NDLI: Recurrent spatial transformer network for high-accuracy image registration in moving PCB defect detection

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Recurrent spatial transformer network for high-accuracy image registration in moving PCB defect detection

Content Provider	IET Digital Library
Author	Huang, Weibo Hua, Guoliang Yu, Zhaofu Liu, Hong
Abstract	Defects detection is an extremely important part in the production of printed circuit board (PCB) to guarantee the quality and reliability. A widely used and researched method for this task is referential comparison method. However, this method gets poor performance on the situation that PCB moves on the conveyor, due to the lack of ability to register test images with referential images. Therefore, accurate image registration which estimates the affine transformation between the captured test images and the referential images becomes an urgent problem to be solved. In this study, a spatial transformer network is proposed. In particular, a recurrent image registration strategy is introduced to step-by-step register the images in a recurrent progress. Furthermore, a referential part is designed to help training the network. Besides, in order to simulate the real moving PCB images and train the proposed model, a factitious dataset is generated by applying random affine transformations to real PCB images. Experiments show that recurrent spatial transformer network can achieve pixel-level accurate image registration. The defects detection precision of referential comparison method has a great improvement by using the registration algorithm.
Starting Page	438
Ending Page	443
Page Count	6
Volume Number	2020
e-ISSN	20513305
Issue Number	Issue 13, Jul (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/joe/2020/13
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/joe.2019.1182
Journal	The Journal of Engineering
Publisher	The Institution of Engineering and Technology
Publisher Date	2020-01-13
Access Restriction	Open
Rights License	Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Subject Keyword	Affine Transforms Automatic Optical Inspection Captured Test Image Computer Vision And Image Processing Technique Defects Detection Precision Electronic Engineering Computing High-accuracy Image Registration Image Registration Inductors And Transformer Integral Transforms Integrated Circuit Reliability Moving PCB Image Object Detection Optical, Image And Video Signal Processing PCB Defect Detection Pixel-level Accurate Image Registration Printed Circuit Printed Circuit Board Random Affine Transformations Recurrent Image Registration Strategy Recurrent Spatial Transformer Network Referential Comparison Method Referential Image Registration Algorithm Reliability Transformer
Content Type	Text
Resource Type	Article

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