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

机译:基于机器视觉的灰色关联理论在IC标记检测中的应用

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摘要

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.
机译:在半导体工业中,IC标记错误仍然是一个问题。这项研究的目的是使用灰色关联分析来识别IC标记。灰色定理通过选择最高的灰色关联度来确定所有选定因素的灰色关联度,即使在信息不完整的情况下。在IC标记识别过程中,首先旋转图像并进行分割。其次,应用阈值和细化操作以减少计算复杂度并从分割的图像中提取特征。最后,采用灰色关联分析法对IC标记进行检测。识别率达到97.5%。与传统方法相比,灰色关联分析具有三个优点:1)不需要大量数据; 2)不需要特定的统计数据分布; 3)不需要考虑因素的独立性。在IC标记检查领域,这是一种简便实用的方法。

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