Learning outcome

After having completed the course, the student has knowledge about central techniques for image processing and image analysis, the theoretical foundation for these techniques, and how the techniques are implemented. The student is familiar with a number of different fields of applications for image processing and image analysis. The student has the skills to apply relevant image processing operations using existing tools, and is able to implement basic image processing operations in an object oriented programming language.

Course Description

Representation of digital images, and fields of application of digital image processing and image analysis. Different techniques for contrast enhancement, noise reduction, segmentation, feature extraction, and classification based on such features. The theoretical foundation for the techniques, and how to implement them.

Teaching and Learning Methods

4-5 hours of lectures, exercises and supervision per week.

Assessment Methods

Four hours individual, written final exam. A number of obligatory exercises must be passed before you can take the exam.

Minor adjustments may occur during the academic year, subject to the decision of the Dean