Course detail

Image Processing

FIT-ZPOAcad. year: 2017/2018

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

Number of ECTS credits

5

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

The C programming language and fundamentals of computer graphics.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

Study evaluation is based on marks obtained for specified items. Minimimum number of marks to pass is 50.

Course curriculum

Syllabus of lectures:
  1. Introduction to image processing
  2. Image data acquiring
  3. Point image transforms
  4. Discrete image transforms
  5. Linear image filtering
  6. Image distortion, types of noise
  7. Optimal filtering
  8. Nonlinear image filtering
  9. Watermarks
  10. Edge detection, segmentation
  11. Movement analysis
  12. Image compression, lossy, looseless
  13. Future of image processing

Syllabus - others, projects and individual work of students:
  1. Individually assigned project for the whole duration of the course.

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

Mid-term test, individual project.

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

Classification of course in study plans

  • Programme IT-MGR-2 Master's

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