• DocumentCode
    2754828
  • Title

    An orientation-selective multi-chip aVLSI applicable to texture analysis

  • Author

    Shimonomura, Kazuhiro ; Yagi, Tetsuya

  • Author_Institution
    Dept. of Electron. Eng., Osaka Univ., Japan
  • Volume
    5
  • fYear
    2005
  • fDate
    31 July-4 Aug. 2005
  • Firstpage
    3267
  • Abstract
    A high resolution neuromorphic aVLSI was fabricated to emulate the orientation selective response of the simple cell in the primary visual cortex. The aVLSI circuits consist of two analog chips: a silicon retina and an orientation chip. The center-surround concentric receptive fields of the silicon retina are aggregated in the orientation chip, mimicking the hierarchical architecture in the visual system of the brain. Both chips have 100 × 100 pixels and therefore, this multi-chip system is applicable to robotic vision. Using the orientation-selective outputs obtained from the multi-chip system, a texture segregation was conducted based on a similar algorithm of the energy computation. The texture image was filtered by the two orthogonally oriented receptive fields of multi-chip system and the filtered images were combined to segregate the area of different texture orientation with the aid of a PC. The study demonstrated that the orientation-selective multi-chip system developed is useful to emulate the texture segregation employing a fundamental architecture to generate the simple cell response in the primary visual cortex and is applicable to robotic vision.
  • Keywords
    VLSI; filtering theory; image texture; neural chips; system-on-chip; aVLSI; analog chip; energy computation; image filtering; multichip system; orientation chip; orientation-selective multichip; robotic vision; silicon retina; texture analysis; texture image; texture segregation; visual system; Brain modeling; Circuits; Computer architecture; Image processing; Neuromorphics; Real time systems; Retina; Robot vision systems; Silicon; Visual system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on
  • Print_ISBN
    0-7803-9048-2
  • Type

    conf

  • DOI
    10.1109/IJCNN.2005.1556451
  • Filename
    1556451