In this paper, we refer to images obtained by mapping dots observed during defect inspections as secondary images. We propose a method of extracting information for specifying the causes of distinctive structural patterns that appear in the secondary images. We suggest the use of a light process for conducting real-time inspection and the feature extraction process simultaneously. The patterns that appear in the secondary images are lines and random dots. In this study, we focus on the recognition of vertical or horizontal line patterns. Vertical or horizontal line patterns are characteristic of secondary images and appear frequently in these images. In parametric space, vertical and horizontal lines are constrained in a specific area. Since our method involves the use of constraints, it performs fast characteristic extractions. Our method is robust to the variation of the average dot densities of the secondary image and helps to realize low-cost recognition.
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