• DocumentCode
    1768780
  • Title

    Real-time range image segmentation on GPU

  • Author

    Jin Xin Hua ; Mun-Ho Jeong

  • Author_Institution
    Dept. of Control & Instrum. Eng., Kwangwoon Univ., Seoul, South Korea
  • fYear
    2014
  • fDate
    22-25 Oct. 2014
  • Firstpage
    150
  • Lastpage
    153
  • Abstract
    In this paper propose a GPU-based parallel processing method for real-time image segmentation with neural oscillator network. Range image segmentation methods can be divided into two categories: edge-based and region-based. Edge-base method is sensitive to noise and region-based method is hard to extracting the boundary detail between the object. However, by using LEGION (Locally Excitatory Globally Inhibitory oscillator networks) to do range image segmentation can overcome above disadvantages. The reason why LEGION is suitable for parallel processing that each oscillator calculate with its 8-neiborhood oscillators in real time when we process image segmentation by LEGION. Thus, using GPU-based parallel processing with LEGION can improve the speed to realize real-time image segmentation.
  • Keywords
    graphics processing units; image segmentation; neural nets; parallel processing; real-time systems; 8-neiborhood oscillators; GPU-based parallel processing method; LEGION; edge-based categories; locally excitatory globally inhibitory oscillator networks; neural oscillator network; real-time range image segmentation method; region-based categories; Graphics processing units; HTML; Image edge detection; Image segmentation; Indexes; Integrated circuits; Oscillators; CUDA; GPGPU; LEGION; range image segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control, Automation and Systems (ICCAS), 2014 14th International Conference on
  • Conference_Location
    Seoul
  • ISSN
    2093-7121
  • Print_ISBN
    978-8-9932-1506-9
  • Type

    conf

  • DOI
    10.1109/ICCAS.2014.6987976
  • Filename
    6987976