• DocumentCode
    2530606
  • Title

    Specular-Reduced Imaging for Inspection of Machined Surfaces

  • Author

    Sills, Ken ; Capson, David ; Bone, Gary

  • Author_Institution
    Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, ON, Canada
  • fYear
    2012
  • fDate
    28-30 May 2012
  • Firstpage
    361
  • Lastpage
    368
  • Abstract
    Specular surfaces pose difficulties for machine vision. In some applications, this may be further complicated by the presence of marks from a machining process. We propose a system that directly illuminates machined specular surfaces with a programmable array of high-power light-emitting diodes. A novel approach is described in which the angle of the incident light is varied over a series of images from which a specular-reduced median image is computed. A quality factor is used to quantitatively characterize the degree to which these specular-reduced median images approximate a diffusely lit image, and this quality factor is shown to depend linearly on the number of specular images used to produce the single specular-reduced median image. Defects such as porosity and scratches are shown to be identifiable in the specular-reduced median images of machined surfaces.
  • Keywords
    Q-factor; automatic optical inspection; computer vision; light emitting diodes; machining; porosity; production engineering computing; defect; high-power light-emitting diode; incident light; inspection; machine vision; machined specular surface; machining process; porosity; programmable array; quality factor; scratch; specular-reduced median image; Cameras; Light emitting diodes; Lighting; Machining; Rough surfaces; Surface roughness; Surface treatment; adaptive lighting; high contrast imaging; specular surface inspection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Robot Vision (CRV), 2012 Ninth Conference on
  • Conference_Location
    Toronto, ON
  • Print_ISBN
    978-1-4673-1271-4
  • Type

    conf

  • DOI
    10.1109/CRV.2012.54
  • Filename
    6233163