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Courses in summer term 2017 / Lecture Computer Vision

The course introduces the basic concepts of image processing. Starting with basic methods of image representation, methods of feature extraction, eg of edges, textures and movement, and image analysis, eg the image segmentation, image regularization and image classification presented.

Textbooks:

  1. Milan Sonka, Vaclav Hlavac, Roger Boyle (2008): Image Processing, Analysis, and Machine Vision, Thomson.
  2. John C. Russ, J. Christian Russ (2008): Introduction to Image Processing and Analysis, CRC Press.
  3. R. C. Gonzalez, R. E Woods (2008): Digital Image Processing, Pearson.
  4. David R. Forsyth, Jean Ponce (2003): Computer Vision: a Modern Approach, Prentice Hall.
  5. G. Aubert, P. Kornprobst (2006): Mathematical Problems in Image Processing. Partial Differential Equations and the Calculus of Variations, Springer.
  6. J. R. Parker (1997): Algorithms for Image Processing and Computer Vision, Wiley.

Lecturer: Prof. Dr. Dr. Lars Schmidt-Thieme
Trainer: Hanh Nguyen
 
Lecture:
Time: Mon 10-12
Location: D 017
Begin: 03.04.2017
Assignment: MSc WI & IMIT & DA
 
Tutorial:
Time: Wed 16-18
Location: P1a
Begin: 12.04.2017
 
Exam:
Date: 28.07.2017
Location:
Begin:
Length: 120 min
 
Exam retake:
Date: 10.10.2017
Location:
Begin:
Length: 120 min
 
More:
Moodle:Moodle
LSF:LSF
Modul- Handbuch:MHB
Last Lecture: here