• DocumentCode
    1992599
  • Title

    Knowledge based geometric object recognition

  • Author

    Morris, R.J. ; Mardia, K.V. ; Taylor, C.C. ; Burrows, J.D.

  • Author_Institution
    Leeds Univ., UK
  • fYear
    1997
  • fDate
    28-30 Apr 1997
  • Firstpage
    47
  • Lastpage
    50
  • Abstract
    The task of recognising rigid objects in an image can be greatly eased by exploiting particular geometric features of the objects. Rather than trying to match the whole object we can just match these particular features. A considerable speed advantage can be obtained over techniques like template matching, J.D. Burrows et al. (1995), as there are efficient algorithms for detecting various geometric primitives. This approach can also cope with small differences in the actual composition of the objects, as a geometric description can ignore these differences. Similarly the algorithm can be made robust with respect to clutter and occlusion/obscurement problems. We concentrate on detecting detonators in two channel X ray images. A selection of dummy detonators is presented. We exploit two particular geometric features: each detonator contains at least one dark object and we call these blobs cold spots; each detonator is approximately a cylinder which we can represent as two parallel edges lying on either side of the cold spot
  • Keywords
    object detection; cold spots; cylinder; dark object; detonators; dummy detonators; geometric description; geometric features; geometric primitives; knowledge based geometric object recognition; occlusion/obscurement problems; parallel edges; rigid object recognition; two channel X ray images;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Security and Detection, 1997. ECOS 97., European Conference on
  • Conference_Location
    London
  • ISSN
    0537-9989
  • Print_ISBN
    0-85296-683-0
  • Type

    conf

  • DOI
    10.1049/cp:19970418
  • Filename
    605796