• DocumentCode
    2466519
  • Title

    Color and illumination invariant dice recognition

  • Author

    Hsu, Gee-Sern ; Peng, Hsiao-Chia ; Yeh, Shang-Min

  • Author_Institution
    Artificial Vision Lab., Nat. Taiwan Univ. of Sci. & Technol., Taipei, Taiwan
  • fYear
    2012
  • fDate
    14-17 Oct. 2012
  • Firstpage
    857
  • Lastpage
    862
  • Abstract
    A system is proposed for automatic reading of the number of dots on dice in general table game settings. Different from previous dice recognition systems which recognize dice of a specific color using a single top-view camera in an enclosure with controlled settings, the proposed one uses multiple cameras to recognize dice of various colors posed in a wide range of viewing angle and under uncontrolled conditions. It is composed of three modules. Module-1 locates the dice using the gradient-conditioned color segmentation (GCCS), proposed in this paper, to segment dice of arbitrary colors from the background. Module-2 exploits the local invariant features good for building homographies across multiple views and lighting conditions. The homographies are used to enhance coplanar features and weaken non-coplanar features, giving a solution to segment the top faces of the dice and make up the features ruined by possible specular reflection. To identify the dots on the segmented top faces, an MSER detector is embedded in Module-3 for its consistency in locating the dot regions regardless of illumination and viewpoint variations. Experiments show that the proposed system performs satisfactorily in various test conditions.
  • Keywords
    feature extraction; gradient methods; image colour analysis; image segmentation; image sensors; lighting; object recognition; GCCS; MSER detector; color invariant dice recognition; coplanar features; gradient-conditioned color segmentation; homographies; illumination invariant dice recognition; lighting conditions; local invariant features; noncoplanar features; single top-view camera; table game settings; uncontrolled conditions; viewing angle; Cameras; Color; Detectors; Feature extraction; Image color analysis; Image edge detection; Lighting; Object recognition; foreground segmentation; invariant feature; local descriptor;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4673-1713-9
  • Electronic_ISBN
    978-1-4673-1712-2
  • Type

    conf

  • DOI
    10.1109/ICSMC.2012.6377835
  • Filename
    6377835