Machine Vision in Production, 5 op

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 cameras)​

  • 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 and algorithms​
  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 illumination colors (wavelengths).
  
• Understanding basic operating principles of the most 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.