• DocumentCode
    2626918
  • Title

    Early segmentation in video compression using CNN processors

  • Author

    László, K. ; Ziliani, F. ; Roska, Tamas ; Kunt, M.

  • Author_Institution
    Comput. & Autom. Inst., Hungarian Acad. of Sci., Budapest, Hungary
  • fYear
    1998
  • fDate
    14-17 Apr 1998
  • Firstpage
    175
  • Lastpage
    180
  • Abstract
    Two analogic (analog and logic) CNN algorithms are presented which segment a video sequence into objects. The algorithms are mainly based on 3 by 3, linear templates. This allows the CNN Universal Machine to execute the task achieving enormous computation speed (1012 equivalent operation per second). The proposed segmentation algorithms rely on texture and contour information only. They differ in the use or not of the color information. The estimated execution time proves that the proposed segmentation method may be implemented in real time. This result and the quality of the obtained frame description are very appealing in the context of the new video coding standard MPEG-4
  • Keywords
    cellular neural nets; data compression; image colour analysis; image segmentation; image texture; video coding; CNN Universal Machine; CNN processors; MPEG-4; analogic CNN algorithms; color information; contour information; early segmentation; texture; video coding standard; video compression; video sequence; Analog computers; Cellular neural networks; Image color analysis; Image segmentation; Laboratories; Layout; MPEG 4 Standard; Signal processing algorithms; Turing machines; Video compression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cellular Neural Networks and Their Applications Proceedings, 1998 Fifth IEEE International Workshop on
  • Conference_Location
    London
  • Print_ISBN
    0-7803-4867-2
  • Type

    conf

  • DOI
    10.1109/CNNA.1998.685359
  • Filename
    685359