• DocumentCode
    2498252
  • Title

    An image recognition based on neural oscillator network

  • Author

    Hoshino, Kenta ; Igarashi, Hajime

  • Author_Institution
    Grad. Sch. of Inf. Sci. & Technol., Hokkaido Univ., Sapporo, Japan
  • fYear
    2010
  • fDate
    18-23 July 2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper introduces a novel image recognition method based on the neural oscillator network. In the present method, the dynamics of neurons is determined from neural coupling strengths relevant to the similarities in pixel levels, which have been used in the conventional image segmentation, as well as geometrical local features obtained from the Gabor filtering. Then the image regions under resultant neural synchronization are identified. It is shown that the accuracy of the present method, applied to the image recognition for pairs of identical and different alphabetical letters, is 76.9% and 62.2%, respectively. Moreover, the simple polygons are also correctly recognized by the present method.
  • Keywords
    Gabor filters; character recognition; image recognition; image resolution; image segmentation; neural nets; oscillators; Gabor filtering; alphabetical letters; geometrical local features; image recognition; image segmentation; neural coupling strengths; neural oscillator network; neuron dynamics; pixel levels; resultant neural synchronization; Image segmentation; Oscillators; Pixel; Synchronization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2010 International Joint Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-6916-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.2010.5596947
  • Filename
    5596947