• DocumentCode
    539530
  • Title

    A Method of Traffic Sign Detecting Based on Color Similarity

  • Author

    Chuan, Lin ; Shenghui, Pan ; Fan, Zhang ; Li Menghe ; Baozhong, Ke

  • Author_Institution
    Dept.of Electron. Inf. & Control Eng., Guangxi Univ. of Technol., Liuzhou, China
  • Volume
    1
  • fYear
    2011
  • fDate
    6-7 Jan. 2011
  • Firstpage
    123
  • Lastpage
    126
  • Abstract
    In order to detect traffic sign effectively and quickly, firstly, this paper firstly discriminates the maximum and minimum values of the color-components R, G and B, and then ignores pixels having little color similarity with traffic sign. Secondly, it regards the points of RGB space as color eigenvector and calculates the cosine value of included angle of vectors to discriminate color similarity. Thirdly, the image is divided into core image, undetermined area and background area by setting two thresholds, and then two corresponding templates and modes are used to scan the image, realizing growth of core image by area mergence. Finally, the operator Roberts is applied to detect fringe of the traffic sign. The experimental result shows that the method has better result of detection both in sunny and in rainy day. The process of detecting avoids huge amount of calculation for color space conversion, and improves the speed of calculation, which will lay the foundation for recognition of traffic sign.
  • Keywords
    image colour analysis; image recognition; object detection; RGB components; Roberts operator; background area; color eigenvector; color similarity; color space conversion; edge detection; image recognition; traffic sign detection; undetermined area; Color; Equations; Image color analysis; Image edge detection; Image segmentation; Mathematical model; Pixel; Color similarity; Edge detection; Growth of core image; Human vision system; Traffic sign;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Measuring Technology and Mechatronics Automation (ICMTMA), 2011 Third International Conference on
  • Conference_Location
    Shangshai
  • Print_ISBN
    978-1-4244-9010-3
  • Type

    conf

  • DOI
    10.1109/ICMTMA.2011.36
  • Filename
    5720737