• DocumentCode
    1804527
  • Title

    Morphological image processing and its parallel implementation

  • Author

    Sha, He ; Wah, Chan Choong

  • Author_Institution
    Sch. of Electr. & Electron. Eng., Nanyang Technol. Inst., Singapore
  • Volume
    1
  • fYear
    1996
  • fDate
    14-18 Oct 1996
  • Firstpage
    539
  • Abstract
    No sequential computer can meet processing demands today. One of the few options for meeting the computation needs is to exploit parallel processing. Morphological image processing algorithms are utilized in many machine vision systems because it is a very powerful image processing tool. Morphology analyses the images from the perspective of set theory and geometry. In this paper, considering the practical restriction of the resources, we proposed a multi-processor architecture for morphological image processing. The architecture is simulated on a HP9000 series 700 workstation. The basic morphological operations such as dilation, erosion and algorithms such as edge detection can be easily and effectively implemented with the proposed architecture. Experimental results indicate that the architecture is robust. We also describe an application of morphological image processing based on this parallel architecture, i.e., marking and counting objects
  • Keywords
    computer vision; edge detection; image processing; mathematical morphology; parallel algorithms; parallel architectures; shared memory systems; HP9000 series 700 workstation; dilation; edge detection; erosion; geometry; machine vision; morphological image processing; multiprocessor architecture; object counting; object marking; parallel architecture; parallel processing; set theory; Concurrent computing; Geometry; Image analysis; Image processing; Machine vision; Morphological operations; Morphology; Parallel processing; Set theory; Workstations;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, 1996., 3rd International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-2912-0
  • Type

    conf

  • DOI
    10.1109/ICSIGP.1996.567321
  • Filename
    567321