Faculty of Information Technology, BUT

Course details

Image Processing

ZPO Acad. year 2019/2020 Summer semester 5 credits

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

Guarantor

Deputy Guarantor

Language of instruction

Czech

Completion

Examination (written)

Time span

26 hrs lectures, 26 hrs projects

Assessment points

51 exam, 10 half-term test, 39 projects

Department

Lecturer

Instructor

Subject specific learning outcomes and competences

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.

Generic learning outcomes and competences

Students will improve their teamwork skills and in exploitation of "C" language.

Learning objectives

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.

Why is the course taught

Prerequisites

Prerequisite kwnowledge and skills

The C programming language and fundamentals of computer graphics.

Study literature

  • Russ, J.C.: The Image Processing Handbook, CRC Press 1995, ISBM 0-8493-2516-1 
  • Šonka, M., Hlaváč, V., Boyle, R.: Image processing, Analysis, and Machine Vision, THOMSON 2013, ISBN-13: 978-9386858146
  • Jahne, B.: Handbook of Computer Vision and Applications, Academic Press, 1999, ISBN 0-12-379770-5

Fundamental literature

  • Hlaváč, V., Šonka, M.: Počítačové vidění, GRADA 1992, ISBN 80-85424-67-3
  • Šonka, M., Hlaváč, V., Boyle, R.: Image processing, Analysis, and Machine Vision, THOMSON 2013, ISBN-13: 978-9386858146
  • IEEE Multimedia, IEEE, USA - série časopisů - různé články
  • 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

Syllabus of lectures

  1. Introduction, representation of image
  2. Linear filtration
  3. Image acquisition
  4. Discrete image transforms, FFT, relationship with filtering
  5. Point image transforms
  6. Edge detection, segmentation
  7. Resampling, warping, morphing
  8. DCT, Wavelets
  9. Watermarks
  10. Image distortion, types of noise
  11. Optimal filtration
  12. Mathematical Morphology
  13. Motion analysis, conclusion

Syllabus - others, projects and individual work of students

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

Progress assessment

Mid-term test, project (homeworks and individual project).

Schedule

DayTypeWeeksRoomStartEndLect.grpGroupsInfo
Frilecturelectures E112 12:0013:50 1MIT 2MIT MGM MMI xx

Course inclusion in study plans

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