Abstract
This paper studies automatic optical inspection for detecting defects on the printed circuit board inner layer. The development of this study can be divided into five stages, they are reference image rebuilding, inspection image normalization, image subtraction, defects separation and defect classification. In the image subtraction stage, the difference between the reference image from the printed circuit board design and the inspected image is checked for defects. Each defect region is separated using a defect outer boundary tracing method. A boundary state transition method is proposed to classify the defect types. This system can recognize eight defect types, open, mouse bite, pinhole, missing conductor, short, spur, excess copper and missing hole. In addition, a comparison with the methods described in the literature is made, proving that the proposed method produces better results .
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References
Moganti M, Ercal F (1996) Automatic PCB inspection algorithms: a survey. Comput Vis Image Underst 63(2):287–313
Hamada T, Nakahata K, Nomoto M, Nakagawa Y, Hashimoto Y, Karasaki K (1990) Automated pattern inspection system for PCB photomasks using design pattern comparison method. 16th Annual Conference of IEEE (IECON ’90), vol. 1, pp 780–785
Ito M, Nikaido Y (1991) Recognition of pattern defects of printed circuit board using topological information. Eleventh IEEE/CHMT International Electronics Manufacturing Technology Symposium, pp 202–206
Wu W-Y, Wang M-J, Liu C-M (1996) Automated inspection of printed circuit boards through machine vision. Comput Ind 28:103–111
Tatibana MH, Lotufo R de A (1997) Novel automatic PCB inspection technique based on connectivity. Proceedings of 10th Brazilian Symposium on Computer Graphics and Image Processing, pp 187–194
Borba JF Facon J (1995) A printed circuit board automated inspection system. Proceedings of the 38th Midwest Symposium on Circuits and Systems, pp 69–72
Ito M, Fujita I, Takeuchi Y, Uchida T (1993) Pattern defect analysis and evaluation of printed circuit boards using CAD data. Fifteenth IEEE/CHMT International Electronics Manufacturing Technology Symposium, pp 7–10
Sonka M, Hlavac V Boyle R (1998) Image processing, analysis, and machine vision, 2nd edn. Brooks/Cole, CA
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Rau, H., Wu, CH. Automatic optical inspection for detecting defects on printed circuit board inner layers. Int J Adv Manuf Technol 25, 940–946 (2005). https://doi.org/10.1007/s00170-004-2299-9
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DOI: https://doi.org/10.1007/s00170-004-2299-9