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PR Digital Image Processing

Learning Outcome

The practical course offers insight into the field of digital image processing:

  • Image acquisition with industrial and consumer cameras
  • Image acquisition and image processing with Matlab
  • Illumination
  • Scene and setup

Course Content

The course consists of the following six main exercises:

  1. Projections, aberrations and metric calibration
  2. Image segmentation
  3. Color segmentation
  4. 3D geometry reconstruction using weakly structured lighting
  5. Parameter estimation, motion deblurring and image stitching
  6. Cognex VisionPro

and the following three additional exercies:

  • Determination of the Model Parameters of a Pendulum
  • Image Processing for Rotating Objects
  • Automated parameter estimation

Learning Methods and Activities

  • Groups of two students do five out of six main exercises and one additional exercise. They have to write one lab report for one of the main exercises and a lab report for the additional exercise.
  • Groups of three students do each of the six main exercises and one additional exercise. They have two write lab reports for two of the main exercises and a lab report for the additional exercise.

The assignment of main exercices to the course dates is organized as follows: For date t (1 to 6), group g (1 to 5) has to prepare the main exercise u = [(t+g-2)%6]+1, where % is the modulo operation.
Example: Group 1 prepares the first exercise for the first date, group 2 the second exercise, and so on...

Grading

  • Participation/motivation
  • Digital documentation of all exercises
  • Written reports

Literature

  • D. Hofer, A. Winkler, P. Hölzl, M. Degelsegger, "Practical Course: Digital Image Processing", course material (english, refer to bibliography for more references)

Language

German