• DocumentCode
    831592
  • Title

    Efficient parallel processing of image contours

  • Author

    Chen, Ling Tony ; Davis, Larry S. ; Kruskal, Clyde P.

  • Author_Institution
    Maryland Univ., College Park, MD, USA
  • Volume
    15
  • Issue
    1
  • fYear
    1993
  • fDate
    1/1/1993 12:00:00 AM
  • Firstpage
    69
  • Lastpage
    81
  • Abstract
    Describes two parallel algorithms for ranking the pixels on a curve in O (log N) time using either an EREW or CREW PRAM model. The algorithms accomplish this with N processors for a √N×√N image. After applying such an algorithm to an image, it is possible to move the pixels from a curve into processors having consecutive addresses. This is important because one can subsequently apply many algorithms to the curve (such as piecewise linear approximation algorithms or point in polygon tests) using segmented scan operations (i.e. parallel prefix operations). Scan operations can be executed in logarithmic time on many interconnection networks, such as hypercube, tree, butterfly, and shuffle exchange machines as well as on the EREW PRAM. The algorithms were implemented on the hypercube structured Connection Machine, and various performance tests were conducted
  • Keywords
    computational complexity; computer vision; hypercube networks; image processing; parallel algorithms; parallel processing; CREW PRAM model; Connection Machine; EREW model; computer vision; hypercube; image contours; parallel algorithms; parallel processing; segmented scan operations; Approximation algorithms; Hypercubes; Image segmentation; Multiprocessor interconnection networks; Parallel algorithms; Parallel processing; Phase change random access memory; Piecewise linear approximation; Pixel; Testing;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/34.184775
  • Filename
    184775