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Automated Bare Board Defect Detection using Pattern Subtraction Technique

by Jithendra P.R. Nayak, Parameshachari B.D.
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 183 - Number 36
Year of Publication: 2021
Authors: Jithendra P.R. Nayak, Parameshachari B.D.

Jithendra P.R. Nayak, Parameshachari B.D. . Automated Bare Board Defect Detection using Pattern Subtraction Technique. International Journal of Computer Applications. 183, 36 ( Nov 2021), 11-15. DOI=10.5120/ijca2021921744

@article{ 10.5120/ijca2021921744,
author = { Jithendra P.R. Nayak, Parameshachari B.D. },
title = { Automated Bare Board Defect Detection using Pattern Subtraction Technique },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2021 },
volume = { 183 },
number = { 36 },
month = { Nov },
year = { 2021 },
issn = { 0975-8887 },
pages = { 11-15 },
numpages = {9},
url = { },
doi = { 10.5120/ijca2021921744 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-07T01:18:48.046976+05:30
%A Jithendra P.R. Nayak
%A Parameshachari B.D.
%T Automated Bare Board Defect Detection using Pattern Subtraction Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 183
%N 36
%P 11-15
%D 2021
%I Foundation of Computer Science (FCS), NY, USA

A Bare board or printed circuit board is the mechanical support that connects the electrical equipment using advanced means, track or signal tracked on copper sheets attached to a continuous substrate. Automated testing of PCBs serves a traditional purpose in computer technology. Aim is to free human inspectors from the inefficient and tedious task of detecting those defects in PCBs that could lead to failure. By comparing a typical PCB image with a faulty PCB image, using a simple extraction algorithm that can highlight major problem areas. Then perform a different image processing function such as blocking the image and filtering the image to remove unwanted edges and sound present in the wrong image and also the effect of noise on the PCB image is eliminated. This method should detect which method is appropriate to obtain the wrong image. Finally, segmentation is used to identify the source of the six various defects such as under etch, mouse bite, pin hole, missing hole, open rotation and short circuit.

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Index Terms

Computer Science
Information Sciences


Image Processing Printed Circuit Board Defect Classification