Computer-Assisted Image Analysis II

10 credits

Syllabus, Master's level, 1TD398

A revised version of the syllabus is available.
Code
1TD398
Education cycle
Second cycle
Main field(s) of study and in-depth level
Computer Science A1F, Technology A1F
Grading system
Pass with distinction, Pass with credit, Pass, Fail
Finalised by
The Faculty Board of Science and Technology, 18 March 2010
Responsible department
Department of Information Technology

Entry requirements

120 credits including Computer-Assisted Image Analysis I or equivalent. At least 5 credits in mathematical statistics.

Learning outcomes

To pass, the student should be able to

  • describe and use advanced filtering methods for noise reduction and edge enhancement;
  • describe and use several sophisticated segmentation methods, image based as well as model based;
  • describe digital topology and geometry in 2 and 3 dimensions;
  • apply classification algorithms to interpret image contents;
  • describe how several image measurement techniques work.

Content

Methods for solving problems in image analysis. Analysis of 3D images (volume, stereo, and time series). Image enhancement. Image segmentation and border detection. Registration of images, search methods and optimisation. Digital geometry and mathematical morphology. Object measurement and characterisation. Classification. Computer vision.

Instruction

Lectures, laboratory work and compulsory assignments.

Assessment

Written examination at the end of the course (6 credits), and approved compulsory assignments (4 credits).

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