Image Analysis is given by the Department of Mathematics at the Faculty of Engineering. The course is also available for students enrolled in the Bachelor´s or Master´s Programme in Mathematics at the Faculty of Science who can take this course as an optional course on upper basic level within their programme. Also, a version of the course can be taken by Ph.D students from both faculties.

The course codes are as follows for the different student categories:

FMAN20, 7.5 credits, for students at Faculty of Engineering
MATC20, 7.5 credits, for students at Faculty of Science
FMA171F, 7.5 credits, for Ph.D students

Course contents

The aim of the course is to give necessary knowledge of digital image analysis for further research within the area and to be able to use digital image analysis within other research areas such as computer graphics, image coding, video coding and industrial image processing problems. The aim is also to prepare the student for further studies in e.g. computer vision, multispectral image analysis and statistical image analysis.

Teaching
The teaching consists of lectures and computer laboratory sessions. We have two (and some weeks three) lectures each week. The lab sessions are meant to be help for the assignments. See course program below for details.

Assessment
The course is assessed through written assignments during the course and possibly a written take-home examination and an associated oral examination. To be awarded a pass with distinction (or grade 4-5), the candidate must pass the take-home examination and an oral examination with distinction.

Course Literature
Szeliski, Computer Vision - Algorithms and Applications, Springer. (Available on-line.)
Forsyth & Ponce, Computer Vision - A Modern Approach, Pearson Education, ISBN 0-13-191193-7. (Optional.)

Links