• DocumentCode
    2439503
  • Title

    An Effective Method for Traffic Signs Segmentation

  • Author

    Hu, Mudan ; Zhu, Shuangdong ; Chen, Ken

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Ningbo Univ., Ningbo, China
  • Volume
    2
  • fYear
    2009
  • fDate
    26-27 Aug. 2009
  • Firstpage
    180
  • Lastpage
    184
  • Abstract
    An effective method for traffic sign segmentation is proposed. Through the selection of appropriate characteristic operator on the basis of the distinctive color features of traffic sign, it first quickly obtains gray image of chromatic aberration. Then, the Otsu´s thresholding algorithm is subsequently applied to locate accurately the candidate regions of the traffic sign. The experimental result shows that the proposed algorithm can extract the traffic sign from the background well up to the technical standards under various natural illuminating conditions, and the segmentation effect is superior to that performed by the generic segmentation with steady threshold, and the performance in shape checking is thus improved. The presented approach is featured in good robustness, high speed, and as a result can be potentially applied to the real-time processing and commercialization.
  • Keywords
    aberrations; feature extraction; image colour analysis; image segmentation; road traffic; chromatic aberration; distinctive color feature; generic segmentation; image thresholding; traffic sign segmentation; Cybernetics; Educational institutions; Image edge detection; Image segmentation; Intelligent systems; Intelligent transportation systems; Man machine systems; Object detection; Shape; Space technology; Otsu algorithm; RGB model; chromatic aberration; image segmentation; traffic sign;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Human-Machine Systems and Cybernetics, 2009. IHMSC '09. International Conference on
  • Conference_Location
    Hangzhou, Zhejiang
  • Print_ISBN
    978-0-7695-3752-8
  • Type

    conf

  • DOI
    10.1109/IHMSC.2009.169
  • Filename
    5336016