eprintid: 3065
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/30/65
datestamp: 2023-11-09 15:51:19
lastmod: 2023-11-09 15:51:19
status_changed: 2023-11-09 15:44:54
type: conference_item
metadata_visibility: show
creators_name: Mohd. Hani, A.F.
creators_name: Malik, A.S.
creators_name: Kamil, R.
creators_name: Thong, C.-M.
title: A review of SMD-PCB defects and detection algorithms
ispublished: pub
keywords: AOI; Automatic optical inspection; Classification accuracy; Classification of defects; Classification performance; Detection algorithm; Electronic manufacturing; Feature extraction algorithms; Manufactured products; Pattern recognition algorithms; Segmentation algorithms; SMD-PCB; Solder-joint defects; Surface mount device, Algorithms; Classifiers; Computer vision; Feature extraction; Image analysis; Image segmentation; Optical testing; Organic pollutants; Polychlorinated biphenyls; Printed circuit boards, Defects
note: cited By 8; Conference of 4th International Conference on Machine Vision: Computer Vision and Image Analysis; Pattern Recognition and Basic Technologies, ICMV 2011 ; Conference Date: 9 December 2011 Through 10 December 2011; Conference Code:88614
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. © 2012 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).
date: 2012
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84857293372&doi=10.1117%2f12.920531&partnerID=40&md5=8e191f5c136ce145587612d3be54a5ab
id_number: 10.1117/12.920531
full_text_status: none
publication: Proceedings of SPIE - The International Society for Optical Engineering
volume: 8350
place_of_pub: Singapore
refereed: TRUE
isbn: 9780819490261
issn: 0277786X
citation:   Mohd. Hani, A.F. and Malik, A.S. and Kamil, R. and Thong, C.-M.  (2012) A review of SMD-PCB defects and detection algorithms.  In: UNSPECIFIED.