• DocumentCode
    1557301
  • Title

    Parallel image component labelling with watershed transformation

  • Author

    Moga, Alina N. ; Gabbouj, Moncef

  • Author_Institution
    Signal Process. Lab., Tampere Univ. of Technol., Finland
  • Volume
    19
  • Issue
    5
  • fYear
    1997
  • fDate
    5/1/1997 12:00:00 AM
  • Firstpage
    441
  • Lastpage
    450
  • Abstract
    The parallel watershed transformation used in gray scale image segmentation is reconsidered on the basis of the component labeling problem. The main idea is to break the sequentiality of the watershed transformation and to correctly delimit the extent of all connected components locally, on each processor, simultaneously. The internal fragmentation of the catchment basins, due to domain decomposition, into smaller subcomponents is finally solved by employing a global connected components operator. Therefore, in a pyramidal structure of master-slave processors, internal contours of adjacent subcomponents within the same component are hierarchically removed. Global final connected areas are efficiently obtained in log2 N steps on a logical grid of N processors. Timings and segmentation results of the algorithm built on top of the message passing interface and tested on the Gray T3D are brought forward to justify the superiority of the novel design solution compared against previous implementations
  • Keywords
    computational complexity; computer vision; image segmentation; message passing; parallel algorithms; transforms; computational complexity; domain decomposition; gray scale image; image segmentation; internal contours; internal fragmentation; message passing interface; parallel algorithm; parallel labelling; watershed transformation; Algorithm design and analysis; Concurrent computing; Image segmentation; Labeling; Message passing; Parallel processing; Pixel; Software algorithms; Testing; Timing;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/34.589204
  • Filename
    589204