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Proceedings Paper

A review of SMD-PCB defects and detection algorithms
Author(s): Ahmad Fadzil Mohd Hani; Aamir Saeed Malik; Raja Kamil; Chung-Mun Thong
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Paper Abstract

Detection and classification of defects on surface mount device printed circuit board (SMD-PCB) is an important requirement in electronic manufacturing process. This process which is primarily performed by automatic optical inspection (AOI) system ensures the functionality and quality of manufactured products. In this paper, the pattern recognition algorithms proposed in the literature for the inspection of defects using AOI are reviewed. The review focuses on segmentation algorithms, choice of features and feature extraction algorithms as well as the types of classifier and their relative classification performance. The review spans a 20 year period from 1990 to 2011. The results of the review suggest that solder joint defect is the type of defects mostly investigated and that the trend is moving towards combining the results of more than one classifier to improve classification accuracy and robustness.

Paper Details

Date Published: 13 January 2012
PDF: 7 pages
Proc. SPIE 8350, Fourth International Conference on Machine Vision (ICMV 2011): Computer Vision and Image Analysis; Pattern Recognition and Basic Technologies, 83501P (13 January 2012); doi: 10.1117/12.920531
Show Author Affiliations
Ahmad Fadzil Mohd Hani, Univ. Teknologi Petronas (Malaysia)
Aamir Saeed Malik, Univ. Teknologi Petronas (Malaysia)
Raja Kamil, Univ. Putra Malaysia (Malaysia)
Chung-Mun Thong, ViTrox Corp. Berhad (Malaysia)


Published in SPIE Proceedings Vol. 8350:
Fourth International Conference on Machine Vision (ICMV 2011): Computer Vision and Image Analysis; Pattern Recognition and Basic Technologies
Safaa S. Mahmoud; Zhu Zeng; Yuting Li, Editor(s)

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