• DocumentCode
    593203
  • Title

    Automatic counting of packaged wafer die based on machine vision

  • Author

    Hsuan-Ting Chang ; Ren-Jie Pan

  • Author_Institution
    Dept. of Electr. Eng., Nat. Yunlin Univ. of Sci. & Technol., Yunlin, Taiwan
  • fYear
    2012
  • fDate
    14-16 Aug. 2012
  • Firstpage
    274
  • Lastpage
    277
  • Abstract
    This paper presents a robust method to automatically determine the number of packaged dies in the residual wafer image, in which most dies have been removed and packaged. We propose the die segmentation region detection algorithm based on vertically and horizontally cumulative histograms and die detection algorithm based on YCbCr color space. The abnormal cases of fractional dies in the wafer boundary and dropped dies during packaging are considered in the proposed method as well. In the experimental results, the proposed method achieves 100% accuracy in counting the number of packaged dies in the ten test cases.
  • Keywords
    computer vision; image colour analysis; image segmentation; production engineering computing; wafer level packaging; YCbCr color space; automatic counting; die detection algorithm; die segmentation region detection algorithm; horizontally cumulative histogram; machine vision; packaging; residual wafer image; vertically cumulative histogram; wafer die packaging; Conferences; Gray-scale; Histograms; Image color analysis; Image recognition; Image segmentation; Machine vision; IC packaging; YCbCr color space; die; optical inspection; wafer;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Security and Intelligence Control (ISIC), 2012 International Conference on
  • Conference_Location
    Yunlin
  • Print_ISBN
    978-1-4673-2587-5
  • Type

    conf

  • DOI
    10.1109/ISIC.2012.6449759
  • Filename
    6449759