• DocumentCode
    319634
  • Title

    Neural network based image recognition system using geometrical moment

  • Author

    Chung, Yuk Ying ; Wong, Man To

  • Author_Institution
    Space Centre for Satellite Navigation, Queensland Univ. of Technol., Brisbane, Qld., Australia
  • Volume
    1
  • fYear
    1997
  • fDate
    4-4 Dec. 1997
  • Firstpage
    383
  • Abstract
    Geometrical moments (GM) have been used in the classification of four closed planar shapes (Gupta and Srinath, 1987). Also a neural network approach for the classification of four closed planar shapes has been used in Khotanzad and Lu (1990). In this paper, a backpropagation neural network is used in the recognition of six different kinds of hand tools using geometrical moments. Experimental results indicate that the neural network approach gives a better recognition accuracy when compared with the two conventional statistical classifiers-namely the single nearest neighbour and minimum-mean-distance. Recognition accuracy using a neural network is over 98%.
  • Keywords
    backpropagation; feature extraction; hand tools; image classification; neural nets; backpropagation neural network; geometrical moment; hand tools; minimum-mean-distance method; neural network based image recognition system; recognition accuracy; single nearest neighbour method; statistical classifiers; Australia; Backpropagation; Dynamic range; Image recognition; Image storage; Neural networks; Satellite navigation systems; Shape; Space technology; Systems engineering and theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    TENCON '97. IEEE Region 10 Annual Conference. Speech and Image Technologies for Computing and Telecommunications., Proceedings of IEEE
  • Conference_Location
    Brisbane, Qld., Australia
  • Print_ISBN
    0-7803-4365-4
  • Type

    conf

  • DOI
    10.1109/TENCON.1997.647336
  • Filename
    647336