INF9305 – Digital Image Analysis
Schedule, syllabus and examination date
Digital images and their properties. Data structures for image analysis. Construction of 2D and 3D filters for image enhancement and analysis. Segmentation and description of objects in images. Pattern recognition. Supervised and unsupervised classification.
The student will bet a basic understanding of concepts, methods and applications of image analysis, pattern recognition, and image classification.
In addition, each PhD student will be given an extended curriculum within the field/research area of the course. The syllabus must be approved by the lecturer so that the student can be admitted to the final exam.
PhD candidates from the University of Oslo should apply for classes and register for examinations through Studentweb.
If a course has limited intake capacity, priority will be given to PhD candidates who follow an individual education plan where this particular course is included. Some national researchers’ schools may have specific rules for ranking applicants for courses with limited intake capacity.
PhD candidates who have been admitted to another higher education institution must apply for a position as a visiting student within a given deadline.
Recommended previous knowledge
The course comprises 2 hours of lectures and 2 hours of exercises per week.
Oral or written (4 hours) examination. All mandatory assignments have to be accepted in order to take the exam.
Grades are awarded on a pass/fail scale. Read more about the grading system.
Explanations and appeals
Resit an examination
Students who can document a valid reason for absence from the regular examination are offered a postponed examination at the beginning of the next semester.
Re-scheduled examinations are not offered to students who withdraw during, or did not pass the original examination.
Note that the first lecture is compulsory. The subject is regarded equal to INF269 and INF3300 when practicing exam regulations.