Opintojakso, lukuvuosi 2023–2024
KONE.522
Machine Vision, 5 op
Tampereen yliopisto
- Kuvaus
- Suoritustavat
Opetusperiodit
Aktiivinen periodissa 1 (1.8.2023–22.10.2023)
Aktiivinen periodissa 2 (23.10.2023–31.12.2023)
Koodi
KONE.522Opetuskieli
englantiLukuvuodet
2022–2023, 2023–2024Opintojakson taso
Syventävät opinnotArvosteluasteikko
Yleinen asteikko, 0-5Vastuuhenkilö
Vastuuopettaja:
Niko SiltalaVastuuorganisaatio
Tekniikan ja luonnontieteiden tiedekunta 100 %
Järjestävä organisaatio
Konetekniikan opetus 100 %
Ydinsisältö
- Machine vision in production automation: Typical applications (2D/3D). Typical system structures. Commonly used 2D and 3D imaging methods.
- Machine vision hardware:
* Different system types (PC based system, smart camera based system)
* Camera types and selection principles: Specifying camera resolution (field-of-view, spatial resolution) and resulting expected measurement resolution.
* Lenses and other optical components: Specifying lens focal length.
* Illumination in machine vision: Importance of illumination concerning the resulting image. Illumination methods and light sources. - Machine vision software and image processing:
Digital image. Typical functionality and special properties of machine vision software. Common programming concepts and methods in machine vision. - Typical machine vision applications/tasks in production automation:
Checking the presence/counting parts - methods
Locating parts for robot pickup - robot and machine vision calibration
Dimensional measurements - measurement accuracy and/or uncertainty
Täydentävä tietämys
- Typical color camera vs. grey-scale camera. Shutter types.
Concepts of depth-of-focus/depth-of-field and optical resolution. - Effect of different light colors (wavelengths).
- Understanding basic operating principles of the most commonly used machine vision software algorithms.
Programming simple machine vision application. - Communicating with other equipment.
Calibrating machine vision system and combining camera and robot coordinates.
Calculating measurement uncertainty.
Osaamistavoitteet
Esitietovaatimukset
Lisätiedot
Oppimateriaalit
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Suoritustapa 1
This completion option (suoritustapa) is primary intended for degree students at TAU, Tampere. Completed and accepted assignments and exercises about topics discussed during the lectures. Accepted project work.
Osallistuminen opetukseen
29.08.2023 – 20.12.2023
Aktiivinen periodissa 1 (1.8.2023–22.10.2023)
Aktiivinen periodissa 2 (23.10.2023–31.12.2023)