Valid for: 2014/15
Decided by: Education Board B
Date of Decision: 2014-04-08
Elective for: BME4-sbh, BME4-br, C5, D4-bg, E4-mt, E4-bg, F4, F4-bg, F4-bm, L5-gi, Pi4-bg, Pi4-biek
Language of instruction: The course will be given in English on demand
The main aim of the course is to give a basic introduction to theory and mathematical methods used in image analysis, to an extent that will allow the student to handle industrial image processing problems. In addition the aim is to help the student develop his or her ability in problem solving, both with or without a computer. A further aim is to prepare the student for further studies in e.g. computer vision, multispectral image analysis and statistical image analysis.
Knowledge and understanding
For a passing grade the student must
Competences and skills
For a passing grade the student must
Basic mathematical concepts: Image transforms, DFT, FFT.
Image enhancement: Grey level transforms, filtering.
Image restoration: Filterings, inverse methods.
Scale space theory: Continuous versus discrete theory, interpolation.
Extraction of special features: Filtering, edge and corner detection.
Segmentation: graph-methods, active contours, mathematical morphology.
Bayesian image handling: MAP estimations, simulation.
Pattern recognition: Classification, SVM, PCA, learning.
Registration
Machine Learning: Training, testing, generalization, hypothesis spaces.
Grading scale: TH
Assessment: Compulsory computer exercises and assignments. Approved results on these are enough to pass the course. To get a higher grade, a written or oral test is required.
Parts
Code: 0114. Name: Image Analysis, Theory Course.
Credits: 7,5. Grading scale: TH.
Code: 0214. Name: Image Analysis, Laboratory Work.
Credits: 0. Grading scale: UG.
Required prior knowledge: FMAF05 Systems and Transforms, or equivalent (for example FMAF10 Applied Mathematics - Linear Systems).
The number of participants is limited to: No
The course overlaps following course/s: FMA170, FMA172
Course coordinator: Anders Holst, studierektor@math.lth.se
Course homepage: http://www.ctr.maths.lu.se/course/imagean/2013/