• DocumentCode
    1343823
  • Title

    Implementation of binary and gray-scale mathematical morphology on the CNN universal machine

  • Author

    Zarándy, Akos ; Stoffels, André ; Roska, Tamás ; Chua, Leon O.

  • Author_Institution
    Comput. & Autom. Inst., Hungarian Acad. of Sci., Budapest, Hungary
  • Volume
    45
  • Issue
    2
  • fYear
    1998
  • fDate
    2/1/1998 12:00:00 AM
  • Firstpage
    163
  • Lastpage
    168
  • Abstract
    A cellular neural network(CNN)-based morphological engine is proposed. An effective implementation method of binary and gray-scale erosion, dilation, and reconstruction is introduced. The binary morphological operators are successfully implemented on an actual CNN universal chip. Experimental results are shown
  • Keywords
    cellular neural nets; image processing; image reconstruction; mathematical morphology; neural chips; CNN universal chip; CNN universal machine; CNN-based morphological engine; binary mathematical morphology; cellular neural network; dilation; erosion; gray-scale mathematical morphology; reconstruction; Cellular neural networks; Engines; Gray-scale; Image reconstruction; Integrated circuit interconnections; Laboratories; Morphology; Optical devices; Optical feedback; Turing machines;
  • fLanguage
    English
  • Journal_Title
    Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7122
  • Type

    jour

  • DOI
    10.1109/81.661683
  • Filename
    661683
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1343823