Assembly Error Detection with OpenCV
Karvonen, Ville (2023)
2023
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2023120835240
https://urn.fi/URN:NBN:fi:amk-2023120835240
Tiivistelmä
The objective for this thesis was to study how computer vision system could be used to detect manual assembly errors on production line. OpenCV library was used to program error detection functions and a prototype tester was built to see how error detection process works in practice. The study was a commission from Aava Mobile Oy.
The thesis goes through the steps of building a computer vision setup to software development with OpenCV. Common hardware options for computer vision systems were studied. The software development part focuses on OpenCV and some of its most useful methods for automated image manipulation.
The project gave a detailed view of how machine vision system works. It showed what kind of results could be expected with a computer vision system setup as in the project. Accumulated knowledge can be used to further develop a computer vision based error detection system for production.
The thesis goes through the steps of building a computer vision setup to software development with OpenCV. Common hardware options for computer vision systems were studied. The software development part focuses on OpenCV and some of its most useful methods for automated image manipulation.
The project gave a detailed view of how machine vision system works. It showed what kind of results could be expected with a computer vision system setup as in the project. Accumulated knowledge can be used to further develop a computer vision based error detection system for production.