Course details

Image Processing

ZPO Acad. year 2023/2024 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

Course coordinator

Language of instruction

Czech, English

Completion

Examination (written)

Time span

  • 26 hrs lectures
  • 26 hrs projects

Assessment points

  • 51 pts final exam
  • 10 pts mid-term test
  • 39 pts projects

Department

Lecturer

Instructor

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.
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.

Recommended prerequisites

Prerequisite knowledge and skills

The C programming language and fundamentals of computer graphics.

Study 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
  • Bradski, G., Kaehler, A.: Learning OpenCV: Computer Vision with the OpenCV Library, OReilly 2008, ISBN: 978-0596516130

Fundamental 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

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

DayTypeWeeksRoomStartEndCapacityLect.grpGroupsInfo
Mon exam 2024-05-20 E104 15:0016:50 1. termín
Wed exam 2024-05-29 E105 15:0016:50 2. termín
Thu lecture 2., 3., 4., 10., 11. of lectures A112 12:0013:5064 1MIT 2MIT NISY NVIZ xx Zemčík
Thu lecture 6., 7., 8., 12., 13. of lectures A112 12:0013:5064 1MIT 2MIT NISY NVIZ xx Beran
Thu lecture 2024-02-08 A112 12:0013:5064 1MIT 2MIT NISY NVIZ xx Nosko
Thu lecture 2024-03-07 A112 12:0013:5064 1MIT 2MIT NISY NVIZ xx Španěl
Thu lecture 2024-04-04 A112 12:0013:5064 1MIT 2MIT NISY NVIZ xx Bařina
Thu exam 2024-06-06 E104 13:0014:50 3. termín

Course inclusion in study plans

Back to top