IN9520 – Digital Image Analysis
Course description
Course content
The course covers methods for analysis of digital images, segmentation, and object description. Central topics are feature extraction and classification of objects in images.
Learning outcome
After this course:
- You have very good knowledge on methods for texture analysis and the assumptions behind them.
- You have very good knowledge of object shape representation and description.
- You can apply the theory and the linear algebra behind central methods for supervised classification of images, in particular Gaussian classifiers.
- You understand the concept of curse-of-dimensionality and can use the theory in practice to carefully choose a subset of features and control the complexity of the classifier robustly.
- You can use the theory behind central methods for feature selection and linear feature transforms.
Admission to the course
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
IN1010 – Object-oriented Programming/IN1910 – Programming with Scientific Applications, IN1000 – Introduction to Object-oriented Programming/IN1900 – Introduction to Programming with Scientific Applications, IN2070 – Digital Image Processing (continued), MAT1110 – Calculus and Linear Algebra
Overlapping courses
- 10 credits overlap with IN5520 – Digital Image Analysis (discontinued).
- 10 credits overlap with INF4300 – Digital image analysis (continued).
- 10 credits overlap with INF9305 – Digital Image Analysis (continued).
- 5 credits overlap with INF9305 – Digital Image Analysis (continued).
Teaching
2 hours of lectures and 2 hours of exercises each week. You must get all mandatory assignments approved before the exam. PhD-students are given an extended mandatory project.
Examination
Oral or written exam (4 hours) dependent on the number of student. PhD students are given additional exercises.
All mandatory assignments must be approved prior to the exam.
It will also be counted as one of?your three?attempts to sit the exam for this course, if you sit the exam for one of the following courses: IN5520 – Digital Image Analysis (discontinued), INF4300 – Digital image analysis (continued), INF9305 – Digital Image Analysis (continued)
Examination support material
Language of examination
You may write your examination paper in Norwegian, Swedish, Danish or English.
Grading scale
Grades are awarded on a pass/fail scale. Read more about the grading system.
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.
More about examinations at UiO
- Use of sources and citations
- Special exam arrangements due to individual needs
- Withdrawal from an exam
- Illness at exams / postponed exams
- Explanation of grades and appeals
- Resitting an exam
- Cheating/attempted cheating
You will find further guides and resources at the web page on examinations at UiO.