• DocumentCode
    2028436
  • Title

    A fast traffic sign detection and classification system based on fusion of colour and morphological information

  • Author

    Khodadadzadeh, Mahdi ; Sarrafzade, Omid ; Ghassemian, Hassan

  • Author_Institution
    Dept. of Electr. Eng., Tarbiat Modares Univ., Tehran, Iran
  • fYear
    2010
  • fDate
    27-28 Oct. 2010
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    A new method for automatic classification of traffic signs is proposed in this paper. The proposed method is based on the fusion of colour and morphological information. The strategy consists of three steps. First, colour information in HSI colour space is used to segment the input image and finding the region of interests (ROIs) with red pixels. Then, morphological profile is building by employing opening and closing operators on each band of colour image. Next, statistical feature extraction is performed based on both morphological profile and original colour image. Finally, the feature vector is classified by support vector machines based on one-vs.-rest method. The proposed method was tested on domestic database including four classes of red signs. Experimental results show the hit-rate of about 97% in considerably low process time.
  • Keywords
    driver information systems; feature extraction; image classification; image colour analysis; image fusion; image segmentation; mathematical morphology; object detection; support vector machines; HSI; colour image analysis; colour space; feature vector; image segmentation; information fusion; morphological profile; region of interests; statistical feature extraction; support vector machines; traffic sign classification; traffic sign detection; Feature extraction; Image color analysis; Pixel; Roads; Shape; Support vector machine classification; Data fusion; morphological profile; statistical features; support vector machines (SVMs); traffic sign classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Vision and Image Processing (MVIP), 2010 6th Iranian
  • Conference_Location
    Isfahan
  • Print_ISBN
    978-1-4244-9706-5
  • Type

    conf

  • DOI
    10.1109/IranianMVIP.2010.5941175
  • Filename
    5941175