NDLI: Defect detection of PCB based on Bayes feature fusion

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Defect detection of PCB based on Bayes feature fusion

Content Provider	IET Digital Library
Author	Lu, Zhisheng He, Qinqin Xiang, Xinguang Liu, Hong
Abstract	With the continuous development of the electronics industry, the number of printed circuit board (PCB) has grown at a rapid rate, and the requirements for the detection systems of PCB have also continuously increased. In the traditional PCB detection, the main reference is the comparison method. However, in a real scene, there are a series of problems such as non-uniform illumination, tilting of the camera angle, and the like, resulting in a less satisfactory effect of the reference comparison method. So, the authors proposed a non-reference comparison framework of PCB defects detection. This framework has achieved good results in speed and accuracy. The authors extract the histogram of oriented gradients and local binary pattern features for each PCB image, respectively, put into the support vector machine to get two independent models. Then, according to Bayes fusion theory, the authors fuse two models for defects classification. The authors have established a PCB data set that includes both defective and defect-free. It has been verified that the accuracy of the verification set is improved compared to the individual features using the fused features. The authors also illustrate the effectiveness of Bayes feature fusion in terms of speed.
Starting Page	1741
Ending Page	1745
Page Count	5
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.2018.8270
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 Optical Inspection Bayes Feature Fusion Bayes Fusion Theory Bayes Method Computer Vision And Image Processing Technique Defect Classification Electronic Engineering Computing Electronics Industry Feature Extraction Fused Feature Image Classification Image Fusion Image Recognition Knowledge Engineering Technique Local Binary Pattern Feature Nonreference Comparison Framework Nonuniform Illumination PCB Data Set PCB Defect Detection PCB Image Printed Circuit Printed Circuit Board Reference Comparison Method Statistics Support Vector Machine Traditional PCB Detection
Content Type	Text
Resource Type	Article

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