculate the rectangle features. Then we obtain a multi-layer classifier cascaded by several strong classifiers using AdaBoost algorithm to detect the contraband. Various passive millimeter images from both published literatures and our own measurements are used for training and testing. The experimental results show that the metallic pistols in different sizes, shapes, and angles can be accurately detected, so this method is useful for automatic detection of pistols.
  • Keywords
    "Feature extraction","Imaging","Classification algorithms","Millimeter wave technology","Training","Image recognition","Object detection"
  • Publisher
    ieee
  • Conference_Titel
    Imaging Systems and Techniques (IST), 2015 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/IST.2015.7294538
  • Filename
    7294538