• DocumentCode
    285302
  • Title

    Massively parallel neural network recognition

  • Author

    Wilson, C.L.

  • Author_Institution
    Nat. Inst. of Stand. & Technol., Gaithersburg, MD, USA
  • Volume
    3
  • fYear
    1992
  • fDate
    7-11 Jun 1992
  • Firstpage
    227
  • Abstract
    The author discusses two complete neural network recognition systems, a character recognition system and a fingerprint classification system. The requirements for a total vision system must include the capability for image isolation, segmentation, and feature extraction, as well as recognition. The systems were developed on a massively parallel array processor which was used to illustrate the importance of these higher-level functions. Both of these systems demonstrated state-of-the-art accuracy but both need improvements to be commercially viable. The issue in the character recognition system is to provide this accuracy at a speed compatible with commercial requirements of 1 page/s. This will require more sophisticated higher-level image parsing functions without loss of accuracy. The issue in fingerprint classification is the requirement for 99.7% accuracy at current speeds
  • Keywords
    character recognition; computer vision; image recognition; parallel processing; character recognition system; feature extraction; fingerprint classification system; higher-level image parsing functions; image isolation; massively parallel array processor; massively parallel neural network recognition; segmentation; total vision system; Character recognition; Concurrent computing; Feature extraction; Fingerprint recognition; Image converters; Image recognition; Image segmentation; Machine vision; NIST; Neural networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1992. IJCNN., International Joint Conference on
  • Conference_Location
    Baltimore, MD
  • Print_ISBN
    0-7803-0559-0
  • Type

    conf

  • DOI
    10.1109/IJCNN.1992.227166
  • Filename
    227166