• DocumentCode
    949015
  • Title

    Machine vision-based gray relational theory applied to IC marking inspection

  • Author

    Jiang, Bernard C. ; Tasi, Szu-Lang ; Wang, Chien-Chih

  • Author_Institution
    Ind. Eng. & Manage. Dept., Yuan Ze Univ., Chung-li, Taiwan
  • Volume
    15
  • Issue
    4
  • fYear
    2002
  • fDate
    11/1/2002 12:00:00 AM
  • Firstpage
    531
  • Lastpage
    539
  • Abstract
    In the semiconductor industry, IC marking error remains a problem. The objective of this study is to identify IC marking using gray relational analysis. The gray theorem determines the gray relational grades of all of the selected factors by choosing the highest gray relational grade, even under incomplete information circumstances. In an IC marking identification procedure, an image is rotated and segmented first. Second, thresholding and thinning operations are applied to reduce the calculation complexity and extract features from the segmented image. Finally, the gray relational analysis method is applied to inspect the IC markings. The identification rate reaches 97.5%. As compared to traditional methods, there are three advantages in gray relational analysis: 1) No large amount of data is needed; 2) No specific statistical data distribution is required; and 3) There is no requirement for the independency of the factors to be considered. It is an easy and practical method in the field of IC marking inspection.
  • Keywords
    automatic optical inspection; computer vision; feature extraction; image segmentation; image thinning; mark scanning equipment; IC marking inspection; calculation complexity; features; gray relational theory; identification rate; incomplete information circumstances; machine vision; marking error; segmented image; statistical data distribution; thinning; thresholding; Character recognition; Electronics industry; Engineering management; Feature extraction; Image segmentation; Industrial engineering; Information analysis; Inspection; Machine vision; Text recognition;
  • fLanguage
    English
  • Journal_Title
    Semiconductor Manufacturing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0894-6507
  • Type

    jour

  • DOI
    10.1109/TSM.2002.804906
  • Filename
    1134171