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

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.