Optimum threshold generation for automated visual inspection of large‐scale integration wafer patterns

The authors have developed a submicron‐level defect detection method that avoids the unnecessary detection of grains produced by some layers. As part of an automated visual inspection system for Large‐Scale Integration wafer multilayer patterns, the developed method can detect defects reliably by automatically generating an optimum threshold for each pattern according to the occurrence of grains in each area of the pattern, and then binarizing the subtracted grayscale images with the threshold. This method is used in comparison inspections of periodic cell patterns in the same die. This can be realized without using design pattern and process information. This paper proposes an edge‐preserving grain‐noise smoothing algorithm that generates a uniform threshold for each region surrounded by the pattern edges according to the grains detected using the multiple cell patterns to be inspected. It is confirmed through experiments with actual LSI wafers that defects on the order of 0.5 μm and greater, which exist at pattern edges and in the regions having no grains, can be detected stably without the unnecessary detection of grains, even with grain sizes on the order of 1 ∼ 1.3 μm in some layers.