NDLI: CNN-based reference comparison method for classifying bare PCB defects

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CNN-based reference comparison method for classifying bare PCB defects

Content Provider	IET Digital Library
Author	Wei, Peng Liu, Chang Liu, Mengyuan Gao, Yunlong Liu, Hong
Abstract	Printed circuit board (PCB) inspection is an essential part of PCB production process. Traditional PCB bare board defect detection methods have their own defects. However, the PCB bare board defect detection method based on automatic optic inspection is a feasible and effective method, and it is having more and more application in industry. Based on the idea of the reference comparison method, this study aims at studying the classification of defects. First of all, the method of extracting defect areas using morphology is studied; meanwhile, a data set containing 1818 images with 6 different detailed defect area image parts are produced. Then, in order to classify defects accurately, a traditional classification algorithm based on digital image processing was attempted, and a defect classification algorithm based on convolutional neural network was proposed. After experimental demonstration, in the actual results, the defect classification algorithm based on convolutional neural network can achieve a fairly high classification accuracy (95.7%), which is much higher than the traditional method, and the new method has stronger stability than the traditional one.
Starting Page	1528
Ending Page	1533
Page Count	6
Volume Number	2018
e-ISSN	20513305
Issue Number	Issue 16, Nov (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/joe/2018/16
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/joe.2018.8271
Journal	The Journal of Engineering
Publisher	The Institution of Engineering and Technology
Publisher Date	2018-08-16
Access Restriction	Open
Rights License	Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Subject Keyword	Automatic Optic Inspection Automatic Optical Inspection Bare PCB Defect Classification Algorithm CNN-based Reference Comparison Method Computer Vision And Image Processing Technique Convolutional Neural Network Digital Image Processing Electronic Engineering Computing Image Classification Image Recognition Neural Computing Technique Neural Nets PCB Bare Board Defect Detection Method PCB Production Process Printed Circuit Printed Circuit Board Inspection Reference Comparison Method
Content Type	Text
Resource Type	Article

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