• DocumentCode
    3558512
  • Title

    Image processing for the oil sands mining industry [In the Spotlight]

  • Author

    Zhang, Hong

  • Author_Institution
    Centre for Intell. Min. Syst., Univ. of Alberta, Edmonton, AB
  • Volume
    25
  • Issue
    6
  • fYear
    2008
  • fDate
    11/1/2008 12:00:00 AM
  • Firstpage
    200
  • Lastpage
    198
  • Abstract
    Oil sands mining is an outdoor and continuous operation, conducted under all weather conditions. Robust and reliable image processing algorithms are called for to deliver accurate information with which operational decisions are made. Oil sands are observed at many points in the ore preparation pipeline, and each scenario defines a separate problem and presents different challenges. For example, oil sands can be imaged at the entrance to the crusher, on a conveyor belt after crushing, or before or after screening on a largely empty belt or with the large fragments amid fine fragments. The problem of measuring ore size can be formulated as one of image segmentation in which the foreground - i.e., relatively large ore fragments - are to be identified and delineated from each other as well as from the background, in a static image or in a video sequence. In what follows we describe the scenario and main steps of the image segmentation-based solution.
  • Keywords
    image segmentation; image sequences; mining industry; oil technology; video signal processing; image processing algorithm; image segmentation; oil sands mining industry; ore preparation pipeline; video sequence; weather condition; Belts; Image processing; Image segmentation; Mining industry; Ores; Petroleum; Pipelines; Robustness; Size measurement; Video sequences;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Magazine, IEEE
  • Publisher
    ieee
  • Conference_Location
    11/1/2008 12:00:00 AM
  • ISSN
    1053-5888
  • Type

    jour

  • DOI
    10.1109/MSP.2008.929837
  • Filename
    4644071