Proceedings of the 2018 International Conference on Mechanical, Electrical, Electronic Engineering & Science (MEEES 2018)

Design of Machine Vision Defect Detecting System Based on Halcon

Authors
Bin Xu, Wenbo Ye, Yurong Wang
Corresponding Author
Bin Xu
Available Online May 2018.
DOI
10.2991/meees-18.2018.61How to use a DOI?
Keywords
machine vision; defect detecting; Industry4.0; Intelligent manufacturing.
Abstract

It can be predicted that Industry4.0 is the general trend of mechanized integrated production in the future. In the field of Industry4.0, people have begun to focus on machine vision inspection. A defect detection machine vision system based on image processing software called Halcon is designed in this paper, which is designed to detect the bad spots on the screen in the production line, the defects of the PCB circuit board on the production line, as well as the scratches and cracks of the ceramic tiles on the production line. This design can be used to eliminate inferior products and strictly control the output rate of finished products.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 International Conference on Mechanical, Electrical, Electronic Engineering & Science (MEEES 2018)
Series
Advances in Engineering Research
Publication Date
May 2018
ISBN
978-94-6252-534-4
ISSN
2352-5401
DOI
10.2991/meees-18.2018.61How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Bin Xu
AU  - Wenbo Ye
AU  - Yurong Wang
PY  - 2018/05
DA  - 2018/05
TI  - Design of Machine Vision Defect Detecting System Based on Halcon
BT  - Proceedings of the 2018 International Conference on Mechanical, Electrical, Electronic Engineering & Science (MEEES 2018)
PB  - Atlantis Press
SP  - 350
EP  - 354
SN  - 2352-5401
UR  - https://doi.org/10.2991/meees-18.2018.61
DO  - 10.2991/meees-18.2018.61
ID  - Xu2018/05
ER  -