• DocumentCode
    3494349
  • Title

    Coherence vector of Oriented Gradients for traffic sign recognition using Neural Networks

  • Author

    Rajesh, R. ; Rajeev, K. ; Suchithra, K. ; Lekhesh, V.P. ; Gopakumar, V. ; Ragesh, N.K.

  • Author_Institution
    Network Syst. & Technol., Thiruvananthapuram, India
  • fYear
    2011
  • fDate
    July 31 2011-Aug. 5 2011
  • Firstpage
    907
  • Lastpage
    910
  • Abstract
    This paper makes use of Coherence Vector of Oriented Gradients (CVOG) for traffic sign recognition. Experiments are conducted on German Traffic Sign benchmark dataset. The results on traffic sign recognition using CVOG features with neural network classifier is promising. The results based on the combination of other features gave better recognition rates.
  • Keywords
    image recognition; neural nets; pattern classification; traffic engineering computing; CVOG features; coherence vector of oriented gradients; neural networks; traffic sign recognition; Biological neural networks; Coherence; Feature extraction; Image color analysis; Image edge detection; Pattern recognition; Roads; CCV; Coherence Vector of Oriented Gradients; Neural Network Classifier; Traffic Sign Recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2011 International Joint Conference on
  • Conference_Location
    San Jose, CA
  • ISSN
    2161-4393
  • Print_ISBN
    978-1-4244-9635-8
  • Type

    conf

  • DOI
    10.1109/IJCNN.2011.6033318
  • Filename
    6033318