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Machine Vision and Applications
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Image registration for automated inspection of printed circuit patterns using CAD reference data

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Abstract

An image registration approach for inspection of printed circuit patterns which has been validated on a prototype system is described. The offline procedure forms, selects, prioritizes, and sorts registration features from CAD-generated reference data. A feature is selected if it satisfies clearance rules that account for the maximum expected discongruence between captured and reference images. The sorting scheme considers the detection complexity of a feature and its distance away from the center of the expected image, since outer features represent potential global distortions better. The runtime registration procedure detects features and finds the parameters that transform pixels into reference data coordinates and vice versa. We represent robust feature-measurement techniques that offer accurate subpixel localization and verify feature authenticity. We describe an edge-detection technique based on a novel way of authenticating zero-crossings and a method that disqualifies edges detected on defects of the part under inspection. © 1993 Springer-Verlag.

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Machine Vision and Applications

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