• DocumentCode
    2263766
  • Title

    Diamond color grading based on machine vision

  • Author

    Ren, Zhiguo ; Liao, Jiarui ; Cai, Lilong

  • Author_Institution
    Dept. of Mech. Eng., Hong Kong Univ. of Sci. & Technol., Kowloon, China
  • fYear
    2009
  • fDate
    Sept. 27 2009-Oct. 4 2009
  • Firstpage
    1970
  • Lastpage
    1976
  • Abstract
    This paper presents an effective method for diamond color grading based on machine vision. In order to acquire satisfactory diamond images, a special light source based on an integrating sphere is employed. After compensating the fluctuation of the light source, the compositive color features, including independent and joint distribution features of Hue and Saturation, are extracted in segmented uniform regions. Then, depending on a trained BP Neural Network, diamonds can be graded by color. Experiment results show that the proposed method can reach a satisfactory accuracy to replace manual grading for real diamonds. The proposed method can also be used to classify other objects by small color difference.
  • Keywords
    backpropagation; computer vision; feature extraction; image colour analysis; image segmentation; neural nets; compositive color features; diamond color grading; diamond images; independent distribution features; joint distribution features; machine vision; segmented uniform regions; special light source; trained BP neural network; Charge coupled devices; Fluctuations; Focusing; Image segmentation; Light sources; Machine vision; Mechanical engineering; Neural networks; Optical modulation; Optical refraction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision Workshops (ICCV Workshops), 2009 IEEE 12th International Conference on
  • Conference_Location
    Kyoto
  • Print_ISBN
    978-1-4244-4442-7
  • Electronic_ISBN
    978-1-4244-4441-0
  • Type

    conf

  • DOI
    10.1109/ICCVW.2009.5457523
  • Filename
    5457523