An improved defect classification algorithm for six printing defects and its implementation on real printed circuit board images
Because decisions made by human inspectors often involve subjective judgment, in addition to being intensive and therefore costly, an automated approach for printed circuit board (PCB) inspection is preferred to eliminate subjective discrimination and thus provide fast, quantitative, and dimensional...
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my.utm.465902017-09-17T00:47:59Z http://eprints.utm.my/id/eprint/46590/ An improved defect classification algorithm for six printing defects and its implementation on real printed circuit board images Ibrahim, Ismail Ibrahim, Zuwairie Khalil, Kamal Mohd. Mokji, Musa Abu Bakar, Syed Ab. Rahman Wan Ahmad, Wan Khairunizam Mokhtar, Norrima QA76 Computer software Because decisions made by human inspectors often involve subjective judgment, in addition to being intensive and therefore costly, an automated approach for printed circuit board (PCB) inspection is preferred to eliminate subjective discrimination and thus provide fast, quantitative, and dimensional assessments. In this study, defect classification is essential to the identification of defect sources. Therefore, an algorithm for PCB defect classification is presented that consists of well-known conventional operations, including image difference, image subtraction, image addition, counted image comparator, flood-fill, and labeling for the classification of six different defects, namely, missing hole, pinhole, underetch, short-circuit, open-circuit, and mousebite. The defect classification algorithm is improved by incorporating proper image registration and thresholding techniques to solve the alignment and uneven illumination problem. The improved PCB defect classification algorithm has been applied to real PCB images to successfully classify all of the defects. 2012 Article PeerReviewed Ibrahim, Ismail and Ibrahim, Zuwairie and Khalil, Kamal and Mohd. Mokji, Musa and Abu Bakar, Syed Ab. Rahman and Wan Ahmad, Wan Khairunizam and Mokhtar, Norrima (2012) An improved defect classification algorithm for six printing defects and its implementation on real printed circuit board images. International Journal of Innovative Computing, Information and Control, 8 (5). pp. 3239-3250. ISSN 1349-4198 |
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QA76 Computer software Ibrahim, Ismail Ibrahim, Zuwairie Khalil, Kamal Mohd. Mokji, Musa Abu Bakar, Syed Ab. Rahman Wan Ahmad, Wan Khairunizam Mokhtar, Norrima An improved defect classification algorithm for six printing defects and its implementation on real printed circuit board images |
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Because decisions made by human inspectors often involve subjective judgment, in addition to being intensive and therefore costly, an automated approach for printed circuit board (PCB) inspection is preferred to eliminate subjective discrimination and thus provide fast, quantitative, and dimensional assessments. In this study, defect classification is essential to the identification of defect sources. Therefore, an algorithm for PCB defect classification is presented that consists of well-known conventional operations, including image difference, image subtraction, image addition, counted image comparator, flood-fill, and labeling for the classification of six different defects, namely, missing hole, pinhole, underetch, short-circuit, open-circuit, and mousebite. The defect classification algorithm is improved by incorporating proper image registration and thresholding techniques to solve the alignment and uneven illumination problem. The improved PCB defect classification algorithm has been applied to real PCB images to successfully classify all of the defects. |
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Article |
author |
Ibrahim, Ismail Ibrahim, Zuwairie Khalil, Kamal Mohd. Mokji, Musa Abu Bakar, Syed Ab. Rahman Wan Ahmad, Wan Khairunizam Mokhtar, Norrima |
author_facet |
Ibrahim, Ismail Ibrahim, Zuwairie Khalil, Kamal Mohd. Mokji, Musa Abu Bakar, Syed Ab. Rahman Wan Ahmad, Wan Khairunizam Mokhtar, Norrima |
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Ibrahim, Ismail |
title |
An improved defect classification algorithm for six printing defects and its implementation on real printed circuit board images |
title_short |
An improved defect classification algorithm for six printing defects and its implementation on real printed circuit board images |
title_full |
An improved defect classification algorithm for six printing defects and its implementation on real printed circuit board images |
title_fullStr |
An improved defect classification algorithm for six printing defects and its implementation on real printed circuit board images |
title_full_unstemmed |
An improved defect classification algorithm for six printing defects and its implementation on real printed circuit board images |
title_sort |
improved defect classification algorithm for six printing defects and its implementation on real printed circuit board images |
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2012 |
url |
http://eprints.utm.my/id/eprint/46590/ |
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1643652080413442048 |
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13.18916 |