초록

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Abstract ▼ AI-Helper

According as the patterns of PCB (Printed Circuit Board) become denser and complicated, human operator can no longer inspect PCB visually with accuracy and fastness. Thus, automatic visual inspection of PCB is required. Automatic visual inspection approaches to detect faults in PCB can be classifie...

According as the patterns of PCB (Printed Circuit Board) become denser and complicated, human operator can no longer inspect PCB visually with accuracy and fastness. Thus, automatic visual inspection of PCB is required. Automatic visual inspection approaches to detect faults in PCB can be classified into two: reference comparison and design rule verification. In the first approach, test PCB patterns are compared with reference model. This paper presents how to generate reference model directly from Gerber CAD data, assuming models are represented by PAHG(Pattern Attributed HyperGraph). We develop 1) an implemental scheme of PAHG, and 2) several algorithms for segmenting, partitioning regions, and extracting regional relations from PCB CAD data instead of PCB image data. Experimental results show the validity of the proposed schemes.