• DocumentCode
    1896425
  • Title

    Machine vision fuzzy object recognition and inspection using a new fuzzy neural network

  • Author

    Chen, B. ; Hoberock, L.L.

  • Author_Institution
    Sch. of Mech. & Aerosp. Eng., Oklahoma State Univ., Stillwater, OK, USA
  • fYear
    1996
  • fDate
    15-18 Sep 1996
  • Firstpage
    206
  • Lastpage
    211
  • Abstract
    A new fuzzy neural network, termed FUZAMP, has been used to deal with situations where the available training data from a machine vision system includes uncertainty. It performs well when used to recognize different types of fuzzy objects presented at different locations and orientations in the camera field of view. FUZAMP has been implemented to correlate human evaluations with machine evaluations of the cleanliness of dishes. Results are compared to those obtained using the so-called fuzzy ARTMAP neural network, with FUZAMP achieving better accuracy than the fuzzy ARTMAP using the same training exemplars
  • Keywords
    computer vision; fuzzy neural nets; inspection; object recognition; FUZAMP; cleanliness; fuzzy ARTMAP neural network; fuzzy neural network; inspection using; machine vision fuzzy object recognition; training data; Cameras; Fuzzy logic; Fuzzy neural networks; Fuzzy sets; Humans; Inspection; Machine vision; Neural networks; Sorting; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control, 1996., Proceedings of the 1996 IEEE International Symposium on
  • Conference_Location
    Dearborn, MI
  • ISSN
    2158-9860
  • Print_ISBN
    0-7803-2978-3
  • Type

    conf

  • DOI
    10.1109/ISIC.1996.556202
  • Filename
    556202