• DocumentCode
    671473
  • Title

    A robust, coarse-to-fine traffic sign detection method

  • Author

    Gangyi Wang ; Guanghui Ren ; Zhilu Wu ; Yaqin Zhao ; Lihui Jiang

  • Author_Institution
    Sch. of Electron. & Inf. Eng., Harbin Inst. of Technol., Harbin, China
  • fYear
    2013
  • fDate
    4-9 Aug. 2013
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    We present a traffic sign detection method which has won the first place for the prohibitory and mandatory signs and the third place for the danger signs in the GTSDB competition. The method uses the histogram of oriented gradient (HOG) and a coarse-to-fine sliding window scheme. Candidate ROIs are first roughly detected within a small-sized window, and then further verified within a large-sized window for higher accuracy. Experimental results show that the proposed method achieves high recall and precision ratios, and is robust to various adverse situations including bad lighting condition, partial occlusion, low quality and small projective deformation.
  • Keywords
    driver information systems; object detection; GTSDB competition; HOG; coarse-to-fine sliding window scheme; danger signs; histogram of oriented gradient; large-sized window; mandatory signs; small-sized window; traffic sign detection method; Accuracy; Feature extraction; Image color analysis; Robustness; Shape; Support vector machines; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2013 International Joint Conference on
  • Conference_Location
    Dallas, TX
  • ISSN
    2161-4393
  • Print_ISBN
    978-1-4673-6128-6
  • Type

    conf

  • DOI
    10.1109/IJCNN.2013.6706812
  • Filename
    6706812