Course content

Computer vision techniques build the basis for an automatic understanding and interpretation of digital images that today can be recorded with a multitude of different imaging devices (e.g. mobile phones, webcams, 3D depth-images, X-ray, MRI,... ). The course is concerned with extensions of basic image processing methods like image enhancement, feature detection and morphological image operations. Along with other techniques fundamental concepts for shape and region description, segmentation and hierarchical image representations are introduced. Useful for classification and recognition tasks the presented methods are applicable in many related areas like optical flow, stereo vision, industrial inspection, robotics and medical image processing.

Learning outcome

The course provides an overview and understanding of several fundamental techniques in Computer Vision. Advanced knowledge in this field is becoming increasingly more and more important. This is in particular true in view of the ever increasing availability of cameras and other imaging devices in nearly all areas of our society. The course helps to build the skills to design and construct advanced computer vision modules that function within a system to achieve the vision system's goals. Application fields include industrial areas, robotics and medical image processing. The learned subjects can be the basis of employment in industry or the public sector, or could be followed for doctoral research in Norway or overseas.

Learning methods and activities

Lectures and exercises. Lectures will be given in English. Portfolio assessment is the basis for the grade in the course. The portfolio includes a final written exam 70% and exercises 30%. The results for the parts are given in %-scores, while the entire portfolio is assigned a letter grade. If there is a re-sit examination, the examination form may change from written to oral. The examination papers will be given in English only. Students are free to choose Norwegian or English for written assessments.

Compulsory assignments

• Exercises

Recommended previous knowledge

TDT4195 Image Processing or equivalent.

Course materials

Book: Digital Image Processing, Rafael C. Gonzalez, Richard E. Woods (Publisher: Pearson)

Credit reductions