• DocumentCode
    2700453
  • Title

    Deciding the Number of Color Histogram Bins for Vehicle Color Recognition

  • Author

    Kim, Ku-Jin ; Park, Sun-Mi ; Choi, Yoo-Joo

  • Author_Institution
    Dept. of Comput. Eng., Kyungpook Nat. Univ., Daegu
  • fYear
    2008
  • fDate
    9-12 Dec. 2008
  • Firstpage
    134
  • Lastpage
    138
  • Abstract
    Given vehicle images, we suggest a way to recognize the color of the vehicle contained in the image. The color feature of a vehicle is represented by a color histogram, and we decide the appropriate number of color histogram bins, which mainly affects the successful recognition rate. After generating the histograms, template matching is used to decide the vehicle color. In HSI (hue saturation intensity) color space, experimental results show that the partition of H, S, and I into 8, 4, 4, respectively, achieves the highest success rate up to 88.34%.
  • Keywords
    image colour analysis; image recognition; vehicles; color histogram bins; hue saturation intensity; vehicle color recognition; vehicle images; Cameras; Colored noise; Feature extraction; Histograms; Image classification; Image recognition; Image retrieval; Image segmentation; Pixel; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Asia-Pacific Services Computing Conference, 2008. APSCC '08. IEEE
  • Conference_Location
    Yilan
  • Print_ISBN
    978-0-7695-3473-2
  • Electronic_ISBN
    978-0-7695-3473-2
  • Type

    conf

  • DOI
    10.1109/APSCC.2008.207
  • Filename
    4780665