Course detail

Image Processing

FIT-ZPOAcad. year: 2018/2019

Introduction to image processing, image acquiring, point and discrete image transforms, linear image filtering, image distortions, types of noise, optimal image filtering, non-linear image filtering, watermarks, edge detection, segmentation, motion analysis, loseless and lossy image compression

Language of instruction

Czech, English

Number of ECTS credits

Mode of study

Not applicable.

Guarantor

prof. Dr. Ing. Pavel Zemčík, dr. h. c.

Department

Department of Computer Graphics and Multimedia (UPGM)

Learning outcomes of the course unit

The students will get acquainted with the image processing basics theory (transformations, filtration, noise reduction, etc.). They will learn how to apply such knowledge on real examples of image processing tasks. They will also get acquainted with "higher" imaging algorithms. Finally, they will learn how to practically program image processing applications through projects.
Students will improve their teamwork skills and in exploitation of "C" language.

Prerequisites


Programming language C, basic knowledge of computer graphics, mathematical
analysis and linear algebra.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

Mid-term test, individual project.

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

To get acquainted with the image processing basics theory (transformations, filtration, noise reduction, etc.). To learn how to apply such knowledge on real examples of image processing tasks. To get acquainted with "higher" imaging algorithms. To learn kow to practically program image processing applications through projects.

Specification of controlled education, way of implementation and compensation for absences

Not applicable.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Basic literature

Hlaváč, V., Šonka, M.: Počítačové vidění, GRADA 1992, ISBN 80-85424-67-3 Jahne, B.: Handbook of Computer Vision and Applications, Academic Press, 1999, ISBN 0-12-379770-5 Russ, J.C.: The Image Processing Handbook, CRC Press 1995, ISBM 0-8493-2516-1

Recommended reading

Hlaváč, V., Šonka, M.: Počítačové vidění, GRADA 1992, ISBN 80-85424-67-3
Jahne, B.: Handbook of Computer Vision and Applications, Academic Press, 1999, ISBN 0-12-379770-5
Russ, J.C.: The Image Processing Handbook, CRC Press 1995, ISBM 0-8493-2516-1

Classification of course in study plans

  • Programme IT-MSC-2 Master's

    branch MMI , 1 year of study, summer semester, compulsory
    branch MBI , 0 year of study, summer semester, elective
    branch MSK , 0 year of study, summer semester, elective
    branch MMM , 0 year of study, summer semester, elective
    branch MBS , 0 year of study, summer semester, elective
    branch MPV , 0 year of study, summer semester, compulsory-optional
    branch MIS , 0 year of study, summer semester, elective
    branch MIN , 0 year of study, summer semester, elective
    branch MGM , 1 year of study, summer semester, compulsory

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

doc. Ing. Vítězslav Beran, Ph.D.
Ing. David Bařina, Ph.D.
prof. Dr. Ing. Pavel Zemčík, dr. h. c.
doc. Ing. Michal Španěl, Ph.D.
Ing. Svetozár Nosko, Ph.D.

Syllabus

  1. Introduction, representation of image, linear filtration  (8. 2. 2019 Zemčík slides, slides, demo)
  2. Image acquisition (15. 2. 2019 Zemčík? slides)
  3. Discrete image transforms, FFT, relationship with filtering(Zemčík 22. 2. 2019 slajdy a slides)
  4. Point image transforms (1. 3. 2019 Beran slides, demo.zip)
  5. Edge detection, segmentation (8. 3. 2019 Beran slides, examples)
  6. Resampling, warping, morphing (15. 3. 2019 Zemčík slides)
  7. DCT, Wavelets (22. 3. 2019 Bařina slides)
  8. Watermarks (29. 3. 2019 Mlích slides, demo)
  9. Test + project status presentation (5. 4. 2019 Beran)
  10. Image distortion, types of noise, optimal filtration (12. 4. 2019 Španěl slides)
  11. no lecture - Good Friday (19. 4. 2019)
  12. Project defences + misc. (26. 4. 2019 Beran)
  13. Matematical morphology, motion analysis, conclusion (3.5. Španěl slides)

Project

26 hod., compulsory

Teacher / Lecturer

doc. Ing. Vítězslav Beran, Ph.D.

Syllabus

  1. Individually assigned project for the whole duration of the course.